diff --git a/docs/source/api/api.rst b/docs/source/api/api.rst index 01a11638a..2c28eaa16 100644 --- a/docs/source/api/api.rst +++ b/docs/source/api/api.rst @@ -11,5 +11,4 @@ API Documentation spatial-functions spatial-indexing spatial-predicates - spatial-aggregations - raster-functions \ No newline at end of file + spatial-aggregations \ No newline at end of file diff --git a/docs/source/index.rst b/docs/source/index.rst index fe1ec92c9..3bf3e1ce5 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -5,8 +5,16 @@ .. image:: images/mosaic_logo.png :alt: mosaic +<<<<<<< HEAD + :align: left +| +.. image:: https://badge.fury.io/py/databricks-mosaic.svg + :target: https://badge.fury.io/py/databricks-mosaic + :alt: PyPI Version +======= :class: mosaic-logo +>>>>>>> databrickslabs-main .. container:: package_health diff --git a/docs/source/usage/grid-indexes.ipynb b/docs/source/usage/grid-indexes.ipynb index 6690c7ae0..6d39eb993 100644 --- a/docs/source/usage/grid-indexes.ipynb +++ b/docs/source/usage/grid-indexes.ipynb @@ -2,495 +2,391 @@ "cells": [ { "cell_type": "markdown", - "source": [ - "# Using grid index systems in Mosaic" - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "1deecb01-8ded-4750-a112-5847e410846b" + "nuid": "1deecb01-8ded-4750-a112-5847e410846b", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "# Using grid index systems in Mosaic" + ] }, { "cell_type": "code", - "source": [ - "from pyspark.sql.functions import *\nfrom mosaic import enable_mosaic\nenable_mosaic(spark, dbutils)" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "f6311e22-f0a8-4025-b612-4367b5f1cac2" + "nuid": "f6311e22-f0a8-4025-b612-4367b5f1cac2", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "from pyspark.sql.functions import *\n", + "from mosaic import enable_mosaic\n", + "enable_mosaic(spark, dbutils)" + ] }, { "cell_type": "markdown", - "source": [ - "Set operations over big geospatial datasets become very expensive without some form of spatial indexing.\n\nSpatial indexes not only allow operations like point-in-polygon joins to be partitioned but, if only approximate results are required, can be used to reduce these to deterministic SQL joins directly on the indexes." - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "e5603057-662b-4bf3-9517-84b35ad7a8b5" + "nuid": "e5603057-662b-4bf3-9517-84b35ad7a8b5", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "Set operations over big geospatial datasets become very expensive without some form of spatial indexing.\n", + "\n", + "Spatial indexes not only allow operations like point-in-polygon joins to be partitioned but, if only approximate results are required, can be used to reduce these to deterministic SQL joins directly on the indexes." + ] }, { "cell_type": "markdown", - "source": [ - "![example h3 point-in-poly image](https://databricks.com/wp-content/uploads/2021/01/blog-geospatial-3.jpg)" - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "c8199fdd-1372-43a4-8edf-f96129f4195a" + "nuid": "c8199fdd-1372-43a4-8edf-f96129f4195a", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "![example h3 point-in-poly image](https://databricks.com/wp-content/uploads/2021/01/blog-geospatial-3.jpg)" + ] }, { "cell_type": "markdown", - "source": [ - "The workflow for a point-in-poly spatial join might look like the following:" - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "39e3cf64-61c9-4930-be5e-91b254cf0984" + "nuid": "39e3cf64-61c9-4930-be5e-91b254cf0984", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "The workflow for a point-in-poly spatial join might look like the following:" + ] }, { "cell_type": "markdown", - "source": [ - "## 1. Read the source point and polygon datasets." - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "947d6e33-06b5-4ea0-bc55-0fdb5b8e8524" + "nuid": "947d6e33-06b5-4ea0-bc55-0fdb5b8e8524", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "## 1. Read the source point and polygon datasets." + ] }, { "cell_type": "code", - "source": [ - "drop_cols = [\n \"rate_code_id\", \"store_and_fwd_flag\", \"dropoff_longitude\",\n \"dropoff_latitude\", \"payment_type\", \"fare_amount\",\n \"extra\", \"mta_tax\", \"tip_amount\", \"tolls_amount\",\n \"total_amount\"\n]\n\ntrips = (\n spark.table(\"delta.`/databricks-datasets/nyctaxi/tables/nyctaxi_yellow`\")\n .drop(*drop_cols)\n .limit(5_000_000)\n .repartition(sc.defaultParallelism * 20)\n)\n\ntrips.show()" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "f1474a53-da53-4955-b944-083fdf3a22a1" + "nuid": "f1474a53-da53-4955-b944-083fdf3a22a1", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+\n|vendor_id| pickup_datetime| dropoff_datetime|passenger_count|trip_distance|pickup_longitude|pickup_latitude|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+\n| CMT|2009-01-01 20:07:33|2009-01-01 20:12:28| 1| 0.8| -74.001041| 40.731|\n| CMT|2009-01-06 15:29:12|2009-01-06 15:51:57| 2| 3.3| -73.996489| 40.725742|\n| CMT|2010-02-14 17:42:16|2010-02-14 17:55:03| 1| 3.4| -74.002949| 40.734254|\n| CMT|2010-02-11 18:19:01|2010-02-11 18:27:54| 1| 1.5| -73.998133| 40.682463|\n| VTS|2009-04-29 12:26:00|2009-04-29 12:35:00| 3| 2.05| -74.001332| 40.72006|\n| VTS|2009-04-24 15:03:00|2009-04-24 15:23:00| 2| 2.89| -73.989952| 40.734625|\n| CMT|2010-02-28 13:55:44|2010-02-28 14:02:37| 1| 1.2| -74.006015| 40.735279|\n| VTS|2009-09-27 08:46:00|2009-09-27 08:59:00| 1| 3.97| -74.000148| 40.717468|\n| CMT|2010-02-18 09:48:52|2010-02-18 10:08:38| 1| 3.0| -73.995177| 40.725297|\n| CMT|2009-04-09 20:33:44|2009-04-09 20:39:33| 2| 0.6| -73.990133| 40.729321|\n| CMT|2010-02-13 22:41:10|2010-02-13 23:07:04| 1| 4.2| -74.009175| 40.706284|\n| CMT|2009-01-25 20:06:51|2009-01-25 20:12:37| 1| 1.3| -74.007384| 40.717929|\n| VTS|2010-02-27 18:19:00|2010-02-27 18:38:00| 1| 4.2| -74.011512| 40.710588|\n| VTS|2010-02-15 10:17:00|2010-02-15 10:24:00| 1| 1.74| -74.016442| 40.711617|\n| CMT|2009-12-26 18:45:49|2009-12-26 18:59:08| 1| 4.8| -74.01014| 40.712263|\n| CMT|2009-12-06 01:00:07|2009-12-06 01:11:41| 2| 4.2| -74.002505| 40.729001|\n| VTS|2009-10-04 14:36:00|2009-10-04 14:42:00| 1| 1.13| -74.006767| 40.718942|\n| CMT|2009-01-18 00:20:50|2009-01-18 00:36:29| 3| 2.1| -73.993258| 40.721401|\n| VTS|2009-05-18 13:24:00|2009-05-18 13:33:00| 1| 1.91| -73.992785| 40.730412|\n| VTS|2009-11-11 21:51:00|2009-11-11 22:13:00| 5| 4.71| -74.010065| 40.733383|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+\nonly showing top 20 rows\n\n
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+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+\nvendor_id| pickup_datetime| dropoff_datetime|passenger_count|trip_distance|pickup_longitude|pickup_latitude|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+\n CMT|2009-01-01 20:07:33|2009-01-01 20:12:28| 1| 0.8| -74.001041| 40.731|\n CMT|2009-01-06 15:29:12|2009-01-06 15:51:57| 2| 3.3| -73.996489| 40.725742|\n CMT|2010-02-14 17:42:16|2010-02-14 17:55:03| 1| 3.4| -74.002949| 40.734254|\n CMT|2010-02-11 18:19:01|2010-02-11 18:27:54| 1| 1.5| -73.998133| 40.682463|\n VTS|2009-04-29 12:26:00|2009-04-29 12:35:00| 3| 2.05| -74.001332| 40.72006|\n VTS|2009-04-24 15:03:00|2009-04-24 15:23:00| 2| 2.89| -73.989952| 40.734625|\n CMT|2010-02-28 13:55:44|2010-02-28 14:02:37| 1| 1.2| -74.006015| 40.735279|\n VTS|2009-09-27 08:46:00|2009-09-27 08:59:00| 1| 3.97| -74.000148| 40.717468|\n CMT|2010-02-18 09:48:52|2010-02-18 10:08:38| 1| 3.0| -73.995177| 40.725297|\n CMT|2009-04-09 20:33:44|2009-04-09 20:39:33| 2| 0.6| -73.990133| 40.729321|\n CMT|2010-02-13 22:41:10|2010-02-13 23:07:04| 1| 4.2| -74.009175| 40.706284|\n CMT|2009-01-25 20:06:51|2009-01-25 20:12:37| 1| 1.3| -74.007384| 40.717929|\n VTS|2010-02-27 18:19:00|2010-02-27 18:38:00| 1| 4.2| -74.011512| 40.710588|\n VTS|2010-02-15 10:17:00|2010-02-15 10:24:00| 1| 1.74| -74.016442| 40.711617|\n CMT|2009-12-26 18:45:49|2009-12-26 18:59:08| 1| 4.8| -74.01014| 40.712263|\n CMT|2009-12-06 01:00:07|2009-12-06 01:11:41| 2| 4.2| -74.002505| 40.729001|\n VTS|2009-10-04 14:36:00|2009-10-04 14:42:00| 1| 1.13| -74.006767| 40.718942|\n CMT|2009-01-18 00:20:50|2009-01-18 00:36:29| 3| 2.1| -73.993258| 40.721401|\n VTS|2009-05-18 13:24:00|2009-05-18 13:33:00| 1| 1.91| -73.992785| 40.730412|\n VTS|2009-11-11 21:51:00|2009-11-11 22:13:00| 5| 4.71| -74.010065| 40.733383|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+\nonly showing top 20 rows\n\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "drop_cols = [\n", + " \"rate_code_id\", \"store_and_fwd_flag\", \"dropoff_longitude\",\n", + " \"dropoff_latitude\", \"payment_type\", \"fare_amount\",\n", + " \"extra\", \"mta_tax\", \"tip_amount\", \"tolls_amount\",\n", + " \"total_amount\"\n", + "]\n", + "\n", + "trips = (\n", + " spark.table(\"delta.`/databricks-datasets/nyctaxi/tables/nyctaxi_yellow`\")\n", + " .drop(*drop_cols)\n", + " .limit(5_000_000)\n", + " .repartition(sc.defaultParallelism * 20)\n", + ")\n", + "\n", + "trips.show()" + ] }, { "cell_type": "code", - "source": [ - "from mosaic import st_geomfromgeojson\n\nuser = spark.sql(\"select current_user() as user\").collect()[0][\"user\"]\n\nneighbourhoods = (\n spark.read.format(\"json\")\n .load(f\"dbfs:/FileStore/shared_uploads/{user}/NYC_Taxi_Zones.geojson\")\n .repartition(sc.defaultParallelism)\n .withColumn(\"geometry\", st_geomfromgeojson(to_json(col(\"geometry\"))))\n .select(\"properties.*\", \"geometry\")\n .drop(\"shape_area\", \"shape_leng\")\n)\n\nneighbourhoods.show()" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "e3a366bf-4d60-4356-8b7b-eedb0beabc8d" + "nuid": "e3a366bf-4d60-4356-8b7b-eedb0beabc8d", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
+-------------+-----------+--------+-------------------+--------------------+\n| borough|location_id|objectid| zone| geometry|\n+-------------+-----------+--------+-------------------+--------------------+\n| Brooklyn| 123| 123| Homecrest|{6, 4326, [[[-73....|\n| Manhattan| 153| 153| Marble Hill|{6, 4326, [[[-73....|\n| Brooklyn| 112| 112| Greenpoint|{6, 4326, [[[-73....|\n| Manhattan| 233| 233|UN/Turtle Bay South|{6, 4326, [[[-73....|\n| Manhattan| 43| 43| Central Park|{6, 4326, [[[-73....|\n| Queens| 201| 201| Rockaway Park|{6, 4326, [[[-73....|\n| Queens| 131| 131| Jamaica Estates|{6, 4326, [[[-73....|\n| Brooklyn| 111| 111|Green-Wood Cemetery|{6, 4326, [[[-73....|\n| Queens| 226| 226| Sunnyside|{6, 4326, [[[-73....|\n| Queens| 129| 129| Jackson Heights|{6, 4326, [[[-73....|\n| Manhattan| 120| 120| Highbridge Park|{6, 4326, [[[-73....|\n| Brooklyn| 76| 76| East New York|{6, 4326, [[[-73....|\n| Manhattan| 24| 24| Bloomingdale|{6, 4326, [[[-73....|\n| Manhattan| 202| 202| Roosevelt Island|{6, 4326, [[[-73....|\n| Manhattan| 100| 100| Garment District|{6, 4326, [[[-73....|\n|Staten Island| 251| 251| Westerleigh|{6, 4326, [[[-74....|\n| Manhattan| 74| 74| East Harlem North|{6, 4326, [[[-73....|\n| Queens| 98| 98| Fresh Meadows|{6, 4326, [[[-73....|\n| Manhattan| 211| 211| SoHo|{6, 4326, [[[-74....|\n| Bronx| 174| 174| Norwood|{6, 4326, [[[-73....|\n+-------------+-----------+--------+-------------------+--------------------+\nonly showing top 20 rows\n\n
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+-------------+-----------+--------+-------------------+--------------------+\n borough|location_id|objectid| zone| geometry|\n+-------------+-----------+--------+-------------------+--------------------+\n Brooklyn| 123| 123| Homecrest|{6, 4326, [[[-73....|\n Manhattan| 153| 153| Marble Hill|{6, 4326, [[[-73....|\n Brooklyn| 112| 112| Greenpoint|{6, 4326, [[[-73....|\n Manhattan| 233| 233|UN/Turtle Bay South|{6, 4326, [[[-73....|\n Manhattan| 43| 43| Central Park|{6, 4326, [[[-73....|\n Queens| 201| 201| Rockaway Park|{6, 4326, [[[-73....|\n Queens| 131| 131| Jamaica Estates|{6, 4326, [[[-73....|\n Brooklyn| 111| 111|Green-Wood Cemetery|{6, 4326, [[[-73....|\n Queens| 226| 226| Sunnyside|{6, 4326, [[[-73....|\n Queens| 129| 129| Jackson Heights|{6, 4326, [[[-73....|\n Manhattan| 120| 120| Highbridge Park|{6, 4326, [[[-73....|\n Brooklyn| 76| 76| East New York|{6, 4326, [[[-73....|\n Manhattan| 24| 24| Bloomingdale|{6, 4326, [[[-73....|\n Manhattan| 202| 202| Roosevelt Island|{6, 4326, [[[-73....|\n Manhattan| 100| 100| Garment District|{6, 4326, [[[-73....|\nStaten Island| 251| 251| Westerleigh|{6, 4326, [[[-74....|\n Manhattan| 74| 74| East Harlem North|{6, 4326, [[[-73....|\n Queens| 98| 98| Fresh Meadows|{6, 4326, [[[-73....|\n Manhattan| 211| 211| SoHo|{6, 4326, [[[-74....|\n Bronx| 174| 174| Norwood|{6, 4326, [[[-73....|\n+-------------+-----------+--------+-------------------+--------------------+\nonly showing top 20 rows\n\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "from mosaic import st_geomfromgeojson\n", + "\n", + "user = spark.sql(\"select current_user() as user\").collect()[0][\"user\"]\n", + "\n", + "neighbourhoods = (\n", + " spark.read.format(\"json\")\n", + " .load(f\"dbfs:/FileStore/shared_uploads/{user}/NYC_Taxi_Zones.geojson\")\n", + " .repartition(sc.defaultParallelism)\n", + " .withColumn(\"geometry\", st_geomfromgeojson(to_json(col(\"geometry\"))))\n", + " .select(\"properties.*\", \"geometry\")\n", + " .drop(\"shape_area\", \"shape_leng\")\n", + ")\n", + "\n", + "neighbourhoods.show()" + ] }, { "cell_type": "markdown", - "source": [ - "## 2. Compute the resolution of index required to optimize the join." - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "ae8cc184-574e-458f-9613-d2225b7a73e8" + "nuid": "ae8cc184-574e-458f-9613-d2225b7a73e8", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "## 2. Compute the resolution of index required to optimize the join." + ] }, { "cell_type": "code", - "source": [ - "from mosaic import MosaicFrame\n\nneighbourhoods_mdf = MosaicFrame(neighbourhoods, \"geometry\")\nhelp(neighbourhoods_mdf.get_optimal_resolution)" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "08dc48c1-9da2-4f8a-a233-aae456cac972" + "nuid": "08dc48c1-9da2-4f8a-a233-aae456cac972", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
Help on method get_optimal_resolution in module mosaic.core.mosaic_frame:\n\nget_optimal_resolution(sample_rows: Union[int, NoneType] = None, sample_fraction: Union[float, NoneType] = None) -> int method of mosaic.core.mosaic_frame.MosaicFrame instance\n Analyzes the geometries in the currently selected geometry column and proposes an optimal\n grid-index resolution.\n \n Provide either `sample_rows` or `sample_fraction` parameters to control how much data is passed to the analyzer.\n (Providing too little data to the analyzer may result in a `NotEnoughGeometriesException`)\n \n Parameters\n ----------\n sample_rows: int, optional\n The number of rows to sample.\n sample_fraction: float, optional\n The proportion of rows to sample.\n \n Returns\n -------\n int\n The recommended grid-index resolution to apply to this MosaicFrame.\n\n
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Help on method get_optimal_resolution in module mosaic.core.mosaic_frame:\n\nget_optimal_resolution(sample_rows: Union[int, NoneType] = None, sample_fraction: Union[float, NoneType] = None) -> int method of mosaic.core.mosaic_frame.MosaicFrame instance\n Analyzes the geometries in the currently selected geometry column and proposes an optimal\n grid-index resolution.\n \n Provide either `sample_rows` or `sample_fraction` parameters to control how much data is passed to the analyzer.\n (Providing too little data to the analyzer may result in a `NotEnoughGeometriesException`)\n \n Parameters\n ----------\n sample_rows: int, optional\n The number of rows to sample.\n sample_fraction: float, optional\n The proportion of rows to sample.\n \n Returns\n -------\n int\n The recommended grid-index resolution to apply to this MosaicFrame.\n\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "from mosaic import MosaicFrame\n", + "\n", + "neighbourhoods_mdf = MosaicFrame(neighbourhoods, \"geometry\")\n", + "help(neighbourhoods_mdf.get_optimal_resolution)" + ] }, { "cell_type": "code", - "source": [ - "(resolution := neighbourhoods_mdf.get_optimal_resolution(sample_fraction=1.))" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "50ed9fb7-3521-40fe-856c-8d5ed9b182d3" + "nuid": "50ed9fb7-3521-40fe-856c-8d5ed9b182d3", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
Out[15]: 9
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Out[15]: 9
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "(resolution := neighbourhoods_mdf.get_optimal_resolution(sample_fraction=1.))" + ] }, { "cell_type": "markdown", - "source": [ - "## 3. Apply the index to the set of points in your left-hand dataframe.\nThis will generate an index value that corresponds to the grid ‘cell’ that this point occupies." - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "fccff6d5-da76-44c6-b015-749d3dcad3ca" + "nuid": "fccff6d5-da76-44c6-b015-749d3dcad3ca", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "## 3. Apply the index to the set of points in your left-hand dataframe.\n", + "This will generate an index value that corresponds to the grid ‘cell’ that this point occupies." + ] }, { "cell_type": "code", - "source": [ - "from mosaic import grid_longlatascellid\nindexed_trips = trips.withColumn(\"ix\", grid_longlatascellid(lon=\"pickup_longitude\", lat=\"pickup_latitude\", resolution=lit(resolution)))\nindexed_trips.show()" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "aad98fce-a22b-47d0-961d-62007acc23dd" + "nuid": "aad98fce-a22b-47d0-961d-62007acc23dd", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------------+\n|vendor_id| pickup_datetime| dropoff_datetime|passenger_count|trip_distance|pickup_longitude|pickup_latitude| ix|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------------+\n| DDS|2009-01-17 18:49:57|2009-01-17 18:56:29| 3| 1.2| -74.004043| 40.733409|617733151092113407|\n| DDS|2009-12-01 00:47:52|2009-12-01 01:00:16| 1| 3.4| -73.991702| 40.726342|617733151087132671|\n| CMT|2009-02-09 16:50:21|2009-02-09 17:02:47| 1| 2.6| -73.999673| 40.733586|617733123805806591|\n| CMT|2009-12-07 07:15:47|2009-12-07 07:32:07| 1| 3.8| -74.01211| 40.716893|617733151084773375|\n| VTS|2009-10-16 22:02:00|2009-10-16 22:08:00| 1| 1.1| -74.010903| 40.71624|617733151084773375|\n| VTS|2009-12-23 22:13:00|2009-12-23 22:18:00| 1| 0.37| -74.002343| 40.73366|617733151092113407|\n| VTS|2009-12-12 01:24:00|2009-12-12 01:38:00| 2| 3.55| -74.002565| 40.728188|617733151091326975|\n| CMT|2009-12-07 13:10:37|2009-12-07 13:13:45| 1| 0.5| -73.999184| 40.73428|617733123805806591|\n| CMT|2009-11-08 22:20:44|2009-11-08 22:31:23| 1| 1.9| -74.003029| 40.733385|617733151092113407|\n| VTS|2009-12-27 20:01:00|2009-12-27 20:04:00| 1| 1.04| -74.000227| 40.732603|617733151092375551|\n| VTS|2009-02-13 14:33:00|2009-02-13 14:50:00| 3| 1.59| -74.006535| 40.732303|617733151092637695|\n| CMT|2009-11-15 21:13:32|2009-11-15 21:25:56| 3| 3.0| -73.998795| 40.730621|617733151092375551|\n| VTS|2009-01-08 18:13:00|2009-01-08 18:33:00| 2| 4.18| -74.0079| 40.712012|617733151021334527|\n| CMT|2009-11-30 13:30:13|2009-11-30 13:41:55| 1| 1.6| -74.004487| 40.734072|617733151092637695|\n| CMT|2009-01-11 20:02:22|2009-01-11 20:08:15| 1| 1.0| -74.004493| 40.713349|617733151020810239|\n| CMT|2009-12-30 18:46:08|2009-12-30 19:02:23| 1| 2.3| -74.010798| 40.716717|617733151084773375|\n| CMT|2009-11-18 21:50:12|2009-11-18 22:05:19| 1| 5.8| -73.992515| 40.694106|617733151038111743|\n| VTS|2009-11-21 12:51:00|2009-11-21 13:27:00| 1| 14.18| -73.9923| 40.715218|617733151109414911|\n| CMT|2009-01-20 09:34:49|2009-01-20 09:37:15| 1| 0.4| -74.0027| 40.733479|617733151092113407|\n| VTS|2009-01-03 07:07:00|2009-01-03 07:18:00| 1| 7.81| -73.994358| 40.690345|617733151037325311|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------------+\nonly showing top 20 rows\n\n
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------------+\nvendor_id| pickup_datetime| dropoff_datetime|passenger_count|trip_distance|pickup_longitude|pickup_latitude| ix|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------------+\n DDS|2009-01-17 18:49:57|2009-01-17 18:56:29| 3| 1.2| -74.004043| 40.733409|617733151092113407|\n DDS|2009-12-01 00:47:52|2009-12-01 01:00:16| 1| 3.4| -73.991702| 40.726342|617733151087132671|\n CMT|2009-02-09 16:50:21|2009-02-09 17:02:47| 1| 2.6| -73.999673| 40.733586|617733123805806591|\n CMT|2009-12-07 07:15:47|2009-12-07 07:32:07| 1| 3.8| -74.01211| 40.716893|617733151084773375|\n VTS|2009-10-16 22:02:00|2009-10-16 22:08:00| 1| 1.1| -74.010903| 40.71624|617733151084773375|\n VTS|2009-12-23 22:13:00|2009-12-23 22:18:00| 1| 0.37| -74.002343| 40.73366|617733151092113407|\n VTS|2009-12-12 01:24:00|2009-12-12 01:38:00| 2| 3.55| -74.002565| 40.728188|617733151091326975|\n CMT|2009-12-07 13:10:37|2009-12-07 13:13:45| 1| 0.5| -73.999184| 40.73428|617733123805806591|\n CMT|2009-11-08 22:20:44|2009-11-08 22:31:23| 1| 1.9| -74.003029| 40.733385|617733151092113407|\n VTS|2009-12-27 20:01:00|2009-12-27 20:04:00| 1| 1.04| -74.000227| 40.732603|617733151092375551|\n VTS|2009-02-13 14:33:00|2009-02-13 14:50:00| 3| 1.59| -74.006535| 40.732303|617733151092637695|\n CMT|2009-11-15 21:13:32|2009-11-15 21:25:56| 3| 3.0| -73.998795| 40.730621|617733151092375551|\n VTS|2009-01-08 18:13:00|2009-01-08 18:33:00| 2| 4.18| -74.0079| 40.712012|617733151021334527|\n CMT|2009-11-30 13:30:13|2009-11-30 13:41:55| 1| 1.6| -74.004487| 40.734072|617733151092637695|\n CMT|2009-01-11 20:02:22|2009-01-11 20:08:15| 1| 1.0| -74.004493| 40.713349|617733151020810239|\n CMT|2009-12-30 18:46:08|2009-12-30 19:02:23| 1| 2.3| -74.010798| 40.716717|617733151084773375|\n CMT|2009-11-18 21:50:12|2009-11-18 22:05:19| 1| 5.8| -73.992515| 40.694106|617733151038111743|\n VTS|2009-11-21 12:51:00|2009-11-21 13:27:00| 1| 14.18| -73.9923| 40.715218|617733151109414911|\n CMT|2009-01-20 09:34:49|2009-01-20 09:37:15| 1| 0.4| -74.0027| 40.733479|617733151092113407|\n VTS|2009-01-03 07:07:00|2009-01-03 07:18:00| 1| 7.81| -73.994358| 40.690345|617733151037325311|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------------+\nonly showing top 20 rows\n\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "from mosaic import grid_longlatascellid\n", + "indexed_trips = trips.withColumn(\"ix\", grid_longlatascellid(lon=\"pickup_longitude\", lat=\"pickup_latitude\", resolution=lit(resolution)))\n", + "indexed_trips.show()" + ] }, { "cell_type": "markdown", - "source": [ - "## 4. Compute the set of indices that fully covers each polygon in the right-hand dataframe\nThis is commonly referred to as a polyfill operation." - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "e127e5be-30e4-4507-8aa9-59399290b8f7" + "nuid": "e127e5be-30e4-4507-8aa9-59399290b8f7", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "## 4. Compute the set of indices that fully covers each polygon in the right-hand dataframe\n", + "This is commonly referred to as a polyfill operation." + ] }, { "cell_type": "code", - "source": [ - "from mosaic import grid_polyfill\n\nindexed_neighbourhoods = (\n neighbourhoods\n .select(\"*\", grid_polyfill(\"geometry\", lit(resolution)).alias(\"ix_set\"))\n .drop(\"geometry\")\n)\n\nindexed_neighbourhoods.show()" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "06e1f722-8530-47c2-aec5-f0a6cb4f9301" + "nuid": "06e1f722-8530-47c2-aec5-f0a6cb4f9301", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
+-------------+-----------+--------+-------------------+--------------------+\n| borough|location_id|objectid| zone| ix_set|\n+-------------+-----------+--------+-------------------+--------------------+\n| Brooklyn| 123| 123| Homecrest|[6177331514226769...|\n| Manhattan| 153| 153| Marble Hill|[6177331229858201...|\n| Brooklyn| 112| 112| Greenpoint|[6177331237832622...|\n| Manhattan| 233| 233|UN/Turtle Bay South|[6177331238679347...|\n| Manhattan| 43| 43| Central Park|[6177331225792348...|\n| Queens| 201| 201| Rockaway Park|[6177331357831659...|\n| Queens| 131| 131| Jamaica Estates|[6177331242658693...|\n| Brooklyn| 111| 111|Green-Wood Cemetery|[6177331522277212...|\n| Queens| 226| 226| Sunnyside|[6177331238566625...|\n| Queens| 129| 129| Jackson Heights|[6177331243222302...|\n| Manhattan| 120| 120| Highbridge Park|[6177331231976325...|\n| Brooklyn| 76| 76| East New York|[6177331236938711...|\n| Manhattan| 24| 24| Bloomingdale|[6177331226458193...|\n| Manhattan| 202| 202| Roosevelt Island|[6177331237777571...|\n| Manhattan| 100| 100| Garment District|[6177331509717893...|\n|Staten Island| 251| 251| Westerleigh|[6177331466128588...|\n| Manhattan| 74| 74| East Harlem North|[6177331226508001...|\n| Queens| 98| 98| Fresh Meadows|[6177331242448977...|\n| Manhattan| 211| 211| SoHo|[6177331510784819...|\n| Bronx| 174| 174| Norwood|[6177331205497159...|\n+-------------+-----------+--------+-------------------+--------------------+\nonly showing top 20 rows\n\n
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
+-------------+-----------+--------+-------------------+--------------------+\n borough|location_id|objectid| zone| ix_set|\n+-------------+-----------+--------+-------------------+--------------------+\n Brooklyn| 123| 123| Homecrest|[6177331514226769...|\n Manhattan| 153| 153| Marble Hill|[6177331229858201...|\n Brooklyn| 112| 112| Greenpoint|[6177331237832622...|\n Manhattan| 233| 233|UN/Turtle Bay South|[6177331238679347...|\n Manhattan| 43| 43| Central Park|[6177331225792348...|\n Queens| 201| 201| Rockaway Park|[6177331357831659...|\n Queens| 131| 131| Jamaica Estates|[6177331242658693...|\n Brooklyn| 111| 111|Green-Wood Cemetery|[6177331522277212...|\n Queens| 226| 226| Sunnyside|[6177331238566625...|\n Queens| 129| 129| Jackson Heights|[6177331243222302...|\n Manhattan| 120| 120| Highbridge Park|[6177331231976325...|\n Brooklyn| 76| 76| East New York|[6177331236938711...|\n Manhattan| 24| 24| Bloomingdale|[6177331226458193...|\n Manhattan| 202| 202| Roosevelt Island|[6177331237777571...|\n Manhattan| 100| 100| Garment District|[6177331509717893...|\nStaten Island| 251| 251| Westerleigh|[6177331466128588...|\n Manhattan| 74| 74| East Harlem North|[6177331226508001...|\n Queens| 98| 98| Fresh Meadows|[6177331242448977...|\n Manhattan| 211| 211| SoHo|[6177331510784819...|\n Bronx| 174| 174| Norwood|[6177331205497159...|\n+-------------+-----------+--------+-------------------+--------------------+\nonly showing top 20 rows\n\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "from mosaic import grid_polyfill\n", + "\n", + "indexed_neighbourhoods = (\n", + " neighbourhoods\n", + " .select(\"*\", grid_polyfill(\"geometry\", lit(resolution)).alias(\"ix_set\"))\n", + " .drop(\"geometry\")\n", + ")\n", + "\n", + "indexed_neighbourhoods.show()" + ] }, { "cell_type": "markdown", - "source": [ - "## 5. ‘Explode’ the polygon index dataframe, such that each polygon index becomes a row in a new dataframe." - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "be2c88fd-9307-4b9a-ada8-fd714142d2d0" + "nuid": "be2c88fd-9307-4b9a-ada8-fd714142d2d0", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "## 5. ‘Explode’ the polygon index dataframe, such that each polygon index becomes a row in a new dataframe." + ] }, { "cell_type": "code", - "source": [ - "exploded_indexed_neighbourhoods = (\n indexed_neighbourhoods\n .withColumn(\"ix\", explode(\"ix_set\"))\n .drop(\"ix_set\")\n)\n\nexploded_indexed_neighbourhoods.show()" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "132de00e-753f-49d6-ab3f-82517eef296a" + "nuid": "132de00e-753f-49d6-ab3f-82517eef296a", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
+--------+-----------+--------+---------+------------------+\n| borough|location_id|objectid| zone| ix|\n+--------+-----------+--------+---------+------------------+\n|Brooklyn| 123| 123|Homecrest|617733151422676991|\n|Brooklyn| 123| 123|Homecrest|617733151503417343|\n|Brooklyn| 123| 123|Homecrest|617733151502893055|\n|Brooklyn| 123| 123|Homecrest|617733151502368767|\n|Brooklyn| 123| 123|Homecrest|617733151492407295|\n|Brooklyn| 123| 123|Homecrest|617733151488737279|\n|Brooklyn| 123| 123|Homecrest|617733151484542975|\n|Brooklyn| 123| 123|Homecrest|617733151484018687|\n|Brooklyn| 123| 123|Homecrest|617733151483494399|\n|Brooklyn| 123| 123|Homecrest|617733151425560575|\n|Brooklyn| 123| 123|Homecrest|617733151424511999|\n|Brooklyn| 123| 123|Homecrest|617733151423463423|\n|Brooklyn| 123| 123|Homecrest|617733151511019519|\n|Brooklyn| 123| 123|Homecrest|617733151505776639|\n|Brooklyn| 123| 123|Homecrest|617733151505252351|\n|Brooklyn| 123| 123|Homecrest|617733151504203775|\n|Brooklyn| 123| 123|Homecrest|617733151503679487|\n|Brooklyn| 123| 123|Homecrest|617733151503155199|\n|Brooklyn| 123| 123|Homecrest|617733151502630911|\n|Brooklyn| 123| 123|Homecrest|617733151502106623|\n+--------+-----------+--------+---------+------------------+\nonly showing top 20 rows\n\n
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
+--------+-----------+--------+---------+------------------+\n borough|location_id|objectid| zone| ix|\n+--------+-----------+--------+---------+------------------+\nBrooklyn| 123| 123|Homecrest|617733151422676991|\nBrooklyn| 123| 123|Homecrest|617733151503417343|\nBrooklyn| 123| 123|Homecrest|617733151502893055|\nBrooklyn| 123| 123|Homecrest|617733151502368767|\nBrooklyn| 123| 123|Homecrest|617733151492407295|\nBrooklyn| 123| 123|Homecrest|617733151488737279|\nBrooklyn| 123| 123|Homecrest|617733151484542975|\nBrooklyn| 123| 123|Homecrest|617733151484018687|\nBrooklyn| 123| 123|Homecrest|617733151483494399|\nBrooklyn| 123| 123|Homecrest|617733151425560575|\nBrooklyn| 123| 123|Homecrest|617733151424511999|\nBrooklyn| 123| 123|Homecrest|617733151423463423|\nBrooklyn| 123| 123|Homecrest|617733151511019519|\nBrooklyn| 123| 123|Homecrest|617733151505776639|\nBrooklyn| 123| 123|Homecrest|617733151505252351|\nBrooklyn| 123| 123|Homecrest|617733151504203775|\nBrooklyn| 123| 123|Homecrest|617733151503679487|\nBrooklyn| 123| 123|Homecrest|617733151503155199|\nBrooklyn| 123| 123|Homecrest|617733151502630911|\nBrooklyn| 123| 123|Homecrest|617733151502106623|\n+--------+-----------+--------+---------+------------------+\nonly showing top 20 rows\n\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "exploded_indexed_neighbourhoods = (\n", + " indexed_neighbourhoods\n", + " .withColumn(\"ix\", explode(\"ix_set\"))\n", + " .drop(\"ix_set\")\n", + ")\n", + "\n", + "exploded_indexed_neighbourhoods.show()" + ] }, { "cell_type": "markdown", - "source": [ - "## 6. Join the new left- and right-hand dataframes directly on the index." - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "a369d19f-2917-4320-ab4a-e701953db7b5" + "nuid": "a369d19f-2917-4320-ab4a-e701953db7b5", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "## 6. Join the new left- and right-hand dataframes directly on the index." + ] }, { "cell_type": "code", - "source": [ - "joined_df = (\n indexed_trips.alias(\"t\")\n .join(exploded_indexed_neighbourhoods.alias(\"n\"), on=\"ix\", how=\"inner\"))\njoined_df.count()" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "09a92bb5-4c72-4757-8176-01e14dbc3504" + "nuid": "09a92bb5-4c72-4757-8176-01e14dbc3504", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
Out[25]: 4934937
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
Out[25]: 4934937
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "joined_df = (\n", + " indexed_trips.alias(\"t\")\n", + " .join(exploded_indexed_neighbourhoods.alias(\"n\"), on=\"ix\", how=\"inner\"))\n", + "joined_df.count()" + ] }, { "cell_type": "markdown", - "source": [ - "## Final notes\nMosaic provides support for Uber’s H3 spatial indexing library as a core part of the API, but we plan to add support for other index systems, including S2 and British National Grid in due course." - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "9825374a-d5d3-407f-9c0d-94c7514edacf" + "nuid": "9825374a-d5d3-407f-9c0d-94c7514edacf", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "## Final notes\n", + "Mosaic provides support for Uber’s H3 spatial indexing library as a core part of the API, but we plan to add support for other index systems, including S2 and British National Grid in due course." + ] } ], "metadata": { "application/vnd.databricks.v1+notebook": { - "notebookName": "spatial-indexes", "dashboards": [], + "language": "python", "notebookMetadata": { "pythonIndentUnit": 2 }, - "language": "python", - "widgets": {}, - "notebookOrigID": 4066942804256643 + "notebookName": "grid-indexes", + "notebookOrigID": 2666786534675200, + "widgets": {} } }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/docs/source/usage/kepler.ipynb b/docs/source/usage/kepler.ipynb index 1e1a6c5d2..73c4de17d 100644 --- a/docs/source/usage/kepler.ipynb +++ b/docs/source/usage/kepler.ipynb @@ -2,6 +2,9 @@ "cells": [ { "cell_type": "markdown", +<<<<<<< HEAD +======= +<<<<<<< HEAD "source": [ "# Kepler visualizations" ], @@ -16,6 +19,36 @@ }, { "cell_type": "markdown", +======= +>>>>>>> databrickslabs-main + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "5dbca100-ca8d-4cb3-be39-72d2aeb85077", + "showTitle": false, + "title": "" + } + }, + "source": [ + "# Kepler visualizations" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "a2712c52-9c84-427e-bff8-814b9fa35d86", + "showTitle": false, + "title": "" + } + }, +<<<<<<< HEAD +======= +>>>>>>> efd95270 (Documentation updates) +>>>>>>> databrickslabs-main "source": [ "You can use the `%%mosaic_kepler` magic function to visualise data using [Kepler.gl](https://kepler.gl/).\n", "\n", @@ -36,6 +69,9 @@ "```\n", "\n", "This magic function is only available in python. It can be used from notebooks with other default languages by storing the intermediate result in a temporary view, and then adding a python cell that uses the `mosaic_kepler` with the temporary view created from another language." +<<<<<<< HEAD +======= +<<<<<<< HEAD ], "metadata": { "application/vnd.databricks.v1+cell": { @@ -98,10 +134,66 @@ }, { "cell_type": "code", +======= +>>>>>>> databrickslabs-main + ] + }, + { + "cell_type": "markdown", + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "573fa05d-6dfd-414e-84c4-6f3618540b60", + "showTitle": false, + "title": "" + } + }, + "source": [ + "## Examples" + ] + }, + { + "cell_type": "code", + "execution_count": 0, + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "c73e5956-dec2-4206-be2d-99bca42d2c93", + "showTitle": false, + "title": "" + } + }, + "outputs": [], + "source": [ + "%pip install databricks-mosaic --quiet" + ] + }, + { + "cell_type": "code", + "execution_count": 0, + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "a18dcbe7-1a01-45f2-a961-dd0f0284cf9c", + "showTitle": false, + "title": "" + } + }, + "outputs": [], +<<<<<<< HEAD +======= +>>>>>>> efd95270 (Documentation updates) +>>>>>>> databrickslabs-main "source": [ "from pyspark.sql.functions import *\n", "import mosaic as mos\n", "mos.enable_mosaic(spark, dbutils)" +<<<<<<< HEAD +======= +<<<<<<< HEAD ], "metadata": { "application/vnd.databricks.v1+cell": { @@ -150,12 +242,51 @@ }, { "cell_type": "code", +======= +>>>>>>> databrickslabs-main + ] + }, + { + "cell_type": "markdown", + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "2a997c83-5aff-4463-8c64-a1dc7a55d7d3", + "showTitle": false, + "title": "" + } + }, + "source": [ + "### Download example shapes" + ] + }, + { + "cell_type": "code", + "execution_count": 0, + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "93072805-dd95-4518-9099-47ca7e85b62d", + "showTitle": false, + "title": "" + } + }, + "outputs": [], +<<<<<<< HEAD +======= +>>>>>>> efd95270 (Documentation updates) +>>>>>>> databrickslabs-main "source": [ "import requests\n", "\n", "req = requests.get('https://data.cityofnewyork.us/api/geospatial/d3c5-ddgc?method=export&format=GeoJSON')\n", "with open('/dbfs/tmp/nyc_taxi_zones.geojson', 'wb') as f:\n", " f.write(req.content)" +<<<<<<< HEAD +======= +<<<<<<< HEAD ], "metadata": { "application/vnd.databricks.v1+cell": { @@ -190,6 +321,27 @@ }, { "cell_type": "code", +======= +>>>>>>> databrickslabs-main + ] + }, + { + "cell_type": "code", + "execution_count": 0, + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "eb739b60-a368-4dc9-9cf7-2f4346ffb06a", + "showTitle": false, + "title": "" + } + }, + "outputs": [], +<<<<<<< HEAD +======= +>>>>>>> efd95270 (Documentation updates) +>>>>>>> databrickslabs-main "source": [ "neighbourhoods = (\n", " spark.read\n", @@ -215,6 +367,9 @@ ")\n", "\n", "neighbourhoods.show()" +<<<<<<< HEAD +======= +<<<<<<< HEAD ], "metadata": { "application/vnd.databricks.v1+cell": { @@ -733,6 +888,266 @@ }, { "cell_type": "code", +======= +>>>>>>> databrickslabs-main + ] + }, + { + "cell_type": "markdown", + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "0c74d4f1-dbe6-4117-b752-4761b6a5d692", + "showTitle": false, + "title": "" + } + }, + "source": [ + "### Plot geometries from Spark dataset" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "4109bf9f-479e-47f1-aea5-fb881136c49e", + "showTitle": false, + "title": "" + } + }, + "source": [ + "#### Internal geometry type" + ] + }, + { + "cell_type": "code", + "execution_count": 0, + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "99be3b7a-3678-44bc-8d4a-ac35346cd724", + "showTitle": false, + "title": "" + } + }, + "outputs": [], + "source": [ + "%%mosaic_kepler\n", + "neighbourhoods \"geom_internal\" \"geometry\"" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "34b3328f-2966-4b6f-859f-325eeec04619", + "showTitle": false, + "title": "" + } + }, + "source": [ + "![mosaic kepler map example geometry](../images/kepler-1.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "f6d1c289-b007-4e40-b354-4c59fef9c2c4", + "showTitle": false, + "title": "" + } + }, + "source": [ + "#### WKT geometry type" + ] + }, + { + "cell_type": "code", + "execution_count": 0, + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "84ee5934-ed9c-4ee8-affd-dd347f375eec", + "showTitle": false, + "title": "" + } + }, + "outputs": [], + "source": [ + "%%mosaic_kepler\n", + "neighbourhoods \"geom_wkt\" \"geometry\"" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "b81a56b6-3d7c-4c87-91b2-fecc2f77333c", + "showTitle": false, + "title": "" + } + }, + "source": [ + "![mosaic kepler map example geometry](../images/kepler-1.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "2acdd70b-decd-4654-8927-9f821e728864", + "showTitle": false, + "title": "" + } + }, + "source": [ + "#### WKB geometry type" + ] + }, + { + "cell_type": "code", + "execution_count": 0, + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "0ddd1cad-dabf-4a9d-9e89-4406e2fda6e4", + "showTitle": false, + "title": "" + } + }, + "outputs": [], + "source": [ + "%%mosaic_kepler\n", + "neighbourhoods \"geom_wkb\" \"geometry\"" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "0f0deddf-3408-470d-8e9a-a6d066d23697", + "showTitle": false, + "title": "" + } + }, + "source": [ + "![mosaic kepler map example geometry](../images/kepler-1.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "590cb32e-2b3f-4ad7-b609-ffef9ae17967", + "showTitle": false, + "title": "" + } + }, + "source": [ + "### Plot geometries from table/view" + ] + }, + { + "cell_type": "code", + "execution_count": 0, + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "782fcc2e-d868-4819-bb01-9c4ea4bafb36", + "showTitle": false, + "title": "" + } + }, + "outputs": [], + "source": [ + "neighbourhoods.createOrReplaceTempView(\"temp_view_neighbourhoods\")" + ] + }, + { + "cell_type": "code", + "execution_count": 0, + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "fe84fa59-998d-4b9a-82c5-f280393ae244", + "showTitle": false, + "title": "" + } + }, + "outputs": [], + "source": [ + "%%mosaic_kepler\n", + "\"temp_view_neighbourhoods\" \"geom_wkt\" \"geometry\"" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "9d7dd0c3-64c5-43bb-aecd-287635929970", + "showTitle": false, + "title": "" + } + }, + "source": [ + "![mosaic kepler map example geometry](../images/kepler-1.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "d34979d6-45e5-4a6f-a12a-52e46cb1e946", + "showTitle": false, + "title": "" + } + }, + "source": [ + "### Plot H3 indexes" + ] + }, + { + "cell_type": "code", + "execution_count": 0, + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "86cdd4f3-34c5-4365-8108-303ca63d97af", + "showTitle": false, + "title": "" + } + }, + "outputs": [], +<<<<<<< HEAD +======= +>>>>>>> efd95270 (Documentation updates) +>>>>>>> databrickslabs-main "source": [ "neighbourhood_chips = (neighbourhoods\n", " .limit(1)\n", @@ -741,6 +1156,9 @@ " )\n", "\n", "neighbourhood_chips.show()" +<<<<<<< HEAD +======= +<<<<<<< HEAD ], "metadata": { "application/vnd.databricks.v1+cell": { @@ -968,10 +1386,101 @@ "nuid": "6c8244f4-4c03-4d12-9d06-d5174ef94626" } } +======= +>>>>>>> databrickslabs-main + ] + }, + { + "cell_type": "code", + "execution_count": 0, + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "84f6d1d7-b270-498b-b1fe-fe6d17e0e713", + "showTitle": false, + "title": "" + } + }, + "outputs": [], + "source": [ + "%%mosaic_kepler\n", + "neighbourhood_chips \"index_id\" \"h3\"" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "a9d921cb-5994-42a9-9518-626486cd1227", + "showTitle": false, + "title": "" + } + }, + "source": [ + "![mosaic kepler map example H3 indexes](../images/kepler-2.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "64cb0e7f-be2e-48f9-bea8-35a147e3f60c", + "showTitle": false, + "title": "" + } + }, + "source": [ + "### Plot H3 chips" + ] + }, + { + "cell_type": "code", + "execution_count": 0, + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "dbe03c2b-a2c2-4b17-a44c-16891e81d3d0", + "showTitle": false, + "title": "" + } + }, + "outputs": [], + "source": [ + "%%mosaic_kepler\n", + "neighbourhood_chips \"wkb\" \"geometry\"" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "6c8244f4-4c03-4d12-9d06-d5174ef94626", + "showTitle": false, + "title": "" + } + }, + "source": [ + "![mosaic kepler map example h3 chips](../images/kepler-3.png)" + ] +<<<<<<< HEAD +======= +>>>>>>> efd95270 (Documentation updates) +>>>>>>> databrickslabs-main } ], "metadata": { "application/vnd.databricks.v1+notebook": { +<<<<<<< HEAD +======= +<<<<<<< HEAD "notebookName": "kepler", "dashboards": [], "notebookMetadata": { @@ -980,6 +1489,20 @@ "language": "python", "widgets": {}, "notebookOrigID": 2874007245243191 +======= +>>>>>>> databrickslabs-main + "dashboards": [], + "language": "python", + "notebookMetadata": { + "pythonIndentUnit": 2 + }, + "notebookName": "kepler", + "notebookOrigID": 2666786534675682, + "widgets": {} +<<<<<<< HEAD +======= +>>>>>>> efd95270 (Documentation updates) +>>>>>>> databrickslabs-main } }, "nbformat": 4, diff --git a/docs/source/usage/quickstart.ipynb b/docs/source/usage/quickstart.ipynb index a643d848b..4eab9ee85 100644 --- a/docs/source/usage/quickstart.ipynb +++ b/docs/source/usage/quickstart.ipynb @@ -2,10235 +2,828 @@ "cells": [ { "cell_type": "markdown", - "source": [ - "# Quickstart notebook\nThe example code here shows how to get up and running with Mosaic using the Python API." - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "c247678b-66ab-4879-b331-bb0532826530" + "nuid": "c247678b-66ab-4879-b331-bb0532826530", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "# Quickstart notebook\n", + "The example code here shows how to get up and running with Mosaic using the Python API." + ] }, { "cell_type": "code", - "source": [ - "from pyspark.sql.functions import *" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "aaf89a78-8b1f-4e27-8cc8-3fa382ff8210" + "nuid": "aaf89a78-8b1f-4e27-8cc8-3fa382ff8210", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "from pyspark.sql.functions import *" + ] }, { "cell_type": "markdown", - "source": [ - "## Enable Mosaic in the notebook\nTo get started, you'll need to attach the python library to your cluster and execute the `enable_mosaic` function." - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "ec0b86d5-e58c-478a-824b-e1165fb267de" + "nuid": "ec0b86d5-e58c-478a-824b-e1165fb267de", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "## Enable Mosaic in the notebook\n", + "To get started, you'll need to attach the python library to your cluster and execute the `enable_mosaic` function." + ] }, { "cell_type": "code", - "source": [ - "from mosaic import enable_mosaic\nenable_mosaic(spark, dbutils)" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "ecb6237c-050b-47c6-98ed-6942a50472e3" + "nuid": "ecb6237c-050b-47c6-98ed-6942a50472e3", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "from mosaic import enable_mosaic\n", + "enable_mosaic(spark, dbutils)" + ] }, { "cell_type": "markdown", - "source": [ - "Mosaic has extra configuration options. Check the docs for more details." - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "d774f893-1152-41de-adde-bdad37e755f7" + "nuid": "d774f893-1152-41de-adde-bdad37e755f7", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "Mosaic has extra configuration options. Check the docs for more details." + ] }, { "cell_type": "code", - "source": [ - "help(enable_mosaic)" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "10776858-768a-450f-9281-6a00e80d04c2" + "nuid": "10776858-768a-450f-9281-6a00e80d04c2", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
Help on function enable_mosaic in module mosaic.api.enable:\n\nenable_mosaic(spark: pyspark.sql.session.SparkSession, dbutils=None) -> None\n Enable Mosaic functions.\n \n Use this function at the start of your workflow to ensure all of the required dependencies are installed and\n Mosaic is configured according to your needs.\n \n Parameters\n ----------\n spark : pyspark.sql.SparkSession\n The active SparkSession.\n dbutils : dbruntime.dbutils.DBUtils\n The dbutils object used for `display` and `displayHTML` functions.\n Optional, only applicable to Databricks users.\n \n Returns\n -------\n \n Notes\n -----\n Users can control various aspects of Mosaic's operation with the following Spark confs:\n \n - `spark.databricks.labs.mosaic.jar.autoattach`: 'true' (default) or 'false'\n Automatically attach the Mosaic JAR to the Databricks cluster? (Optional)\n - `spark.databricks.labs.mosaic.jar.location`\n Explicitly specify the path to the Mosaic JAR.\n (Optional and not required at all in a standard Databricks environment).\n - `spark.databricks.labs.mosaic.geometry.api`: 'OGC' (default) or 'JTS'\n Explicitly specify the underlying geometry library to use for spatial operations. (Optional)\n - `spark.databricks.labs.mosaic.index.system`: 'H3' (default)\n Explicitly specify the index system to use for optimized spatial joins. (Optional)\n\n
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
Help on function enable_mosaic in module mosaic.api.enable:\n\nenable_mosaic(spark: pyspark.sql.session.SparkSession, dbutils=None) -> None\n Enable Mosaic functions.\n \n Use this function at the start of your workflow to ensure all of the required dependencies are installed and\n Mosaic is configured according to your needs.\n \n Parameters\n ----------\n spark : pyspark.sql.SparkSession\n The active SparkSession.\n dbutils : dbruntime.dbutils.DBUtils\n The dbutils object used for `display` and `displayHTML` functions.\n Optional, only applicable to Databricks users.\n \n Returns\n -------\n \n Notes\n -----\n Users can control various aspects of Mosaic's operation with the following Spark confs:\n \n - `spark.databricks.labs.mosaic.jar.autoattach`: 'true' (default) or 'false'\n Automatically attach the Mosaic JAR to the Databricks cluster? (Optional)\n - `spark.databricks.labs.mosaic.jar.location`\n Explicitly specify the path to the Mosaic JAR.\n (Optional and not required at all in a standard Databricks environment).\n - `spark.databricks.labs.mosaic.geometry.api`: 'OGC' (default) or 'JTS'\n Explicitly specify the underlying geometry library to use for spatial operations. (Optional)\n - `spark.databricks.labs.mosaic.index.system`: 'H3' (default)\n Explicitly specify the index system to use for optimized spatial joins. (Optional)\n\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "help(enable_mosaic)" + ] }, { "cell_type": "markdown", - "source": [ - "## Geometry constructors and the Mosaic internal geometry format" - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "ac3649d8-5561-4370-b5d3-a36bf5068fd1" + "nuid": "ac3649d8-5561-4370-b5d3-a36bf5068fd1", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "## Geometry constructors and the Mosaic internal geometry format" + ] }, { "cell_type": "markdown", - "source": [ - "Mosaic allows users to create new Point geometries from a pair of Spark DoubleType columns." - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "c9e64d22-ebbc-4ea7-97aa-2dd6e240c9ad" + "nuid": "c9e64d22-ebbc-4ea7-97aa-2dd6e240c9ad", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "Mosaic allows users to create new Point geometries from a pair of Spark DoubleType columns." + ] }, { "cell_type": "code", - "source": [ - "from mosaic import st_point\n\nlons = [-80., -80., -70., -70., -80.]\nlats = [ 35., 45., 45., 35., 35.]\n\nbounds_df = (\n spark\n .createDataFrame({\"lon\": lon, \"lat\": lat} for lon, lat in zip(lons, lats))\n .coalesce(1)\n .withColumn(\"point_geom\", st_point(\"lon\", \"lat\"))\n)\nbounds_df.show()" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "aa85d1b2-8ec1-4879-87b4-cf55eb12820c" + "nuid": "aa85d1b2-8ec1-4879-87b4-cf55eb12820c", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
+----+-----+--------------------+\n| lat| lon| point_geom|\n+----+-----+--------------------+\n|35.0|-80.0|{1, [[[-80.0, 35....|\n|45.0|-80.0|{1, [[[-80.0, 45....|\n|45.0|-70.0|{1, [[[-70.0, 45....|\n|35.0|-70.0|{1, [[[-70.0, 35....|\n|35.0|-80.0|{1, [[[-80.0, 35....|\n+----+-----+--------------------+\n\n
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
+----+-----+--------------------+\n lat| lon| point_geom|\n+----+-----+--------------------+\n35.0|-80.0|{1, [[[-80.0, 35....|\n45.0|-80.0|{1, [[[-80.0, 45....|\n45.0|-70.0|{1, [[[-70.0, 45....|\n35.0|-70.0|{1, [[[-70.0, 35....|\n35.0|-80.0|{1, [[[-80.0, 35....|\n+----+-----+--------------------+\n\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "from mosaic import st_point\n", + "\n", + "lons = [-80., -80., -70., -70., -80.]\n", + "lats = [ 35., 45., 45., 35., 35.]\n", + "\n", + "bounds_df = (\n", + " spark\n", + " .createDataFrame({\"lon\": lon, \"lat\": lat} for lon, lat in zip(lons, lats))\n", + " .coalesce(1)\n", + " .withColumn(\"point_geom\", st_point(\"lon\", \"lat\"))\n", + ")\n", + "bounds_df.show()" + ] }, { "cell_type": "markdown", - "source": [ - "Mosaic Point geometries can be aggregated into LineString and Polygon geometries using the respective constructors." - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "e0229f66-1fe7-4218-905f-6fe265fd2441" + "nuid": "e0229f66-1fe7-4218-905f-6fe265fd2441", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "Mosaic Point geometries can be aggregated into LineString and Polygon geometries using the respective constructors." + ] }, { "cell_type": "code", - "source": [ - "from mosaic import st_makeline\n\nbounds_df = (\n bounds_df\n .groupBy()\n .agg(collect_list(\"point_geom\").alias(\"bounding_coords\"))\n .select(st_makeline(\"bounding_coords\").alias(\"bounding_ring\"))\n)\nbounds_df.show()" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "c143e704-333d-4c15-800d-7dcefc924f71" + "nuid": "c143e704-333d-4c15-800d-7dcefc924f71", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
+--------------------+\n| bounding_ring|\n+--------------------+\n|{3, [[[-80.0, 35....|\n+--------------------+\n\n
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
+--------------------+\n bounding_ring|\n+--------------------+\n{3, [[[-80.0, 35....|\n+--------------------+\n\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "from mosaic import st_makeline\n", + "\n", + "bounds_df = (\n", + " bounds_df\n", + " .groupBy()\n", + " .agg(collect_list(\"point_geom\").alias(\"bounding_coords\"))\n", + " .select(st_makeline(\"bounding_coords\").alias(\"bounding_ring\"))\n", + ")\n", + "bounds_df.show()" + ] }, { "cell_type": "code", - "source": [ - "from mosaic import st_makepolygon\n\nbounds_df = bounds_df.select(st_makepolygon(\"bounding_ring\").alias(\"bounds\"))\nbounds_df.show()" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "0282fcbd-f9b1-4708-b015-dc9e0fac9072" + "nuid": "0282fcbd-f9b1-4708-b015-dc9e0fac9072", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
+--------------------+\n| bounds|\n+--------------------+\n|{5, [[[-80.0, 35....|\n+--------------------+\n\n
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
+--------------------+\n bounds|\n+--------------------+\n{5, [[[-80.0, 35....|\n+--------------------+\n\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "from mosaic import st_makepolygon\n", + "\n", + "bounds_df = bounds_df.select(st_makepolygon(\"bounding_ring\").alias(\"bounds\"))\n", + "bounds_df.show()" + ] }, { "cell_type": "markdown", - "source": [ - "## Geometry clipping without an index" - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "459a46e8-e7cb-4bb0-a167-e359889d15a9" + "nuid": "459a46e8-e7cb-4bb0-a167-e359889d15a9", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "## Geometry clipping without an index" + ] }, { "cell_type": "markdown", - "source": [ - "Mosaic implements set intersection functions: contains, intersects, overlaps etc. Here you can see `st_contains` being used to clip points by a polygon geometry." - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "02d90b72-81b4-48a9-b117-b7976bca13aa" + "nuid": "02d90b72-81b4-48a9-b117-b7976bca13aa", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "Mosaic implements set intersection functions: contains, intersects, overlaps etc. Here you can see `st_contains` being used to clip points by a polygon geometry." + ] }, { "cell_type": "code", - "source": [ - "tripsTable = spark.table(\"delta.`/databricks-datasets/nyctaxi/tables/nyctaxi_yellow`\")" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "e5ec8d70-8d6b-44b9-ad2a-ef593e2011bd" + "nuid": "e5ec8d70-8d6b-44b9-ad2a-ef593e2011bd", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "tripsTable = spark.table(\"delta.`/databricks-datasets/nyctaxi/tables/nyctaxi_yellow`\")" + ] }, { "cell_type": "code", - "source": [ - "from mosaic import st_contains\ntrips = (\n tripsTable\n .limit(5_000_000)\n .repartition(sc.defaultParallelism * 20)\n .drop(\"vendorId\", \"rateCodeId\", \"store_and_fwd_flag\", \"payment_type\")\n .withColumn(\"pickup_geom\", st_point(\"pickup_longitude\", \"pickup_latitude\"))\n .withColumn(\"dropoff_geom\", st_point(\"dropoff_longitude\", \"dropoff_latitude\"))\n .crossJoin(bounds_df)\n .where(st_contains(\"bounds\", \"pickup_geom\"))\n .where(st_contains(\"bounds\", \"dropoff_geom\"))\n .cache()\n)" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "ad0e72a9-4e2e-45fe-ba39-d2933859154d" + "nuid": "ad0e72a9-4e2e-45fe-ba39-d2933859154d", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "from mosaic import st_contains\n", + "trips = (\n", + " tripsTable\n", + " .limit(5_000_000)\n", + " .repartition(sc.defaultParallelism * 20)\n", + " .drop(\"vendorId\", \"rateCodeId\", \"store_and_fwd_flag\", \"payment_type\")\n", + " .withColumn(\"pickup_geom\", st_point(\"pickup_longitude\", \"pickup_latitude\"))\n", + " .withColumn(\"dropoff_geom\", st_point(\"dropoff_longitude\", \"dropoff_latitude\"))\n", + " .crossJoin(bounds_df)\n", + " .where(st_contains(\"bounds\", \"pickup_geom\"))\n", + " .where(st_contains(\"bounds\", \"dropoff_geom\"))\n", + " .cache()\n", + ")" + ] }, { "cell_type": "code", - "source": [ - "trips.show()" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "9aa22657-47c6-4de6-8e48-733a150b00a0" + "nuid": "9aa22657-47c6-4de6-8e48-733a150b00a0", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+\n|vendor_id| pickup_datetime| dropoff_datetime|passenger_count|trip_distance|pickup_longitude|pickup_latitude|rate_code_id|dropoff_longitude|dropoff_latitude|fare_amount|extra|mta_tax|tip_amount|tolls_amount|total_amount| pickup_geom| dropoff_geom| bounds|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+\n| CMT|2009-10-12 19:35:21|2009-10-12 19:44:36| 1| 1.4| -74.000018| 40.720534| null| -73.995008| 40.734112| 6.5| 0.0| null| 0.0| 0.0| 6.5|{1, [[[-74.000018...|{1, [[[-73.995008...|{5, [[[-80.0, 35....|\n| CMT|2010-09-02 07:37:40|2010-09-02 07:53:17| 1| 6.8| -74.016477| 40.70971| 1| -73.97509| 40.759392| 17.3| 0.0| 0.5| 1.0| 0.0| 18.8|{1, [[[-74.016477...|{1, [[[-73.97509,...|{5, [[[-80.0, 35....|\n| CMT|2009-11-28 13:00:00|2009-11-28 13:01:57| 1| 0.5| -73.999666| 40.733384| null| -73.991751| 40.730273| 3.3| 0.0| 0.5| 0.0| 0.0| 3.8|{1, [[[-73.999666...|{1, [[[-73.991751...|{5, [[[-80.0, 35....|\n| CMT|2009-11-30 07:49:13|2009-11-30 08:12:38| 1| 12.9| -74.007033| 40.734931| null| -73.87277| 40.774319| 29.7| 0.0| 0.5| 6.04| 0.0| 36.24|{1, [[[-74.007033...|{1, [[[-73.87277,...|{5, [[[-80.0, 35....|\n| VTS|2009-01-03 01:55:00|2009-01-03 02:04:00| 5| 2.09| -73.993217| 40.72416| null| -73.9944| 40.74624| 7.7| 0.5| null| 0.0| 0.0| 8.2|{1, [[[-73.993217...|{1, [[[-73.9944, ...|{5, [[[-80.0, 35....|\n| VTS|2009-11-09 17:21:00|2009-11-09 17:32:00| 1| 5.19| -74.010003| 40.707022| null| -73.963853| 40.75677| 13.3| 1.0| 0.5| 0.0| 0.0| 14.8|{1, [[[-74.010003...|{1, [[[-73.963853...|{5, [[[-80.0, 35....|\n| VTS|2010-06-09 01:13:00|2010-06-09 01:27:00| 1| 8.09| -74.008697| 40.707335| 1| -73.949605| 40.78761| 19.7| 0.5| 0.5| 0.0| 0.0| 20.7|{1, [[[-74.008697...|{1, [[[-73.949605...|{5, [[[-80.0, 35....|\n| VTS|2009-01-28 18:36:00|2009-01-28 18:50:00| 1| 2.92| -74.008823| 40.72089| null| -73.994055| 40.747588| 10.1| 1.0| null| 3.0| 0.0| 14.1|{1, [[[-74.008823...|{1, [[[-73.994055...|{5, [[[-80.0, 35....|\n| CMT|2010-06-02 14:21:05|2010-06-02 14:28:43| 1| 5.0| -74.011653| 40.702604| 1| -73.971851| 40.749807| 12.5| 0.0| 0.5| 2.6| 0.0| 15.6|{1, [[[-74.011653...|{1, [[[-73.971851...|{5, [[[-80.0, 35....|\n| VTS|2009-11-26 15:38:00|2009-11-26 15:47:00| 5| 2.36| -73.997208| 40.722108| null| -73.99647| 40.748185| 8.1| 0.0| 0.5| 2.0| 0.0| 10.6|{1, [[[-73.997208...|{1, [[[-73.99647,...|{5, [[[-80.0, 35....|\n| CMT|2009-12-07 10:36:06|2009-12-07 10:42:26| 1| 1.3| -73.99067| 40.73065| null| -73.975539| 40.741353| 6.1| 0.0| 0.5| 0.0| 0.0| 6.6|{1, [[[-73.99067,...|{1, [[[-73.975539...|{5, [[[-80.0, 35....|\n| CMT|2009-11-15 09:11:42|2009-11-15 09:26:34| 1| 3.7| -73.990065| 40.687341| null| -73.999566| 40.730219| 12.1| 0.0| 0.5| 0.0| 0.0| 12.6|{1, [[[-73.990065...|{1, [[[-73.999566...|{5, [[[-80.0, 35....|\n| CMT|2010-06-27 17:27:25|2010-06-27 17:47:44| 2| 5.0| -74.008459| 40.712233| 1| -73.9516| 40.718877| 15.7| 0.0| 0.5| 3.0| 0.0| 19.2|{1, [[[-74.008459...|{1, [[[-73.9516, ...|{5, [[[-80.0, 35....|\n| VTS|2009-01-30 21:05:00|2009-01-30 21:34:00| 1| 5.99| -73.994397| 40.694843| null| -73.921257| 40.685107| 18.9| 0.5| null| 0.6| 0.0| 20.0|{1, [[[-73.994397...|{1, [[[-73.921257...|{5, [[[-80.0, 35....|\n| CMT|2009-01-14 07:43:53|2009-01-14 07:55:14| 2| 2.9| -74.007602| 40.725098| null| -73.977846| 40.751608| 9.3| 0.0| null| 0.0| 0.0| 9.3|{1, [[[-74.007602...|{1, [[[-73.977846...|{5, [[[-80.0, 35....|\n| VTS|2010-05-11 16:33:00|2010-05-11 16:41:00| 1| 0.99| -74.011205| 40.715468| 1| -74.011072| 40.708882| 5.7| 1.0| 0.5| 0.0| 0.0| 7.2|{1, [[[-74.011205...|{1, [[[-74.011072...|{5, [[[-80.0, 35....|\n| VTS|2009-01-19 09:43:00|2009-01-19 09:47:00| 1| 0.56| -73.991123| 40.731297| null| -73.98681| 40.736703| 4.1| 0.0| null| 0.0| 0.0| 4.1|{1, [[[-73.991123...|{1, [[[-73.98681,...|{5, [[[-80.0, 35....|\n| CMT|2009-11-14 15:46:36|2009-11-14 15:51:01| 2| 1.2| -74.008448| 40.734271| null| -74.006075| 40.720237| 4.9| 0.0| 0.5| 0.0| 0.0| 5.4|{1, [[[-74.008448...|{1, [[[-74.006075...|{5, [[[-80.0, 35....|\n| CMT|2009-11-17 16:50:35|2009-11-17 17:01:34| 1| 1.6| -74.00679| 40.730546| null| -73.9904| 40.73815| 7.7| 1.0| 0.5| 1.5| 0.0| 10.7|{1, [[[-74.00679,...|{1, [[[-73.9904, ...|{5, [[[-80.0, 35....|\n| CMT|2009-11-30 23:30:43|2009-11-30 23:42:54| 2| 2.9| -74.009605| 40.710155| null| -73.993875| 40.741554| 10.1| 0.5| 0.5| 2.22| 0.0| 13.32|{1, [[[-74.009605...|{1, [[[-73.993875...|{5, [[[-80.0, 35....|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+\nonly showing top 20 rows\n\n
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+\nvendor_id| pickup_datetime| dropoff_datetime|passenger_count|trip_distance|pickup_longitude|pickup_latitude|rate_code_id|dropoff_longitude|dropoff_latitude|fare_amount|extra|mta_tax|tip_amount|tolls_amount|total_amount| pickup_geom| dropoff_geom| bounds|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+\n CMT|2009-10-12 19:35:21|2009-10-12 19:44:36| 1| 1.4| -74.000018| 40.720534| null| -73.995008| 40.734112| 6.5| 0.0| null| 0.0| 0.0| 6.5|{1, [[[-74.000018...|{1, [[[-73.995008...|{5, [[[-80.0, 35....|\n CMT|2010-09-02 07:37:40|2010-09-02 07:53:17| 1| 6.8| -74.016477| 40.70971| 1| -73.97509| 40.759392| 17.3| 0.0| 0.5| 1.0| 0.0| 18.8|{1, [[[-74.016477...|{1, [[[-73.97509,...|{5, [[[-80.0, 35....|\n CMT|2009-11-28 13:00:00|2009-11-28 13:01:57| 1| 0.5| -73.999666| 40.733384| null| -73.991751| 40.730273| 3.3| 0.0| 0.5| 0.0| 0.0| 3.8|{1, [[[-73.999666...|{1, [[[-73.991751...|{5, [[[-80.0, 35....|\n CMT|2009-11-30 07:49:13|2009-11-30 08:12:38| 1| 12.9| -74.007033| 40.734931| null| -73.87277| 40.774319| 29.7| 0.0| 0.5| 6.04| 0.0| 36.24|{1, [[[-74.007033...|{1, [[[-73.87277,...|{5, [[[-80.0, 35....|\n VTS|2009-01-03 01:55:00|2009-01-03 02:04:00| 5| 2.09| -73.993217| 40.72416| null| -73.9944| 40.74624| 7.7| 0.5| null| 0.0| 0.0| 8.2|{1, [[[-73.993217...|{1, [[[-73.9944, ...|{5, [[[-80.0, 35....|\n VTS|2009-11-09 17:21:00|2009-11-09 17:32:00| 1| 5.19| -74.010003| 40.707022| null| -73.963853| 40.75677| 13.3| 1.0| 0.5| 0.0| 0.0| 14.8|{1, [[[-74.010003...|{1, [[[-73.963853...|{5, [[[-80.0, 35....|\n VTS|2010-06-09 01:13:00|2010-06-09 01:27:00| 1| 8.09| -74.008697| 40.707335| 1| -73.949605| 40.78761| 19.7| 0.5| 0.5| 0.0| 0.0| 20.7|{1, [[[-74.008697...|{1, [[[-73.949605...|{5, [[[-80.0, 35....|\n VTS|2009-01-28 18:36:00|2009-01-28 18:50:00| 1| 2.92| -74.008823| 40.72089| null| -73.994055| 40.747588| 10.1| 1.0| null| 3.0| 0.0| 14.1|{1, [[[-74.008823...|{1, [[[-73.994055...|{5, [[[-80.0, 35....|\n CMT|2010-06-02 14:21:05|2010-06-02 14:28:43| 1| 5.0| -74.011653| 40.702604| 1| -73.971851| 40.749807| 12.5| 0.0| 0.5| 2.6| 0.0| 15.6|{1, [[[-74.011653...|{1, [[[-73.971851...|{5, [[[-80.0, 35....|\n VTS|2009-11-26 15:38:00|2009-11-26 15:47:00| 5| 2.36| -73.997208| 40.722108| null| -73.99647| 40.748185| 8.1| 0.0| 0.5| 2.0| 0.0| 10.6|{1, [[[-73.997208...|{1, [[[-73.99647,...|{5, [[[-80.0, 35....|\n CMT|2009-12-07 10:36:06|2009-12-07 10:42:26| 1| 1.3| -73.99067| 40.73065| null| -73.975539| 40.741353| 6.1| 0.0| 0.5| 0.0| 0.0| 6.6|{1, [[[-73.99067,...|{1, [[[-73.975539...|{5, [[[-80.0, 35....|\n CMT|2009-11-15 09:11:42|2009-11-15 09:26:34| 1| 3.7| -73.990065| 40.687341| null| -73.999566| 40.730219| 12.1| 0.0| 0.5| 0.0| 0.0| 12.6|{1, [[[-73.990065...|{1, [[[-73.999566...|{5, [[[-80.0, 35....|\n CMT|2010-06-27 17:27:25|2010-06-27 17:47:44| 2| 5.0| -74.008459| 40.712233| 1| -73.9516| 40.718877| 15.7| 0.0| 0.5| 3.0| 0.0| 19.2|{1, [[[-74.008459...|{1, [[[-73.9516, ...|{5, [[[-80.0, 35....|\n VTS|2009-01-30 21:05:00|2009-01-30 21:34:00| 1| 5.99| -73.994397| 40.694843| null| -73.921257| 40.685107| 18.9| 0.5| null| 0.6| 0.0| 20.0|{1, [[[-73.994397...|{1, [[[-73.921257...|{5, [[[-80.0, 35....|\n CMT|2009-01-14 07:43:53|2009-01-14 07:55:14| 2| 2.9| -74.007602| 40.725098| null| -73.977846| 40.751608| 9.3| 0.0| null| 0.0| 0.0| 9.3|{1, [[[-74.007602...|{1, [[[-73.977846...|{5, [[[-80.0, 35....|\n VTS|2010-05-11 16:33:00|2010-05-11 16:41:00| 1| 0.99| -74.011205| 40.715468| 1| -74.011072| 40.708882| 5.7| 1.0| 0.5| 0.0| 0.0| 7.2|{1, [[[-74.011205...|{1, [[[-74.011072...|{5, [[[-80.0, 35....|\n VTS|2009-01-19 09:43:00|2009-01-19 09:47:00| 1| 0.56| -73.991123| 40.731297| null| -73.98681| 40.736703| 4.1| 0.0| null| 0.0| 0.0| 4.1|{1, [[[-73.991123...|{1, [[[-73.98681,...|{5, [[[-80.0, 35....|\n CMT|2009-11-14 15:46:36|2009-11-14 15:51:01| 2| 1.2| -74.008448| 40.734271| null| -74.006075| 40.720237| 4.9| 0.0| 0.5| 0.0| 0.0| 5.4|{1, [[[-74.008448...|{1, [[[-74.006075...|{5, [[[-80.0, 35....|\n CMT|2009-11-17 16:50:35|2009-11-17 17:01:34| 1| 1.6| -74.00679| 40.730546| null| -73.9904| 40.73815| 7.7| 1.0| 0.5| 1.5| 0.0| 10.7|{1, [[[-74.00679,...|{1, [[[-73.9904, ...|{5, [[[-80.0, 35....|\n CMT|2009-11-30 23:30:43|2009-11-30 23:42:54| 2| 2.9| -74.009605| 40.710155| null| -73.993875| 40.741554| 10.1| 0.5| 0.5| 2.22| 0.0| 13.32|{1, [[[-74.009605...|{1, [[[-73.993875...|{5, [[[-80.0, 35....|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+\nonly showing top 20 rows\n\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "trips.show()" + ] }, { "cell_type": "markdown", - "source": [ - "## Read from GeoJson, compute some basic geometry attributes" - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "c9353ac7-aa07-4d75-8b16-0031803ea31e" + "nuid": "c9353ac7-aa07-4d75-8b16-0031803ea31e", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "## Read from GeoJson, compute some basic geometry attributes" + ] }, { "cell_type": "markdown", - "source": [ - "You've seen how Mosaic can create geometries from Spark native data types but it also provides functions to translate Well Known Text (WKT), Well Known Binary (WKB) and GeoJSON representations to Mosaic geometries." - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "db5daf84-fc48-45ce-81a7-5af76b7b6010" + "nuid": "db5daf84-fc48-45ce-81a7-5af76b7b6010", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "You've seen how Mosaic can create geometries from Spark native data types but it also provides functions to translate Well Known Text (WKT), Well Known Binary (WKB) and GeoJSON representations to Mosaic geometries." + ] }, { "cell_type": "code", - "source": [ - "from mosaic import st_geomfromgeojson\n\ngeoJsonDF = (\n spark.read.format(\"json\")\n .load(\"dbfs:/FileStore/shared_uploads/stuart.lynn@databricks.com/NYC_Taxi_Zones.geojson\")\n .withColumn(\"geometry\", st_geomfromgeojson(to_json(col(\"geometry\"))))\n .select(\"properties.*\", \"geometry\")\n .drop(\"shape_area\", \"shape_leng\")\n)\n\ngeoJsonDF.show()" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "49505635-4e84-480e-9892-e3e816af2226" + "nuid": "49505635-4e84-480e-9892-e3e816af2226", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
+-------------+-----------+--------+--------------------+--------------------+\n| borough|location_id|objectid| zone| geometry|\n+-------------+-----------+--------+--------------------+--------------------+\n| EWR| 1| 1| Newark Airport|{6, [[[-74.184452...|\n| Queens| 2| 2| Jamaica Bay|{6, [[[-73.823375...|\n| Bronx| 3| 3|Allerton/Pelham G...|{6, [[[-73.847926...|\n| Manhattan| 4| 4| Alphabet City|{6, [[[-73.971774...|\n|Staten Island| 5| 5| Arden Heights|{6, [[[-74.174217...|\n|Staten Island| 6| 6|Arrochar/Fort Wad...|{6, [[[-74.063673...|\n| Queens| 7| 7| Astoria|{6, [[[-73.904136...|\n| Queens| 8| 8| Astoria Park|{6, [[[-73.923340...|\n| Queens| 9| 9| Auburndale|{6, [[[-73.785024...|\n| Manhattan| 24| 24| Bloomingdale|{6, [[[-73.959536...|\n| Queens| 10| 10| Baisley Park|{6, [[[-73.783266...|\n| Brooklyn| 11| 11| Bath Beach|{6, [[[-74.001098...|\n| Manhattan| 12| 12| Battery Park|{6, [[[-74.015657...|\n| Manhattan| 13| 13| Battery Park City|{6, [[[-74.012441...|\n| Bronx| 18| 18| Bedford Park|{6, [[[-73.885139...|\n| Brooklyn| 25| 25| Boerum Hill|{6, [[[-73.981552...|\n| Brooklyn| 14| 14| Bay Ridge|{6, [[[-74.034073...|\n| Queens| 15| 15|Bay Terrace/Fort ...|{6, [[[-73.777403...|\n| Brooklyn| 22| 22| Bensonhurst West|{6, [[[-73.992549...|\n|Staten Island| 23| 23|Bloomfield/Emerso...|{6, [[[-74.195686...|\n+-------------+-----------+--------+--------------------+--------------------+\nonly showing top 20 rows\n\n
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
+-------------+-----------+--------+--------------------+--------------------+\n borough|location_id|objectid| zone| geometry|\n+-------------+-----------+--------+--------------------+--------------------+\n EWR| 1| 1| Newark Airport|{6, [[[-74.184452...|\n Queens| 2| 2| Jamaica Bay|{6, [[[-73.823375...|\n Bronx| 3| 3|Allerton/Pelham G...|{6, [[[-73.847926...|\n Manhattan| 4| 4| Alphabet City|{6, [[[-73.971774...|\nStaten Island| 5| 5| Arden Heights|{6, [[[-74.174217...|\nStaten Island| 6| 6|Arrochar/Fort Wad...|{6, [[[-74.063673...|\n Queens| 7| 7| Astoria|{6, [[[-73.904136...|\n Queens| 8| 8| Astoria Park|{6, [[[-73.923340...|\n Queens| 9| 9| Auburndale|{6, [[[-73.785024...|\n Manhattan| 24| 24| Bloomingdale|{6, [[[-73.959536...|\n Queens| 10| 10| Baisley Park|{6, [[[-73.783266...|\n Brooklyn| 11| 11| Bath Beach|{6, [[[-74.001098...|\n Manhattan| 12| 12| Battery Park|{6, [[[-74.015657...|\n Manhattan| 13| 13| Battery Park City|{6, [[[-74.012441...|\n Bronx| 18| 18| Bedford Park|{6, [[[-73.885139...|\n Brooklyn| 25| 25| Boerum Hill|{6, [[[-73.981552...|\n Brooklyn| 14| 14| Bay Ridge|{6, [[[-74.034073...|\n Queens| 15| 15|Bay Terrace/Fort ...|{6, [[[-73.777403...|\n Brooklyn| 22| 22| Bensonhurst West|{6, [[[-73.992549...|\nStaten Island| 23| 23|Bloomfield/Emerso...|{6, [[[-74.195686...|\n+-------------+-----------+--------+--------------------+--------------------+\nonly showing top 20 rows\n\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "from mosaic import st_geomfromgeojson\n", + "\n", + "geoJsonDF = (\n", + " spark.read.format(\"json\")\n", + " .load(\"dbfs:/FileStore/shared_uploads/stuart.lynn@databricks.com/NYC_Taxi_Zones.geojson\")\n", + " .withColumn(\"geometry\", st_geomfromgeojson(to_json(col(\"geometry\"))))\n", + " .select(\"properties.*\", \"geometry\")\n", + " .drop(\"shape_area\", \"shape_leng\")\n", + ")\n", + "\n", + "geoJsonDF.show()" + ] }, { "cell_type": "markdown", - "source": [ - "Mosaic provides a number of functions for extracting the properties of geometries. Here are some that are relevant to Polygon geometries:" - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "880c5fb4-c0b2-456b-9167-cb6327876dbd" + "nuid": "880c5fb4-c0b2-456b-9167-cb6327876dbd", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "Mosaic provides a number of functions for extracting the properties of geometries. Here are some that are relevant to Polygon geometries:" + ] }, { "cell_type": "code", - "source": [ - "from mosaic import st_area, st_length\n(\n geoJsonDF\n .withColumn(\"calculatedArea\", abs(st_area(\"geometry\")))\n .withColumn(\"calculatedLength\", st_length(\"geometry\"))\n .select(\"geometry\", \"calculatedArea\", \"calculatedLength\")\n).show()" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "939d35fd-d868-4e73-8338-3cb8142fffe9" + "nuid": "939d35fd-d868-4e73-8338-3cb8142fffe9", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
+--------------------+--------------------+--------------------+\n| geometry| calculatedArea| calculatedLength|\n+--------------------+--------------------+--------------------+\n|{6, [[[-74.184452...|7.823067885002562E-4| 0.1163574531886787|\n|{6, [[[-73.823375...|0.001422779097814599| 0.8431218810128789|\n|{6, [[[-73.847926...|3.144141568206508E-4| 0.08434110590105784|\n|{6, [[[-73.971774...| 7.94539194214528E-5| 0.03559982116907461|\n|{6, [[[-74.174217...|4.979574893632193E-4| 0.09214648985735088|\n|{6, [[[-74.063673...|4.046076598541714E-4| 0.12905753305870837|\n|{6, [[[-73.904136...|3.897879892739018...| 0.10741717112348065|\n|{6, [[[-73.923340...|2.658771690499072E-5|0.027590691195158792|\n|{6, [[[-73.785024...|3.384438031986125...| 0.0997840924710119|\n|{6, [[[-73.959536...|4.193691000471793E-5|0.034022318280805826|\n|{6, [[[-73.783266...|4.358238180810105...| 0.09983947941552027|\n|{6, [[[-74.001098...|2.029913532381591E-4| 0.07243934539937844|\n|{6, [[[-74.015657...|1.078595394871048...| 0.01759380786230351|\n|{6, [[[-74.012441...|4.874002713725957E-5| 0.04726120195723124|\n|{6, [[[-73.885139...|1.488501639473639E-4| 0.06979954985700013|\n|{6, [[[-73.981552...|1.241682673558662...| 0.04714581993191898|\n|{6, [[[-74.034073...|6.636590898190788E-4| 0.13622530962992194|\n|{6, [[[-73.777403...|4.588438269978550...| 0.1295148763926726|\n|{6, [[[-73.992549...|4.613649657988681...| 0.11844001178496774|\n|{6, [[[-74.195686...|0.002090822778761513| 0.3007595308122533|\n+--------------------+--------------------+--------------------+\nonly showing top 20 rows\n\n
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
+--------------------+--------------------+--------------------+\n geometry| calculatedArea| calculatedLength|\n+--------------------+--------------------+--------------------+\n{6, [[[-74.184452...|7.823067885002562E-4| 0.1163574531886787|\n{6, [[[-73.823375...|0.001422779097814599| 0.8431218810128789|\n{6, [[[-73.847926...|3.144141568206508E-4| 0.08434110590105784|\n{6, [[[-73.971774...| 7.94539194214528E-5| 0.03559982116907461|\n{6, [[[-74.174217...|4.979574893632193E-4| 0.09214648985735088|\n{6, [[[-74.063673...|4.046076598541714E-4| 0.12905753305870837|\n{6, [[[-73.904136...|3.897879892739018...| 0.10741717112348065|\n{6, [[[-73.923340...|2.658771690499072E-5|0.027590691195158792|\n{6, [[[-73.785024...|3.384438031986125...| 0.0997840924710119|\n{6, [[[-73.959536...|4.193691000471793E-5|0.034022318280805826|\n{6, [[[-73.783266...|4.358238180810105...| 0.09983947941552027|\n{6, [[[-74.001098...|2.029913532381591E-4| 0.07243934539937844|\n{6, [[[-74.015657...|1.078595394871048...| 0.01759380786230351|\n{6, [[[-74.012441...|4.874002713725957E-5| 0.04726120195723124|\n{6, [[[-73.885139...|1.488501639473639E-4| 0.06979954985700013|\n{6, [[[-73.981552...|1.241682673558662...| 0.04714581993191898|\n{6, [[[-74.034073...|6.636590898190788E-4| 0.13622530962992194|\n{6, [[[-73.777403...|4.588438269978550...| 0.1295148763926726|\n{6, [[[-73.992549...|4.613649657988681...| 0.11844001178496774|\n{6, [[[-74.195686...|0.002090822778761513| 0.3007595308122533|\n+--------------------+--------------------+--------------------+\nonly showing top 20 rows\n\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "from mosaic import st_area, st_length\n", + "(\n", + " geoJsonDF\n", + " .withColumn(\"calculatedArea\", abs(st_area(\"geometry\")))\n", + " .withColumn(\"calculatedLength\", st_length(\"geometry\"))\n", + " .select(\"geometry\", \"calculatedArea\", \"calculatedLength\")\n", + ").show()" + ] }, { "cell_type": "code", - "source": [ - "geoJsonDF.count()" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "920599a2-6c52-40e4-8547-a99f757406a6" + "nuid": "920599a2-6c52-40e4-8547-a99f757406a6", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
Out[12]: 263
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
Out[12]: 263
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "geoJsonDF.count()" + ] }, { "cell_type": "markdown", - "source": [ - "## Example point-in-poly with indexing" - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "e0d34f66-7498-4a86-9dd3-b2664ebc535c" + "nuid": "e0d34f66-7498-4a86-9dd3-b2664ebc535c", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "## Example point-in-poly with indexing" + ] }, { "cell_type": "markdown", - "source": [ - "Mosaic has built-in support for the popular spatial indexing library, H3. The user has access to functions for generating point indices and the sets of indices covering polygons, allowing point-in-polygon joins to be transformed into deterministic SQL joins." - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "cb687786-0494-468d-b2e4-dbe847ea887b" + "nuid": "cb687786-0494-468d-b2e4-dbe847ea887b", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "Mosaic has built-in support for the popular spatial indexing library, H3. The user has access to functions for generating point indices and the sets of indices covering polygons, allowing point-in-polygon joins to be transformed into deterministic SQL joins." + ] }, { "cell_type": "code", - "source": [ - "from mosaic import grid_longlatascellid\n\ntrips_with_geom = (\n trips\n .withColumn(\"pickup_h3\", grid_longlatascellid(lon=\"pickup_longitude\", lat=\"pickup_latitude\", resolution=lit(10)))\n .withColumn(\"dropoff_h3\", grid_longlatascellid(lon=\"dropoff_longitude\", lat=\"dropoff_latitude\", resolution=lit(10)))\n)\n\ntrips_with_geom.show()" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "0ef8a536-fda8-4a9a-a2e6-58ad0c39cc8b" + "nuid": "0ef8a536-fda8-4a9a-a2e6-58ad0c39cc8b", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+------------------+------------------+\n|vendor_id| pickup_datetime| dropoff_datetime|passenger_count|trip_distance|pickup_longitude|pickup_latitude|rate_code_id|dropoff_longitude|dropoff_latitude|fare_amount|extra|mta_tax|tip_amount|tolls_amount|total_amount| pickup_geom| dropoff_geom| bounds| pickup_h3| dropoff_h3|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+------------------+------------------+\n| CMT|2009-10-12 19:35:21|2009-10-12 19:44:36| 1| 1.4| -74.000018| 40.720534| null| -73.995008| 40.734112| 6.5| 0.0| null| 0.0| 0.0| 6.5|{1, [[[-74.000018...|{1, [[[-73.995008...|{5, [[[-80.0, 35....|622236750705885183|622236723432488959|\n| CMT|2010-09-02 07:37:40|2010-09-02 07:53:17| 1| 6.8| -74.016477| 40.70971| 1| -73.97509| 40.759392| 17.3| 0.0| 0.5| 1.0| 0.0| 18.8|{1, [[[-74.016477...|{1, [[[-73.97509,...|{5, [[[-80.0, 35....|622236750651359231|622236723493961727|\n| CMT|2009-11-28 13:00:00|2009-11-28 13:01:57| 1| 0.5| -73.999666| 40.733384| null| -73.991751| 40.730273| 3.3| 0.0| 0.5| 0.0| 0.0| 3.8|{1, [[[-73.999666...|{1, [[[-73.991751...|{5, [[[-80.0, 35....|622236723433046015|622236750715092991|\n| CMT|2009-11-30 07:49:13|2009-11-30 08:12:38| 1| 12.9| -74.007033| 40.734931| null| -73.87277| 40.774319| 29.7| 0.0| 0.5| 6.04| 0.0| 36.24|{1, [[[-74.007033...|{1, [[[-73.87277,...|{5, [[[-80.0, 35....|622236750719975423|622236724015759359|\n| VTS|2009-01-03 01:55:00|2009-01-03 02:04:00| 5| 2.09| -73.993217| 40.72416| null| -73.9944| 40.74624| 7.7| 0.5| null| 0.0| 0.0| 8.2|{1, [[[-73.993217...|{1, [[[-73.9944, ...|{5, [[[-80.0, 35....|622236750717878271|622236723431276543|\n| VTS|2009-11-09 17:21:00|2009-11-09 17:32:00| 1| 5.19| -74.010003| 40.707022| null| -73.963853| 40.75677| 13.3| 1.0| 0.5| 0.0| 0.0| 14.8|{1, [[[-74.010003...|{1, [[[-73.963853...|{5, [[[-80.0, 35....|622236750647689215|622236723504381951|\n| VTS|2010-06-09 01:13:00|2010-06-09 01:27:00| 1| 8.09| -74.008697| 40.707335| 1| -73.949605| 40.78761| 19.7| 0.5| 0.5| 0.0| 0.0| 20.7|{1, [[[-74.008697...|{1, [[[-73.949605...|{5, [[[-80.0, 35....|622236750647820287|622236722210668543|\n| VTS|2009-01-28 18:36:00|2009-01-28 18:50:00| 1| 2.92| -74.008823| 40.72089| null| -73.994055| 40.747588| 10.1| 1.0| null| 3.0| 0.0| 14.1|{1, [[[-74.008823...|{1, [[[-73.994055...|{5, [[[-80.0, 35....|622236750713159679|622236723439304703|\n| CMT|2010-06-02 14:21:05|2010-06-02 14:28:43| 1| 5.0| -74.011653| 40.702604| 1| -73.971851| 40.749807| 12.5| 0.0| 0.5| 2.6| 0.0| 15.6|{1, [[[-74.011653...|{1, [[[-73.971851...|{5, [[[-80.0, 35....|622236750639857663|622236723496026111|\n| VTS|2009-11-26 15:38:00|2009-11-26 15:47:00| 5| 2.36| -73.997208| 40.722108| null| -73.99647| 40.748185| 8.1| 0.0| 0.5| 2.0| 0.0| 10.6|{1, [[[-73.997208...|{1, [[[-73.99647,...|{5, [[[-80.0, 35....|622236750706966527|622236723431309311|\n| CMT|2009-12-07 10:36:06|2009-12-07 10:42:26| 1| 1.3| -73.99067| 40.73065| null| -73.975539| 40.741353| 6.1| 0.0| 0.5| 0.0| 0.0| 6.6|{1, [[[-73.99067,...|{1, [[[-73.975539...|{5, [[[-80.0, 35....|622236750715092991|622236723437502463|\n| CMT|2009-11-15 09:11:42|2009-11-15 09:26:34| 1| 3.7| -73.990065| 40.687341| null| -73.999566| 40.730219| 12.1| 0.0| 0.5| 0.0| 0.0| 12.6|{1, [[[-73.990065...|{1, [[[-73.999566...|{5, [[[-80.0, 35....|622236750667481087|622236750719549439|\n| CMT|2010-06-27 17:27:25|2010-06-27 17:47:44| 2| 5.0| -74.008459| 40.712233| 1| -73.9516| 40.718877| 15.7| 0.0| 0.5| 3.0| 0.0| 19.2|{1, [[[-74.008459...|{1, [[[-73.9516, ...|{5, [[[-80.0, 35....|622236750648639487|622236723415482367|\n| VTS|2009-01-30 21:05:00|2009-01-30 21:34:00| 1| 5.99| -73.994397| 40.694843| null| -73.921257| 40.685107| 18.9| 0.5| null| 0.6| 0.0| 20.0|{1, [[[-73.994397...|{1, [[[-73.921257...|{5, [[[-80.0, 35....|622236750665449471|622236723618283519|\n| CMT|2009-01-14 07:43:53|2009-01-14 07:55:14| 2| 2.9| -74.007602| 40.725098| null| -73.977846| 40.751608| 9.3| 0.0| null| 0.0| 0.0| 9.3|{1, [[[-74.007602...|{1, [[[-73.977846...|{5, [[[-80.0, 35....|622236750711291903|622236723435503615|\n| VTS|2010-05-11 16:33:00|2010-05-11 16:41:00| 1| 0.99| -74.011205| 40.715468| 1| -74.011072| 40.708882| 5.7| 1.0| 0.5| 0.0| 0.0| 7.2|{1, [[[-74.011205...|{1, [[[-74.011072...|{5, [[[-80.0, 35....|622236750712831999|622236750647459839|\n| VTS|2009-01-19 09:43:00|2009-01-19 09:47:00| 1| 0.56| -73.991123| 40.731297| null| -73.98681| 40.736703| 4.1| 0.0| null| 0.0| 0.0| 4.1|{1, [[[-73.991123...|{1, [[[-73.98681,...|{5, [[[-80.0, 35....|622236750715060223|622236723429539839|\n| CMT|2009-11-14 15:46:36|2009-11-14 15:51:01| 2| 1.2| -74.008448| 40.734271| null| -74.006075| 40.720237| 4.9| 0.0| 0.5| 0.0| 0.0| 5.4|{1, [[[-74.008448...|{1, [[[-74.006075...|{5, [[[-80.0, 35....|622236750719844351|622236750713126911|\n| CMT|2009-11-17 16:50:35|2009-11-17 17:01:34| 1| 1.6| -74.00679| 40.730546| null| -73.9904| 40.73815| 7.7| 1.0| 0.5| 1.5| 0.0| 10.7|{1, [[[-74.00679,...|{1, [[[-73.9904, ...|{5, [[[-80.0, 35....|622236750718894079|622236723426754559|\n| CMT|2009-11-30 23:30:43|2009-11-30 23:42:54| 2| 2.9| -74.009605| 40.710155| null| -73.993875| 40.741554| 10.1| 0.5| 0.5| 2.22| 0.0| 13.32|{1, [[[-74.009605...|{1, [[[-73.993875...|{5, [[[-80.0, 35....|622236750646968319|622236723430490111|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+------------------+------------------+\nonly showing top 20 rows\n\n
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+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+------------------+------------------+\nvendor_id| pickup_datetime| dropoff_datetime|passenger_count|trip_distance|pickup_longitude|pickup_latitude|rate_code_id|dropoff_longitude|dropoff_latitude|fare_amount|extra|mta_tax|tip_amount|tolls_amount|total_amount| pickup_geom| dropoff_geom| bounds| pickup_h3| dropoff_h3|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+------------------+------------------+\n CMT|2009-10-12 19:35:21|2009-10-12 19:44:36| 1| 1.4| -74.000018| 40.720534| null| -73.995008| 40.734112| 6.5| 0.0| null| 0.0| 0.0| 6.5|{1, [[[-74.000018...|{1, [[[-73.995008...|{5, [[[-80.0, 35....|622236750705885183|622236723432488959|\n CMT|2010-09-02 07:37:40|2010-09-02 07:53:17| 1| 6.8| -74.016477| 40.70971| 1| -73.97509| 40.759392| 17.3| 0.0| 0.5| 1.0| 0.0| 18.8|{1, [[[-74.016477...|{1, [[[-73.97509,...|{5, [[[-80.0, 35....|622236750651359231|622236723493961727|\n CMT|2009-11-28 13:00:00|2009-11-28 13:01:57| 1| 0.5| -73.999666| 40.733384| null| -73.991751| 40.730273| 3.3| 0.0| 0.5| 0.0| 0.0| 3.8|{1, [[[-73.999666...|{1, [[[-73.991751...|{5, [[[-80.0, 35....|622236723433046015|622236750715092991|\n CMT|2009-11-30 07:49:13|2009-11-30 08:12:38| 1| 12.9| -74.007033| 40.734931| null| -73.87277| 40.774319| 29.7| 0.0| 0.5| 6.04| 0.0| 36.24|{1, [[[-74.007033...|{1, [[[-73.87277,...|{5, [[[-80.0, 35....|622236750719975423|622236724015759359|\n VTS|2009-01-03 01:55:00|2009-01-03 02:04:00| 5| 2.09| -73.993217| 40.72416| null| -73.9944| 40.74624| 7.7| 0.5| null| 0.0| 0.0| 8.2|{1, [[[-73.993217...|{1, [[[-73.9944, ...|{5, [[[-80.0, 35....|622236750717878271|622236723431276543|\n VTS|2009-11-09 17:21:00|2009-11-09 17:32:00| 1| 5.19| -74.010003| 40.707022| null| -73.963853| 40.75677| 13.3| 1.0| 0.5| 0.0| 0.0| 14.8|{1, [[[-74.010003...|{1, [[[-73.963853...|{5, [[[-80.0, 35....|622236750647689215|622236723504381951|\n VTS|2010-06-09 01:13:00|2010-06-09 01:27:00| 1| 8.09| -74.008697| 40.707335| 1| -73.949605| 40.78761| 19.7| 0.5| 0.5| 0.0| 0.0| 20.7|{1, [[[-74.008697...|{1, [[[-73.949605...|{5, [[[-80.0, 35....|622236750647820287|622236722210668543|\n VTS|2009-01-28 18:36:00|2009-01-28 18:50:00| 1| 2.92| -74.008823| 40.72089| null| -73.994055| 40.747588| 10.1| 1.0| null| 3.0| 0.0| 14.1|{1, [[[-74.008823...|{1, [[[-73.994055...|{5, [[[-80.0, 35....|622236750713159679|622236723439304703|\n CMT|2010-06-02 14:21:05|2010-06-02 14:28:43| 1| 5.0| -74.011653| 40.702604| 1| -73.971851| 40.749807| 12.5| 0.0| 0.5| 2.6| 0.0| 15.6|{1, [[[-74.011653...|{1, [[[-73.971851...|{5, [[[-80.0, 35....|622236750639857663|622236723496026111|\n VTS|2009-11-26 15:38:00|2009-11-26 15:47:00| 5| 2.36| -73.997208| 40.722108| null| -73.99647| 40.748185| 8.1| 0.0| 0.5| 2.0| 0.0| 10.6|{1, [[[-73.997208...|{1, [[[-73.99647,...|{5, [[[-80.0, 35....|622236750706966527|622236723431309311|\n CMT|2009-12-07 10:36:06|2009-12-07 10:42:26| 1| 1.3| -73.99067| 40.73065| null| -73.975539| 40.741353| 6.1| 0.0| 0.5| 0.0| 0.0| 6.6|{1, [[[-73.99067,...|{1, [[[-73.975539...|{5, [[[-80.0, 35....|622236750715092991|622236723437502463|\n CMT|2009-11-15 09:11:42|2009-11-15 09:26:34| 1| 3.7| -73.990065| 40.687341| null| -73.999566| 40.730219| 12.1| 0.0| 0.5| 0.0| 0.0| 12.6|{1, [[[-73.990065...|{1, [[[-73.999566...|{5, [[[-80.0, 35....|622236750667481087|622236750719549439|\n CMT|2010-06-27 17:27:25|2010-06-27 17:47:44| 2| 5.0| -74.008459| 40.712233| 1| -73.9516| 40.718877| 15.7| 0.0| 0.5| 3.0| 0.0| 19.2|{1, [[[-74.008459...|{1, [[[-73.9516, ...|{5, [[[-80.0, 35....|622236750648639487|622236723415482367|\n VTS|2009-01-30 21:05:00|2009-01-30 21:34:00| 1| 5.99| -73.994397| 40.694843| null| -73.921257| 40.685107| 18.9| 0.5| null| 0.6| 0.0| 20.0|{1, [[[-73.994397...|{1, [[[-73.921257...|{5, [[[-80.0, 35....|622236750665449471|622236723618283519|\n CMT|2009-01-14 07:43:53|2009-01-14 07:55:14| 2| 2.9| -74.007602| 40.725098| null| -73.977846| 40.751608| 9.3| 0.0| null| 0.0| 0.0| 9.3|{1, [[[-74.007602...|{1, [[[-73.977846...|{5, [[[-80.0, 35....|622236750711291903|622236723435503615|\n VTS|2010-05-11 16:33:00|2010-05-11 16:41:00| 1| 0.99| -74.011205| 40.715468| 1| -74.011072| 40.708882| 5.7| 1.0| 0.5| 0.0| 0.0| 7.2|{1, [[[-74.011205...|{1, [[[-74.011072...|{5, [[[-80.0, 35....|622236750712831999|622236750647459839|\n VTS|2009-01-19 09:43:00|2009-01-19 09:47:00| 1| 0.56| -73.991123| 40.731297| null| -73.98681| 40.736703| 4.1| 0.0| null| 0.0| 0.0| 4.1|{1, [[[-73.991123...|{1, [[[-73.98681,...|{5, [[[-80.0, 35....|622236750715060223|622236723429539839|\n CMT|2009-11-14 15:46:36|2009-11-14 15:51:01| 2| 1.2| -74.008448| 40.734271| null| -74.006075| 40.720237| 4.9| 0.0| 0.5| 0.0| 0.0| 5.4|{1, [[[-74.008448...|{1, [[[-74.006075...|{5, [[[-80.0, 35....|622236750719844351|622236750713126911|\n CMT|2009-11-17 16:50:35|2009-11-17 17:01:34| 1| 1.6| -74.00679| 40.730546| null| -73.9904| 40.73815| 7.7| 1.0| 0.5| 1.5| 0.0| 10.7|{1, [[[-74.00679,...|{1, [[[-73.9904, ...|{5, [[[-80.0, 35....|622236750718894079|622236723426754559|\n CMT|2009-11-30 23:30:43|2009-11-30 23:42:54| 2| 2.9| -74.009605| 40.710155| null| -73.993875| 40.741554| 10.1| 0.5| 0.5| 2.22| 0.0| 13.32|{1, [[[-74.009605...|{1, [[[-73.993875...|{5, [[[-80.0, 35....|622236750646968319|622236723430490111|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+------------------+------------------+\nonly showing top 20 rows\n\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "from mosaic import grid_longlatascellid\n", + "\n", + "trips_with_geom = (\n", + " trips\n", + " .withColumn(\"pickup_h3\", grid_longlatascellid(lon=\"pickup_longitude\", lat=\"pickup_latitude\", resolution=lit(10)))\n", + " .withColumn(\"dropoff_h3\", grid_longlatascellid(lon=\"dropoff_longitude\", lat=\"dropoff_latitude\", resolution=lit(10)))\n", + ")\n", + "\n", + "trips_with_geom.show()" + ] }, { "cell_type": "code", - "source": [ - "from mosaic import grid_polyfill\n\nneighbourhoods = (\n geoJsonDF\n .repartition(sc.defaultParallelism)\n .select(\"*\", explode(grid_polyfill(\"geometry\", lit(10))).alias(\"h3\"))\n .drop(\"geometry\")\n)\n\nneighbourhoods.show()" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "21627a45-71e0-4286-907b-94de6f04ec43" + "nuid": "21627a45-71e0-4286-907b-94de6f04ec43", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
+-------------+-----------+--------+---------------+------------------+\n| borough|location_id|objectid| zone| h3|\n+-------------+-----------+--------+---------------+------------------+\n|Staten Island| 99| 99|Freshkills Park|622236745731309567|\n|Staten Island| 99| 99|Freshkills Park|622236745690841087|\n|Staten Island| 99| 99|Freshkills Park|622236745723674623|\n|Staten Island| 99| 99|Freshkills Park|622236745683206143|\n|Staten Island| 99| 99|Freshkills Park|622236745691987967|\n|Staten Island| 99| 99|Freshkills Park|622236745684353023|\n|Staten Island| 99| 99|Freshkills Park|622236745733603327|\n|Staten Island| 99| 99|Freshkills Park|622236745725968383|\n|Staten Island| 99| 99|Freshkills Park|622236745701916671|\n|Staten Island| 99| 99|Freshkills Park|622236745734750207|\n|Staten Island| 99| 99|Freshkills Park|622236745694281727|\n|Staten Island| 99| 99|Freshkills Park|622236745703063551|\n|Staten Island| 99| 99|Freshkills Park|622236745679011839|\n|Staten Island| 99| 99|Freshkills Park|622236745761095679|\n|Staten Island| 99| 99|Freshkills Park|622236745680158719|\n|Staten Island| 99| 99|Freshkills Park|622236745696575487|\n|Staten Island| 99| 99|Freshkills Park|622236745762242559|\n|Staten Island| 99| 99|Freshkills Park|622236745681305599|\n|Staten Island| 99| 99|Freshkills Park|622236745730555903|\n|Staten Island| 99| 99|Freshkills Park|622236745690087423|\n+-------------+-----------+--------+---------------+------------------+\nonly showing top 20 rows\n\n
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
+-------------+-----------+--------+---------------+------------------+\n borough|location_id|objectid| zone| h3|\n+-------------+-----------+--------+---------------+------------------+\nStaten Island| 99| 99|Freshkills Park|622236745731309567|\nStaten Island| 99| 99|Freshkills Park|622236745690841087|\nStaten Island| 99| 99|Freshkills Park|622236745723674623|\nStaten Island| 99| 99|Freshkills Park|622236745683206143|\nStaten Island| 99| 99|Freshkills Park|622236745691987967|\nStaten Island| 99| 99|Freshkills Park|622236745684353023|\nStaten Island| 99| 99|Freshkills Park|622236745733603327|\nStaten Island| 99| 99|Freshkills Park|622236745725968383|\nStaten Island| 99| 99|Freshkills Park|622236745701916671|\nStaten Island| 99| 99|Freshkills Park|622236745734750207|\nStaten Island| 99| 99|Freshkills Park|622236745694281727|\nStaten Island| 99| 99|Freshkills Park|622236745703063551|\nStaten Island| 99| 99|Freshkills Park|622236745679011839|\nStaten Island| 99| 99|Freshkills Park|622236745761095679|\nStaten Island| 99| 99|Freshkills Park|622236745680158719|\nStaten Island| 99| 99|Freshkills Park|622236745696575487|\nStaten Island| 99| 99|Freshkills Park|622236745762242559|\nStaten Island| 99| 99|Freshkills Park|622236745681305599|\nStaten Island| 99| 99|Freshkills Park|622236745730555903|\nStaten Island| 99| 99|Freshkills Park|622236745690087423|\n+-------------+-----------+--------+---------------+------------------+\nonly showing top 20 rows\n\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "from mosaic import grid_polyfill\n", + "\n", + "neighbourhoods = (\n", + " geoJsonDF\n", + " .repartition(sc.defaultParallelism)\n", + " .select(\"*\", explode(grid_polyfill(\"geometry\", lit(10))).alias(\"h3\"))\n", + " .drop(\"geometry\")\n", + ")\n", + "\n", + "neighbourhoods.show()" + ] }, { "cell_type": "code", - "source": [ - "joined_df = trips_with_geom.alias(\"t\").join(neighbourhoods.alias(\"n\"), on=expr(\"t.pickup_h3 = n.h3\"), how=\"inner\")\njoined_df.count()" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "c3e68351-52d4-4a8b-8ce6-4898dedd0ecc" + "nuid": "c3e68351-52d4-4a8b-8ce6-4898dedd0ecc", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
Out[15]: 4934151
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
Out[15]: 4934151
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "joined_df = trips_with_geom.alias(\"t\").join(neighbourhoods.alias(\"n\"), on=expr(\"t.pickup_h3 = n.h3\"), how=\"inner\")\n", + "joined_df.count()" + ] }, { "cell_type": "markdown", - "source": [ - "## Mosaic spatial join optimizations" - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "c4fb8772-94b2-4fbe-aaf9-6e261609b009" + "nuid": "c4fb8772-94b2-4fbe-aaf9-6e261609b009", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "## Mosaic spatial join optimizations" + ] }, { "cell_type": "markdown", - "source": [ - "Mosaic provides easy access to the optimized spatial join technique described in [this](https://databricks.com/blog/2021/10/11/efficient-point-in-polygon-joins-via-pyspark-and-bng-geospatial-indexing.html) blog post." - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "c7696c95-820a-434e-9535-48807e1fb27c" + "nuid": "c7696c95-820a-434e-9535-48807e1fb27c", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "Mosaic provides easy access to the optimized spatial join technique described in [this](https://databricks.com/blog/2021/10/11/efficient-point-in-polygon-joins-via-pyspark-and-bng-geospatial-indexing.html) blog post." + ] }, { "cell_type": "code", - "source": [ - "from mosaic import grid_tessellateexplode\n\nmosaic_neighbourhoods = (\n geoJsonDF\n .repartition(sc.defaultParallelism)\n .select(\"*\", grid_tessellateexplode(\"geometry\", lit(10)))\n .drop(\"geometry\")\n)\n\nmosaic_neighbourhoods.show()" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "1319c9ca-149c-4208-8512-f035ffff467b" + "nuid": "1319c9ca-149c-4208-8512-f035ffff467b", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
+-------------+-----------+--------+---------------+-------+------------------+----+\n| borough|location_id|objectid| zone|is_core| h3| wkb|\n+-------------+-----------+--------+---------------+-------+------------------+----+\n|Staten Island| 99| 99|Freshkills Park| true|622236745694314495|null|\n|Staten Island| 99| 99|Freshkills Park| true|622236745679077375|null|\n|Staten Island| 99| 99|Freshkills Park| true|622236745734160383|null|\n|Staten Island| 99| 99|Freshkills Park| true|622236745762275327|null|\n|Staten Island| 99| 99|Freshkills Park| true|622236745731801087|null|\n|Staten Island| 99| 99|Freshkills Park| true|622236745725935615|null|\n|Staten Island| 99| 99|Freshkills Park| true|622236745680224255|null|\n|Staten Island| 99| 99|Freshkills Park| true|622236745689595903|null|\n|Staten Island| 99| 99|Freshkills Park| true|622236745683730431|null|\n|Staten Island| 99| 99|Freshkills Park| true|622236745723576319|null|\n|Staten Island| 99| 99|Freshkills Park| true|622236745763422207|null|\n|Staten Island| 99| 99|Freshkills Park| true|622236745693102079|null|\n|Staten Island| 99| 99|Freshkills Park| true|622236745732947967|null|\n|Staten Island| 99| 99|Freshkills Park| true|622236745702473727|null|\n|Staten Island| 99| 99|Freshkills Park| true|622236745696608255|null|\n|Staten Island| 99| 99|Freshkills Park| true|622236745736454143|null|\n|Staten Island| 99| 99|Freshkills Park| true|622236745761062911|null|\n|Staten Island| 99| 99|Freshkills Park| true|622236745690742783|null|\n|Staten Island| 99| 99|Freshkills Park| true|622236745675505663|null|\n|Staten Island| 99| 99|Freshkills Park| true|622236745730588671|null|\n+-------------+-----------+--------+---------------+-------+------------------+----+\nonly showing top 20 rows\n\n
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
+-------------+-----------+--------+---------------+-------+------------------+----+\n borough|location_id|objectid| zone|is_core| h3| wkb|\n+-------------+-----------+--------+---------------+-------+------------------+----+\nStaten Island| 99| 99|Freshkills Park| true|622236745694314495|null|\nStaten Island| 99| 99|Freshkills Park| true|622236745679077375|null|\nStaten Island| 99| 99|Freshkills Park| true|622236745734160383|null|\nStaten Island| 99| 99|Freshkills Park| true|622236745762275327|null|\nStaten Island| 99| 99|Freshkills Park| true|622236745731801087|null|\nStaten Island| 99| 99|Freshkills Park| true|622236745725935615|null|\nStaten Island| 99| 99|Freshkills Park| true|622236745680224255|null|\nStaten Island| 99| 99|Freshkills Park| true|622236745689595903|null|\nStaten Island| 99| 99|Freshkills Park| true|622236745683730431|null|\nStaten Island| 99| 99|Freshkills Park| true|622236745723576319|null|\nStaten Island| 99| 99|Freshkills Park| true|622236745763422207|null|\nStaten Island| 99| 99|Freshkills Park| true|622236745693102079|null|\nStaten Island| 99| 99|Freshkills Park| true|622236745732947967|null|\nStaten Island| 99| 99|Freshkills Park| true|622236745702473727|null|\nStaten Island| 99| 99|Freshkills Park| true|622236745696608255|null|\nStaten Island| 99| 99|Freshkills Park| true|622236745736454143|null|\nStaten Island| 99| 99|Freshkills Park| true|622236745761062911|null|\nStaten Island| 99| 99|Freshkills Park| true|622236745690742783|null|\nStaten Island| 99| 99|Freshkills Park| true|622236745675505663|null|\nStaten Island| 99| 99|Freshkills Park| true|622236745730588671|null|\n+-------------+-----------+--------+---------------+-------+------------------+----+\nonly showing top 20 rows\n\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "from mosaic import grid_tessellateexplode\n", + "\n", + "mosaic_neighbourhoods = (\n", + " geoJsonDF\n", + " .repartition(sc.defaultParallelism)\n", + " .select(\"*\", grid_tessellateexplode(\"geometry\", lit(10)))\n", + " .drop(\"geometry\")\n", + ")\n", + "\n", + "mosaic_neighbourhoods.show()" + ] }, { "cell_type": "markdown", - "source": [ - "Mosaic also includes a convenience function for displaying dataframes with geometry columns." - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "ee5d5a0a-2f2f-4095-9ec8-ce3ba0af6eaa" + "nuid": "ee5d5a0a-2f2f-4095-9ec8-ce3ba0af6eaa", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "Mosaic also includes a convenience function for displaying dataframes with geometry columns." + ] }, { "cell_type": "code", - "source": [ - "from mosaic import displayMosaic\ndisplayMosaic(mosaic_neighbourhoods)" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "162fc850-a289-416f-af6d-2dd73f30e93e" + "nuid": "162fc850-a289-416f-af6d-2dd73f30e93e", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "overflow": true, - "datasetInfos": [], - "data": [ - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745694314495, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745679077375, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745734160383, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745762275327, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745731801087, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745725935615, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745680224255, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745689595903, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745683730431, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745723576319, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745763422207, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745693102079, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745732947967, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745702473727, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745696608255, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745736454143, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745761062911, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745690742783, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745675505663, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745730588671, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745694248959, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745679011839, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745734094847, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745762209791, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745731735551, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745725870079, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745680158719, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745689530367, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745683664895, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745763356671, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745693036543, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745732882431, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745702408191, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745681305599, - null - ], - [ - "Staten Island", - "99", - "99", - "Freshkills Park", - true, - 622236745760997375, - 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Staten Island9999Freshkills Parkfalse622236745769549823AQMAAAABAAAACAAAAEsfeSjQilLAvI5xoTlMREBSSHP3yYpSwGY4QrM7TERAOPSwLMWKUsBX9gTsV0xEQOaTaHXEilLAzKLeUl9MREDTO0MRx4pSwLxEjlVjTERAUghS8dWKUsAn/qZcXkxEQAYG43zailLAFXeRgklMREBLH3k= (truncated)
Staten Island9999Freshkills Parkfalse622236746168893439AQMAAAABAAAACgAAAEFnNV4qjVLAwD4mP1tHREBSQQgeKo1SwJ1uO2ZcR0RAZL/3cTSNUsCXXLZDbEdEQMYbEV82jVLAcXR5nmtHREBx/B14P41SwJ9IGV9eR0RAd4R8yzqNUsDHj1iuXkdEQDyyRxU2jVLAdJqzbl5HREDzpns= (truncated)
Staten Island9999Freshkills Parkfalse622236745673244671AQYAAAACAAAAAQMAAAABAAAABQAAAGfnWjFYjFLAcCT/1uFKREBEWyhGUYxSwCD74ifkSkRAow3VNFKMUsA4U1F95kpEQD0y/b9ZjFLAYpJwO+RKREBn51oxWIxSwHAk/9bhSkRAAQMAAAABAAAABQAAALTRzktOjFLAkEgTJ+U= (truncated)
Staten Island9999Freshkills Parkfalse622236745730293759AQMAAAABAAAADwAAAHsrqeBrjVLALNBqRGhIREC72IoDXY1SwL+PlD9tSERAycTpeliNUsAWLoUYgkhEQF/qes9ijVLAaVta9pFIREB0K4b3bo1SwMamceONSERAC8KjXG+NUsBsmGihjEhEQKB950BwjVLAOz81o4lIREDlS8k= (truncated)
Staten Island9999Freshkills Parkfalse622236745757982719AQMAAAABAAAACAAAAFvg22aMilLANALWn7VLREB+k+jbiopSwE9M1CO2S0RAGDjhCnqKUsDZZAofz0tEQO+Cb7V5ilLATtUVkNBLREBwrGJPg4pSwGznOlPfS0RAL1ApL5KKUsBiUqda2ktEQNP227qWilLAaLPtgMVLREBb4Ns= (truncated)
Staten Island9999Freshkills Parkfalse622236745736519679AQMAAAABAAAABgAAABIxNdUtjVLALY8s+hJKRECy44BiKo1SwHiQ5CEUSkRA9g1i2SWNUsCgwZ/7KEpEQBUkeHMujVLAEIjHMTZKREByI0BpLo1SwE8n89smSkRAEjE11S2NUsAtjyz6EkpEQA==
Staten Island9999Freshkills Parktrue622236745678913535null
Staten Island9999Freshkills Parkfalse622236745682026495AQMAAAABAAAABwAAABhV/Kp6i1LAh31HSGFMRECUDmrva4tSwAQrrjVmTERABZFSZGeLUsARqwQQe0xEQKfzQ7lxi1LAY4jX8IpMRED1jqXhcotSwCtxt42KTERAYIM7BnqLUsBWLJGmYkxEQBhV/Kp6i1LAh31HSGFMREA=
Staten Island9999Freshkills Parkfalse622236745735405567AQMAAAABAAAALAAAACBtiIU+jVLASpeWu6xJREC8PLExMo1SwFki59ywSURAVV6sqC2NUsD4YnG2xUlEQFL7/MY3jVLATD7rQNVJREBHH4DjN41SwDCgssfTSURAIsTaMjiNUsBjWkyr0UlEQI02BZ04jVLAtALEwc9JRED26fE= (truncated)
Staten Island9999Freshkills Parkfalse622236745696149503AQMAAAABAAAACQAAAORf+0wejFLAur1XzyRIRECcUfVWHYxSwICcAXIlSERA39+yMxqMUsA/LFb4JkhEQMyzxCgEjFLA7KJzdS9IRECy6bdfA4xSwLMk9RAzSERAMuo1sw2MUsD2iZTvQkhEQLzpcZAcjFLAsm3J9T1IRECArRk= (truncated)
Staten Island9999Freshkills Parkfalse622236745742188543AQMAAAABAAAACAAAAIprKi5ti1LAwRpDy59MREAWlwtOXotSwFh5zcSkTERAjxrcwlmLUsBkxz+fuUxEQE1c3xdki1LAZg02gMlMREAFjWoXZ4tSwK+BhX/ITERAVAUJCGiLUsDfm3gqx0xEQOtdaKtui1LA144nFaJMRECKayo= (truncated)
Staten Island9999Freshkills Parkfalse622236745699262463AQMAAAABAAAACQAAAJjNyNXrilLAKAnxzP9JREDMTz333IpSwFwbsMUESkRA/2kpzNqKUsC/hKG4DkpEQJ1M8g/ailLAz8UH5RlKREAWV8fm2YpSwFyfwuQbSkRA9IGfv+KKUsAImNB+KUpEQB9AQZ7xilLAEb4HhiRKRECw80s= (truncated)
Staten Island9999Freshkills Parkfalse622236745695592447AQMAAAABAAAAFAAAACHyBz3Zi1LAvWeqxEVIREAEgGFh14tSwOf3dj5ISERATDZXYNeLUsCOiL8/SEhEQOccQV/Xi1LAvJIdQUhIRECJnmNZ04tSwD3fZQVNSERAwUAYJM+LUsD72D9wUUhEQC2BQSPPi1LAkpgWcVFIREBFkXY= (truncated)
Staten Island9999Freshkills Parkfalse622236745912778751AQMAAAABAAAABAAAAGogq/+5jFLAFbLcF2VHREDDmav/s4xSwCv2LqVwR0RAqYJpwreMUsAlCLhib0dEQGogq/+5jFLAFbLcF2VHREA=
Staten Island9999Freshkills Parkfalse622236745769877503AQMAAAABAAAABAAAAAESmsN+ilLAN0D7LPRLRECZpv25fIpSwPYgS9v0S0RAJSoxv3+KUsA+gcyv9UtEQAESmsN+ilLAN0D7LPRLREA=
Staten Island9999Freshkills Parkfalse622236745691365375AQMAAAABAAAACwAAAGozUIn1ilLAEKQIQdlHREAw8SYW9IpSwMcGf+jfR0RALiPBaP6KUsDAqrbH70dEQBJ93QEMi1LA/HtxO+tHREA3kig6BotSwLZ1sPHlR0RAxGtyuQCLUsAGDz7t4EdEQAg8IJ7/ilLA9ibo6t9HREDs7PU= (truncated)
Staten Island9999Freshkills Parkfalse622236745736290303AQMAAAABAAAABgAAAO0EkPJDjVLAR0N/nJ5JREBBXEPvQo1SwJNXp0SjSURA56I3SkONUsBSb/DdoklEQNmKbSVEjVLAIcjG8KFJRECgZKwxRI1SwIaCYj+gSURA7QSQ8kONUsBHQ3+cnklEQA==
Staten Island9999Freshkills Parktrue622236745921560575null
Staten Island9999Freshkills Parkfalse622236745913106431AQMAAAABAAAAEAAAAIIWNIjqjFLAZ2Od0SZHREBZDm1g6IxSwLkJSe8mR0RAA+xnOuaMUsDe2MI4J0dEQNYVpRfkjFLAj2zZrSdHREA05cPV4oxSwDR9Fg0oR0RAKXtIjd6MUsChDoq9O0dEQJJi9ODojFLA9Hgrm0tHREDMPG8= (truncated)
Staten Island9999Freshkills Parkfalse622236745698476031AQMAAAABAAAACQAAALL+ux3oilLAISejGFNJREBRTn3L4IpSwJM6VYtVSURAr2wazOCKUsAX3FEnVklEQKdUfongilLARGuvEmdJRED8vVvz34pSwAZAevV3SURAzrEi0N+KUsB9ldCGfElEQEwaBObtilLAFHgZ0XdJREBOsPA= (truncated)
Staten Island9999Freshkills Parkfalse622236745769648127AQMAAAABAAAABwAAAJ5JnIXCilLA0IWqL3hMRECiHMIJwopSwI4IEFl4TERA/atadMCKUsCS30q4iExEQO271ie+ilLAeH+vT6BMREBgDW9OyIpSwLcrH+ucTERAEwwY2syKUsCQ2O0QiExEQJ5JnIXCilLA0IWqL3hMREA=
Staten Island9999Freshkills Parkfalse622236746168991743AQMAAAABAAAAbgAAAOZxFHmcjVLAepg7ZklHRECjlbOcjY1SwBiZeWFOR0RAeDp0FImNUsAwnOU5Y0dEQNRjiUWTjVLAJcIu4XJHRED/Zstpk41SwACBE3xyR0RAaf7Oo5ONUsAQfUPlcUdEQB0fx+CTjVLAt2EwUXFHRED02aI= (truncated)
Staten Island9999Freshkills Parkfalse622236745673342975AQMAAAABAAAACQAAAB+zGpprjFLA/inKAshKRECwB1G7XIxSwNN6Kv3MSkRAZ+daMViMUsBwJP/W4UpEQD0y/b9ZjFLAYpJwO+RKREDd+3RsX4xSwLrmzYjiSkRArimgTm6MUsBukC0X5kpEQBjpkTV0jFLAQxtKzt9KRED9fQQ= (truncated)
Staten Island9999Freshkills Parktrue622236745680125951null
Staten Island9999Freshkills Parkfalse622236745672785919AQMAAAABAAAABwAAACtBCaInjFLAVe8AGPJKREBS8sO1HIxSwGna4b/1SkRArQe3bRuMUsDdVY+i+0pEQACZCuIdjFLA31deePlKREB6WJ8NIYxSwBYZS+72SkRASHDjSSSMUsDgOSWX9EpEQCtBCaInjFLAVe8AGPJKREA=
Staten Island9999Freshkills Parkfalse622236745690578943AQMAAAABAAAACQAAADmf/S3qilLA0p0dH8tIREDeljZq24pSwFzACA/QSERAHQuVdduKUsDBMc0y00hEQP7D8CDcilLA/mL9X+hIREAm+Thi3IpSwFEUV5HtSERABbJIGOGKUsBnDLvP9EhEQA6OJ/bvilLAP+gT1+9IREBuE/g= (truncated)
Staten Island9999Freshkills Parkfalse622236745761751039AQMAAAABAAAACAAAAIfQ/ZbEilLAbsZnK/BLRECF0TG3tYpSwH21MST1S0RAZUAtzbGKUsAxnLUYB0xEQIMkNPu8ilLAoHafRg5MREA7iZpExYpSwPaBRZsWTERAImKyX8qKUsAJfFzmFExEQDhHP+vOilLAxBlxDABMRECH0P0= (truncated)
Staten Island9999Freshkills Parktrue622236745679568895null
Staten Island9999Freshkills Parkfalse622236745743400959AQMAAAABAAAACAAAAG3Nwusyi1LABCIZR+1MREAhLGkLJItSwLFPb0DyTERAyND3fx+LUsBWzvUaB01EQJsA9NQpi1LAtHY0/BZNREC4lME/MotSwGymuysUTURAS5QPEDuLUsB9Dzo1B01EQNZYwUA9i1LAkKk/KP1MREBtzcI= (truncated)
Staten Island9999Freshkills Parkfalse622236745742843903AQMAAAABAAAABwAAAAEzn97yilLA2oyXBhZNREClgCsC5IpSwAfxVf4aTURA2LgymeuKUsAqkB94HE1EQCuus3/wilLAjowFRh1NREDVFnRh9YpSwF42raweTURAx31npfmKUsB65hRxIE1EQAEzn97yilLA2oyXBhZNREA=
Staten Island9999Freshkills Parkfalse622236745735503871AQMAAAABAAAAJwAAAGmcpnQzjVLA6wiKbupJREBKr4qWJI1SwJq/oWnvSURAfd5tDSCNUsBt20dDBEpEQLLjgGIqjVLAeJDkIRRKREASMTXVLY1SwC2PLPoSSkRAUz3cvy2NUsD9FD0cEEpEQKFRPQkujVLABAdpMg5KREAF9AY= (truncated)
Staten Island9999Freshkills Parkfalse622236745763749887AQMAAAABAAAACAAAALtW8YHOilLArlVM4gRLREDBzi5tyIpSwG9it+oGS0RA4J4bi8eKUsBsOitdEktEQMJtrBbEilLAuHWkiSxLREC47C9rxYpSwBUYJ5UuS0RAq7F7StSKUsCSfmGcKUtEQKxz0tXYilLAjfHswhRLREC7VvE= (truncated)
Staten Island9999Freshkills Parkfalse622236745742286847AQMAAAABAAAABQAAAPWOpeFyi1LAK3G3jYpMRECn80O5cYtSwGOI1/CKTERAimsqLm2LUsDBGkPLn0xEQOpdaKtui1LA1o4nFaJMRED1jqXhcotSwCtxt42KTERA
Staten Island9999Freshkills Parkfalse622236745762635775AQMAAAABAAAABwAAAHYlWVvWilLAhyqUnKFKREBbb3kU0IpSwFIVyLWjSkRAEeoHDc2KUsDk8VD5ykpEQInPy0TNilLAQyYNT8tKRECketcj3IpSwOq4SVbGSkRA5zIUr+CKUsBhDwZ9sUpEQHYlWVvWilLAhyqUnKFKREA=
Staten Island9999Freshkills Parkfalse622236745730162687AQMAAAABAAAAGgAAAIWgZ8V9jVLAs+4/8U5IREDJVDRpcI1SwFX6gGtTSERAeyup4GuNUsAs0GpEaEhEQJIooa11jVLAxTnhUXdIREArfNixdY1SwDytwUR3SERAuryaHHaNUsDfR6badUhEQHJmIY12jVLAAyiXwHNIRECYmyg= (truncated)
Staten Island9999Freshkills Parkfalse622236745760964607AQMAAAABAAAADwAAAA6xuwjBilLASTCfrUNLREAMPY6+wIpSwIpDl99FS0RADlNtYMCKUsASCxWsSUtEQDbSl+C/ilLA1AOZb01LREC/N2w/v4pSwAJlaydRS0RAwVRcfb6KUsC3/NzQVEtEQOpFM529ilLA4aMZP1hLREAiICs= (truncated)
Staten Island9999Freshkills Parkfalse622236745681895423AQMAAAABAAAABAAAACCTZnWFi1LAwuEBV0pMREDpjmBaf4tSwCRuzGFMTERAFEPU6XqLUsBUWqrCYExEQCCTZnWFi1LAwuEBV0pMREA=
Staten Island9999Freshkills Parkfalse622236745913204735AQMAAAABAAAACwAAABXjZov2jFLAiJgF+yhHREBY9ydG/IxSwGiLbMgxR0RARIHViAONUsD2Ja9ZL0dEQP5xVegCjVLAOz+bzi5HRECGIiypAY1SwJeud90tR0RAGzyPYQCNUsCfkFYILUdEQEWuBTf+jFLARiql8CtHRECeYPs= (truncated)
Staten Island9999Freshkills Parkfalse622236745691791359AQMAAAABAAAADAAAACoGIm3eilLAkiWYz9FHREAB8qRI3opSwD3ytDXaR0RAQqf0OOWKUsCSOQ7h5EdEQDDxJhb0ilLAxwZ/6N9HREBqM1CJ9YpSwBCkCEHZR0RAJkRisPKKUsB/rkns10dEQHVLi13vilLAjx6hh9ZHRECs1T8= (truncated)
Staten Island9999Freshkills Parkfalse622236745762963455AQMAAAABAAAABAAAANaM/WrUilLANt5z9mZKRED0jon204pSwBTVNlZtSkRAJZolHtWKUsCeeuUJaEpEQNaM/WrUilLANt5z9mZKREA=
Staten Island9999Freshkills Parkfalse622236745912647679AQMAAAABAAAABwAAANhuy9LNjFLAokyR2T1HREBeY4fGzYxSwL/8KPI9R0RAxheJEMSMUsCuK4O2UUdEQISpaybAjFLAhxjtP1lHRECjve0ny4xSwCBSJpBVR0RA40TQsM+MUsBWlAK4QEdEQNhuy9LNjFLAokyR2T1HREA=
Staten Island9999Freshkills Parkfalse622236745769746431AQMAAAABAAAACAAAAC9QKS+SilLAYlKnWtpLREBwrGJPg4pSwGznOlPfS0RAARKaw36KUsA3QPss9EtEQCUqMb9/ilLAPoHMr/VLREDbr8BfhYpSwEVfuDv3S0RA56Ztm5iKUsBVd9Ul/EtEQMadPYOcilLALk/KO+pLREAvUCk= (truncated)
Staten Island9999Freshkills Parkfalse622236746169090047AQMAAAABAAAAWQAAAG9CaOCOjVLAOgej74dHREAwmN0DgI1SwM+E2eqMR0RA6FCGe3uNUsAlamHDoUdEQHGZzc+FjVLAnx/BoLFHREDG46MAiY1SwK+q9o6wR0RArlsIMomNUsDMdGTwr0dEQNW/eIWJjVLAbZaq8K5HRECmLPQ= (truncated)
Staten Island9999Freshkills Parkfalse622236746168532991AQMAAAABAAAABwAAANOJOWFxjVLA9XyFoVpHREBd8nW9X41SwGstTkBjR0RAGO8Ff1yNUsAjLT8rckdEQM57ItNmjVLAvnCgCIJHREBMhKqvdY1SwAgXhQ19R0RAFsj/N3qNUsCVSRI1aEdEQNOJOWFxjVLA9XyFoVpHREA=
Staten Island9999Freshkills Parkfalse622236745690677247AQMAAAABAAAABwAAAJaTnyPeilLAwauyGAxJREAEAkaS3opSwJtPO5QSSURAs//Tnd+KUsAmHsVpI0lEQJfWoh3gilLAx6cvHi9JREDsCoZV4opSwAM5TWAuSURA4olu4OaKUsDtgduHGUlEQJaTnyPeilLAwauyGAxJREA=
Staten Island9999Freshkills Parkfalse622236745679667199AQMAAAABAAAABwAAAMOqaqPMjFLAADEi3UZKRECt/ALFvYxSwIZS2ddLSkRA44l6O7mMUsCOL4yxYEpEQNmtbZDDjFLAVzyWkHBKRECI/Em7y4xSwP8/YdRtSkRAJAV3dNGMUsDK4jpDTkpEQMOqaqPMjFLAADEi3UZKREA=
Staten Island9999Freshkills Parkfalse622236745750839295AQMAAAABAAAABgAAAFzYInTAilLAKfO+NQBNREBB/k2MtIpSwMpgZzAETURAyb1QWLOKUsBkYsfNEE1EQCMFdJHJilLAtfyqqxVNREAm6djIyopSwNdDPBcQTURAXNgidMCKUsAp8741AE1EQA==
Staten Island9999Freshkills Parktrue622236745729376255null
Staten Island9999Freshkills Parkfalse622236745696903167AQMAAAABAAAABwAAAM9QZfeFi1LA9tCAtUlIRECs3yEigotSwIct0/1KSERAaMvol32LUsCB4A7WX0hEQO0eHOuHi1LAnRMdtW9IREAy4IrIlotSwAp217tqSERAF8kzsZqLUsDi+w3JWEhEQM9QZfeFi1LA9tCAtUlIREA=
Staten Island9999Freshkills Parkfalse622236745757065215AQMAAAABAAAABQAAAB2rT82hilLAK9g3t5JLREAufZ0+nIpSwPDVNVCcS0RAoABJppuKUsAe8X8ynUtEQKlDKdKfilLAYkKWzZtLREAdq0/NoYpSwCvYN7eSS0RA
Staten Island9999Freshkills Parkfalse622236745742385151AQMAAAABAAAABAAAAAWNahdni1LAroGFf8hMREBNXN8XZItSwGYNNoDJTERAhFTWEWOLUsBFdtUyzkxEQAWNahdni1LAroGFf8hMREA=
Staten Island9999Freshkills Parkfalse622236745673768959AQMAAAABAAAACAAAAI43junqi1LADDmyaEBLRECqLKB54otSwMOecDtDS0RAuW8o792LUsCLtlgVWEtEQDyb7UPoi1LAvdlg9WdLREBL45x39otSwD0i0TRjS0RATkGm0feLUsDL/C7aX0tEQOKa9+v6i1LAfkZ+mlFLRECON44= (truncated)
Staten Island9999Freshkills Parktrue622236745769517055null
Staten Island9999Freshkills Parkfalse622236745730260991AQMAAAABAAAAJgAAAHUrhvdujVLAxqZx441IREBf6nrPYo1SwGlbWvaRSERAa9LXRl6NUsCgEGDPpkhEQCQuXl9mjVLAFu6JPrNIRECqx/yQZo1SwKFpRfiySERA89HMMmeNUsDb/RiHskhEQMQxL5dnjVLAgs8Jg7JIREDFrU4= (truncated)
Staten Island9999Freshkills Parkfalse622236745743269887AQMAAAABAAAACAAAAEU7ZFdGi1LAF8oxc9NMRECSMx53N4tSwNddmWzYTERAbc3C6zKLUsAEIhlH7UxEQNZYwUA9i1LAkKk/KP1MREB8ENtiQ4tSwFa2PBv7TERA10BbHU+LUsAOw4d76kxEQPwhZaxQi1LA2TBAVONMREBFO2Q= (truncated)
Staten Island9999Freshkills Parkfalse622236745700343807AQMAAAABAAAACAAAAF424J3eilLALDWSr4FIREDzmPH+24pSwM2v64+CSERALwjLvNuKUsD5/EBKkEhEQKkTtzrbilLAQoMUz6hIREBjPyg624pSwFetVXipSERAb9flZeSKUsBWt0dnpkhEQP5FsvDoilLAZgAcj5FIREBeNuA= (truncated)
Staten Island9999Freshkills Parkfalse622236745678880767AQMAAAABAAAABgAAANJGsZ6rjFLA33bcPp9KRECeJwzAnIxSwMGtejmkSkRA6c9VNpiMUsCaJVATuUpEQKAIEl2YjFLApnjRTrlKREDlerXBrYxSwCmzKoeiSkRA0kaxnquMUsDfdtw+n0pEQA==
Staten Island9999Freshkills Parkfalse622236745742712831AQMAAAABAAAACgAAAAz8pEoGi1LAyBTvMvxMREB/bTpq94pSwA6sGCwBTURAATOf3vKKUsDajJcGFk1EQMd9Z6X5ilLAeuYUcSBNREBJ5nIy+opSwDKGhKsgTURA/wLa5v6KUsBkDCo/I01EQCtf+PEAi1LA3S+QpyRNREAaRQM= (truncated)
Staten Island9999Freshkills Parkfalse622236745735372799AQMAAAABAAAAJAAAAMRo/LY3jVLAZffo2dZJREBpnKZ0M41SwOsIim7qSURA+d1JyzSNUsD6t8l87ElEQDOCDd40jVLAKUIqbuxJREACiayTNY1SwJK7PRLsSURAMcec9zWNUsC0/EBQ60lEQG9eIGI2jVLAxnHpRupJRECXcwE= (truncated)
Staten Island9999Freshkills Parkfalse622236745920643071AQMAAAABAAAABgAAANgYEA6VjFLAkR28UKlHREBPXNQyhIxSwBUZLAvHR0RAmBuE5IeMUsDtzke4zEdEQEHcYMGWjFLAZtQKvsdHREA1JodKm4xSwMaoveWyR0RA2BgQDpWMUsCRHbxQqUdEQA==
Staten Island9999Freshkills Parktrue622236745680879615null
Staten Island9999Freshkills Parkfalse622236745691332607AQMAAAABAAAACAAAABJ93QEMi1LA/HtxO+tHREAuI8Fo/opSwMCqtsfvR0RA7q8m3vmKUsCTnpWfBEhEQCAT1TAEi1LAk5HYfhRIREDBRCAOE4tSwIZzJIYPSERA1NammBeLUsAwKjeu+kdEQKCuRdAPi1LAtqLotu5HREASfd0= (truncated)
Staten Island9999Freshkills Parktrue622236745733701631null
Staten Island9999Freshkills Parktrue622236745750937599null
Staten Island9999Freshkills Parktrue622236745697001471null
Staten Island9999Freshkills Parkfalse622236745760833535AQMAAAABAAAACAAAAKuxe0rUilLAkn5hnClLREC47C9rxYpSwBUYJ5UuS0RACie2XMGKUsC632YxQUtEQA+xuwjBilLASTCfrUNLREBEL7Yzy4pSwLZnZk9TS0RA7DYYE9qKUsB2BpdWTktEQPoEcZ7eilLAFWYNfTlLRECrsXs= (truncated)
Staten Island9999Freshkills Parkfalse622236745735700479AQMAAAABAAAAEwAAALQHo0M7jVLA7nzuKYdJRED5LMdlLI1SwMHtAyWMSURAWFPE3CeNUsCnGHn+oElEQLw8sTEyjVLAWSLn3LBJREAgbYiFPo1SwEqXlrusSURAcUhlED+NUsAdsK/OqklEQKg1mTlBjVLAWq13QqVJRECkwDw= (truncated)
Staten Island9999Freshkills Parkfalse622236745681764351AQMAAAABAAAACAAAAIwmheW8i1LA9Z0od7BLRECoGgsGrotSwGaO7HC1S0RAbX5Pe6mLUsAx9f1KyktEQPfWIdCzi1LAuMBZK9pLREBb/ekiwItSwL+n7gvWS0RA89LTEsSLUsBCCgbTzktEQJTYWTrHi1LAUUlsV8BLRECMJoU= (truncated)
Staten Island9999Freshkills Parkfalse622236745762832383AQMAAAABAAAACAAAAKR61yPcilLA6rhJVsZKRECJz8tEzYpSwEMmDU/LSkRAN9I95MyKUsB0iwoKzUpEQGNgliHLilLAj5WO2+NKRECiDEYN04pSwCjc7AjwSkRArPln7OGKUsATpx8Q60pEQNS9pnfmilLAx+nGNtZKRECketc= (truncated)
Staten Island9999Freshkills Parkfalse622236746168958975AQMAAAABAAAABgAAAM3Ma5ePjVLABgLhpYRHREBvQmjgjo1SwDoHo++HR0RAaOCiCI+NUsBKW2wtiEdEQEa8qCGPjVLAAsfclIdHRECeZNxxj41SwKi7GpuFR0RAzcxrl4+NUsAGAuGlhEdEQA==
Staten Island9999Freshkills Parkfalse622236745690546175AQMAAAABAAAACAAAAA6OJ/bvilLAP+gT1+9IREAFskgY4YpSwGcMu8/0SERAjlqPpN2KUsD/cP+mBElEQJaTnyPeilLAwauyGAxJREDiiW7g5opSwO2B24cZSURAQ6RjvvWKUsA/liqPFElEQPk0Nkn6ilLARJ6/tv9IREAOjic= (truncated)
Staten Island9999Freshkills Parkfalse622236745761718271AQMAAAABAAAABwAAACJisl/KilLACXxc5hRMREA6iZpExYpSwPeBRZsWTERAM5Feqc6KUsC21skMIExEQFNIc/fJilLAZjhCsztMREBLH3ko0IpSwLyOcaE5TERAtBAItNSKUsABGnHHJExEQCJisl/KilLACXxc5hRMREA=
Staten Island9999Freshkills Parkfalse622236745679536127AQMAAAABAAAAJQAAAMpDMQvgjFLAkZqtCC1KREDVLt0s0YxSwLIXdgMySkRAw6pqo8yMUsAAMSLdRkpEQCQFd3TRjFLAy+I6Q05KREDMy6rN1IxSwH/qWMs7SkRAsvtiPdWMUsAl1UwkPEpEQDNcjp7VjFLAviqGWjxKRECH/M4= (truncated)
Staten Island9999Freshkills Parktrue622236745736585215null
Staten Island9999Freshkills Parkfalse622236745729245183AQMAAAABAAAALAAAADLQxNOGjVLAz4V57BFIRECv9KUCfo1SwPc4++AUSERAULkyenmNUsCkLsm5KUhEQDva5neBjVLAiAm1/zVIREDhkTR5gY1SwLvnIvo1SERAjqF22YGNUsBbvuRsNEhEQKLNoDyCjVLA1TJT4TJIREAoKbI= (truncated)
Staten Island9999Freshkills Parkfalse622236745743368191AQMAAAABAAAABQAAALiUwT8yi1LAbKa7KxRNRECbAPTUKYtSwLR2NPwWTURAqtP19CiLUsA8pAQAG01EQP+oH2Qxi1LAZxLDbhVNREC4lME/MotSwGymuysUTURA
Staten Island9999Freshkills Parkfalse622236745756934143AQMAAAABAAAABwAAABc4Zze2ilLAMPCOuGpLREDAxvqotIpSwA3YGShuS0RAlKxE5a6KUsAfGV4bektEQNHHlx6pilLAGoA+XYVLRECyHU09s4pSwO3XS/uBS0RABtHRyLeKUsDPwLQhbUtEQBc4Zze2ilLAMPCOuGpLREA=
Staten Island9999Freshkills Parkfalse622236745696215039AQMAAAABAAAACwAAALXuThv0i1LAX6sObDdIRECpl7jr64tSwJZhodE7SERAviuZm+OLUsCvTCm8P0hEQCZswprji1LAt++JvD9IRECwmeqZ44tSwLKS6rw/SERA/9ZrM9uLUsDnWTwnQ0hEQCHyBz3Zi1LAvWeqxEVIREDXEmA= (truncated)
Staten Island9999Freshkills Parkfalse622236745692545023AQMAAAABAAAABAAAACgicrTcilLA83wbF0dIREArG9yo3IpSwKOPqGtLSERAQxO1YN2KUsDDjPsfSEhEQCgicrTcilLA83wbF0dIREA=
Staten Island9999Freshkills Parkfalse622236745724461055AQMAAAABAAAACgAAAJkOOndRjVLA525JvwtJREB5rTCbR41SwEbzBw0PSURAGLZdEkONUsDlZEXmI0lEQHzYJmdNjVLAyKNsxDNJREDHUhhOT41SwGiaQiEzSURAVbkEolKNUsDNYIVVDUlEQBEZy0dSjVLAsnLBeQxJREDOZYg= (truncated)
Staten Island9999Freshkills Parkfalse622236745695657983AQMAAAABAAAADgAAABfJM7Gai1LA4vsNyVhIREAy4IrIlotSwAp217tqSERAAcDUG6GLUsAf2NiaekhEQGgqRvmvi1LAXRV4oXVIRECQ4BJKtItSwLrTGtBhSERAV+uEyrGLUsCmx90dYkhEQNwdcPWti1LAPRtxCGJIREAleDs= (truncated)
Staten Island9999Freshkills Parkfalse622236745691987967AQMAAAABAAAACAAAAKooeOkvi1LAZfYDlQlIREAcETM+LItSwNxVi2waSERAQI0OkTaLUsBkq7RLKkhEQIwUX25Fi1LAAEXKUiVIRECyP2O7SItSwFMVnSsWSERAGWXJvjmLUsDyC945D0hEQCyKW1sxi1LA8nYzsgpIRECqKHg= (truncated)
Staten Island9999Freshkills Parkfalse622236745680977919AQMAAAABAAAABwAAANOw7Nqbi1LA+8pp2QhMREA2MDX7jItSwAXBFNMNTERAT6RLcIiLUsCRtUitIkxEQCoAeomRi1LAx5K2qDBMREAKMIfLlItSwMZjWLspTERA4lHgu6CLUsD3hrhYEExEQNOw7Nqbi1LA+8pp2QhMREA=
Staten Island9999Freshkills Parkfalse622236745691430911AQMAAAABAAAABQAAAKGuRdAPi1LAt6Lotu5HREDU1qaYF4tSwDAqN676R0RANvJdkBuLUsBQenpa+UdEQERPK2Eai1LAqpOQYfhHREChrkXQD4tSwLei6LbuR0RA
Staten Island9999Freshkills Parkfalse622236745723346943AQMAAAABAAAAHAAAAGvS10ZejVLAoBBgz6ZIREDprY9pT41SwNBJgsqrSERA0KrW4EqNUsAEx46jwEhEQE+zeTVVjVLA1lmHgdBIREAyjfLbX41SwFCY5O/MSERAe70cJGCNUsDujN4AzEhEQFS6eo1gjVLAyM+DecpIREA8O1w= (truncated)
Staten Island9999Freshkills Parkfalse622236745921626111AQMAAAABAAAAEQAAALDgyKhgjFLA/P5Tsv9HREAmjv71XIxSwJoITWsDSERALyUTaVuMUsDV0oQvBEhEQHb+39FZjFLAiBZRugRIREB0ovMzWIxSwJm8fgoFSERArsftklaMUsCQYVkfBUhEQO6VdPJUjFLAy8ax+ARIREBH/Co= (truncated)
Staten Island9999Freshkills Parkfalse622236745743138815AQMAAAABAAAABwAAAGANb07IilLAtysf65xMREDuu9YnvopSwHh/r0+gTERAv4zxC7uKUsAFUjo3wExEQG4OBTe/ilLAgZ2dn8ZMREB3/VMXzopSwJUttKbBTERAnAj/otKKUsB5yG3MrExEQGANb07IilLAtysf65xMREA=
Staten Island9999Freshkills Parktrue622236745760931839null
Staten Island9999Freshkills Parkfalse622236745678749695AQMAAAABAAAABgAAANo04wa/jFLANC5eaoVKREAJr1EosIxSwNDBDWWKSkRA0kaxnquMUsDfdtw+n0pEQOV6tcGtjFLAKbMqh6JKREATkUgmw4xSwD9Zlb+LSkRA2jTjBr+MUsA0Ll5qhUpEQA==
Staten Island9999Freshkills Parkfalse622236745920511999AQMAAAABAAAABgAAAB+VN+mljFLAHNlvlotHREDYGBAOlYxSwJEdvFCpR0RANSaHSpuMUsDGqL3lskdEQGtSUCeqjFLAWFdv661HREBgsmCwroxSwKzyKBOZR0RAH5U36aWMUsAc2W+Wi0dEQA==
Staten Island9999Freshkills Parkfalse622236745913171967AQMAAAABAAAADwAAAESB1YgDjVLA9iWvWS9HREBY9ydG/IxSwGiLbMgxR0RAzDxvvfeMUsBI0JegRkdEQNurMRECjVLA62YsflZHRECtKa/tEI1SwCGbfYNRR0RA4we/chONUsD4CLrtRUdEQOQrAhUOjVLAbjrjPT9HREDV1s8= (truncated)
Staten Island9999Freshkills Parkfalse622236745673965567AQMAAAABAAAABgAAAEvjnHf2i1LAPSLRNGNLREA8m+1D6ItSwL3ZYPVnS0RAVdVzueOLUsAaBV7PfEtEQFNTPCboi1LAeowAnINLREAh5ikQ9YtSwJ9Au7BmS0RAS+Ocd/aLUsA9ItE0Y0tEQA==
Staten Island9999Freshkills Parkfalse622236745673408511AQMAAAABAAAACAAAALu+rP0+jFLAFZO+8dZKREBwIdIeMIxSwFla8uvbSkRAsHDnACyMUsCsmrvU7kpEQD17KOM1jFLA0yHRc+dKREDaHSmNPoxSwP+vXF34SkRA6nN7k0eMUsBq4qLW7kpEQPSifVJJjFLAABdO0eZKREC7vqw= (truncated)
Staten Island9999Freshkills Parkfalse622236745730457599AQMAAAABAAAAFgAAAFC5Mnp5jVLApC7JuSlIRECCNz6dao1SwMdz+rQuSERAAxK1FGaNUsB/Ms+NQ0hEQMlUNGlwjVLAVfqAa1NIRECGoGfFfY1SwLPuP/FOSERAJLS19n2NUsCxrrQ2TUhEQG7V+1p+jVLAQGxP70lIREBH65U= (truncated)
Staten Island9999Freshkills Parktrue622236745733570559null
Staten Island9999Freshkills Parkfalse622236745672851455AQMAAAABAAAADwAAAKGV1vf+i1LAVCD6s/9KREAkb9cY8ItSwL79760ES0RAS6x3juuLUsBGQryHGUtEQGwbygf0i1LAJW8njSZLRECDK1bD9ItSwG9lkhwmS0RA+S3loviLUsClnVOJJUtEQHh2Qfb6i1LACQXJVCRLREB4iTo= (truncated)
Staten Island9999Freshkills Parktrue622236745679634431null
Staten Island9999Freshkills Parkfalse622236745729343487AQMAAAABAAAAMAAAALZOdEeBjVLAuBxeecZHRECt1b9qco1SwHIWjXTLR0RAkaFQ4m2NUsA83TBN4EdEQF/MqTZ4jVLASvizKvBHREC1qGG0go1SwD9bjabsR0RA/if6toKNUsDrgP2F7EdEQFP048mCjVLAMdgQxutHREB3w1Q= (truncated)
Staten Island9999Freshkills Parkfalse622236745696870399AQMAAAABAAAABgAAAEWNn5Zfi1LAgCxlxitIRECZTqSeXotSwGFA4TgwSERAUeOs8WiLUsC89vAXQEhEQHlj38Rzi1LAr3/MeDxIREBIZEZ1Y4tSwFVgYpswSERARY2fll+LUsCALGXGK0hEQA==
Staten Island9999Freshkills Parkfalse622236745742909439AQMAAAABAAAABwAAABpFAxQMi1LAKc7H7iBNREArX/jxAItSwN0vkKckTURAt+MycwOLUsDWUVVhJk1EQFn34MwHi1LAdi8zCSpNREDxR4LqC4tSwO4heSsuTURAVQ/kDRKLUsBEojUeKk1EQBpFAxQMi1LAKc7H7iBNREA=
Staten Island9999Freshkills Parkfalse622236745724559359AQMAAAABAAAABwAAALzcUd5IjVLAoCu/nUhJREC81p8AOo1SwFsl3JhNSURAlu60dzWNUsAEdDVyYklEQGz0j8w/jVLASxiAUHJJRECAqMkSRo1SwIYIUzZwSURADEdtl0yNUsBlF5tVTklEQLzcUd5IjVLAoCu/nUhJREA=
Staten Island9999Freshkills Parkfalse622236745681633279AQMAAAABAAAACAAAAHFDkU/Qi1LA+6JIo5ZLREBo0CpwwYtSwD31HZ2bS0RAjCaF5byLUsD1nSh3sEtEQJTYWTrHi1LAUUlsV8BLREA6o7cGzYtSwEBezGa+S0RAtPl/1dGLUsCbaA+VtUtEQKNTumjZi1LA7hZenqRLREBxQ5E= (truncated)
Staten Island9999Freshkills Parkfalse622236745723445247AQMAAAABAAAAIgAAAP+rvqxQjVLAp+2oWuVIREDrtEzPQY1SwKyfw1XqSERA9sF7Rj2NUsDw+usu/0hEQHmtMJtHjVLARvMHDQ9JRECZDjp3UY1SwOduSb8LSURAmy3qFFGNUsC8VxJ1C0lEQGJCHqRQjVLAXAF+CQtJREBL7aw= (truncated)
Staten Island9999Freshkills Parkfalse622236745698312191AQMAAAABAAAABgAAAG08OvjeilLAAk6WhphJREAXiRYn3opSwHp3p6WzSURASdt4DN6KUsCTTEAZt0lEQAdjDkXgilLAksMkW7ZJREC98xLQ5IpSwK4ObYKhSURAbTw6+N6KUsACTpaGmElEQA==
Staten Island9999Freshkills Parkfalse622236746168827903AQMAAAABAAAACwAAAOMHv3ITjVLA+Ai67UVHRECtKa/tEI1SwCGbfYNRR0RASSCIQRuNUsCoXQVhYUdEQFJBCB4qjVLAnW47ZlxHREBBZzVeKo1SwL8+Jj9bR0RAEqjAJyiNUsBQpshPWkdEQGmfbbkjjVLAMafh2ldHRECVqug= (truncated)
Staten Island9999Freshkills Parkfalse622236745679962111AQMAAAABAAAABAAAAFysMkV+jFLAjn+zF9VKRED9fQTvdYxSwKC1NOLXSkRAGOmRNXSMUsBEG0rO30pEQFysMkV+jFLAjn+zF9VKREA=
Staten Island9999Freshkills Parktrue622236745761587199null
Staten Island9999Freshkills Parkfalse622236745743237119AQMAAAABAAAABQAAAHwQ22JDi1LAVrY8G/tMREDWWMFAPYtSwJCpPyj9TERAS5QPEDuLUsB8Dzo1B01EQIhW+cFAi1LAdqb41P5MREB8ENtiQ4tSwFa2PBv7TERA
Staten Island9999Freshkills Parkfalse622236745700311039AQMAAAABAAAABwAAAG/X5WXkilLAVrdHZ6ZIREBjPyg624pSwFetVXipSERARaTUKNuKUsDEqJYAvkhEQN6WNmrbilLAW8AID9BIREA5n/0t6opSwNKdHR/LSERANhnMuO6KUsAT0dxGtkhEQG/X5WXkilLAVrdHZ6ZIREA=
Staten Island9999Freshkills Parkfalse622236745678847999AQMAAAABAAAABgAAAIj8SbvLjFLA/z9h1G1KREDZrW2Qw4xSwFc8lpBwSkRA2jTjBr+MUsA0Ll5qhUpEQBORSCbDjFLAP1mVv4tKREAyXwIQx4xSwCYt7JSHSkRAiPxJu8uMUsD/P2HUbUpEQA==
Staten Island9999Freshkills Parkfalse622236745921167359AQMAAAABAAAAEAAAAKpBmSoxjFLAVBV0KgpIRED1+tsXMIxSwFhnw8cLSERApyPfVi6MUsDCi142D0hEQMWNn+ksjFLAf5uV5RJIREDhGj3pKoxSwHFZtOIWSERACuO+oCiMUsBPdzyYGkhEQP3niRcmjFLAunh29B1IREBiNAs= (truncated)
Staten Island9999Freshkills Parkfalse622236745696083967AQMAAAABAAAABwAAAMyzxCgEjFLA7KJzdS9IREBu3gM3/ItSwO2BqIQySERASSVnIfSLUsB7p8hoN0hEQLXuThv0i1LAX6sObDdIRECckX6C9ItSwBocpQo4SERAsum3XwOMUsCzJPUQM0hEQMyzxCgEjFLA7KJzdS9IREA=
Staten Island9999Freshkills Parkfalse622236745692413951AQMAAAABAAAACgAAADDKLXbmilLAKU0UcB5IRECm7lIW3YpSwAIPmpIhSERAH2+7+9yKUsCZ6njbK0hEQOuxW87cilLApw88aD1IREAE2tXF3IpSwEW4R5dASERAKCJytNyKUsDzfBsXR0hEQEMTtWDdilLAw4z7H0hIREA0Zyc= (truncated)
Staten Island9999Freshkills Parkfalse622236745763586047AQMAAAABAAAABwAAACTefjTeilLAaUjOVz5KREBedQAm14pSwAbCx7NASkRA1oz9atSKUsA23nP2ZkpEQCWaJR7VilLAnnrlCWhKRECJLfH844pSwGA6JBFjSkRAId0TiOiKUsC8dRE4TkpEQCTefjTeilLAaUjOVz5KREA=
Staten Island9999Freshkills Parkfalse622236745913270271AQMAAAABAAAADgAAADTlw9XijFLANH0WDShHRECJpqD54YxSwC4EOU4oR0RAlFrR4d+MUsAMQHYZKUdEQEjurdHdjFLAvhj/DipHREALh6TK24xSwD4NLC4rR0RA2usdztmMUsBZZjV2LEdEQJ+QvQ7XjFLAZJ+IVy9HREC48dQ= (truncated)
Staten Island9999Freshkills Parkfalse622236745699196927AQMAAAABAAAABQAAALrsGn7bilLAuFfbgQJKRECdmFAc24pSwJ6EgfYJSkRA/2kpzNqKUsC/hKG4DkpEQMxPPffcilLAXBuwxQRKREC67Bp+24pSwLhX24ECSkRA
Staten Island9999Freshkills Parkfalse622236745695526911AQMAAAABAAAABQAAAIRo44zDi1LALs7IBFtIRECnGKKbwYtSwLNuDmBcSERA5S3Pf8GLUsACxJtwXEhEQMdPtWDDi1LAoZytz1tIRECEaOOMw4tSwC7OyARbSERA
Staten Island9999Freshkills Parkfalse622236745680846847AQMAAAABAAAABwAAABMxZEWvi1LAlzqABe9LRECXScBloItSwJGTPP/zS0RA07Ds2puLUsD7ymnZCExEQOJR4Lugi1LA94a4WBBMREAQZNodo4tSwNinvkcLTERA+pIzCrGLUsBy1VS98UtEQBMxZEWvi1LAlzqABe9LREA=
Staten Island9999Freshkills Parkfalse622236745769811967AQMAAAABAAAABwAAAFbvBmOrilLANo0bQ+VLREDGnT2DnIpSwC5PyjvqS0RA56Ztm5iKUsBVd9Ul/EtEQG61ciKmilLAQ0i3mv9LREBlQC3NsYpSwDKctRgHTERAhdExt7WKUsB9tTEk9UtEQFbvBmOrilLANo0bQ+VLREA=
Staten Island9999Freshkills Parkfalse622236746168598527AQYAAAACAAAAAQMAAAABAAAABAAAAMYbEV82jVLAcHR5nmtHREBkv/dxNI1SwJdctkNsR0RA1WQIwjONUsCPAKtsb0dEQMYbEV82jVLAcHR5nmtHREABAwAAAAEAAAAHAAAAJsRYLUiNUsDiJhvEbkdEQPRca30xjVLAU6dZ2nk= (truncated)
Staten Island9999Freshkills Parkfalse622236745750904831AQMAAAABAAAABgAAAPBjVKnZilLAqUM/HgtNREAm6djIyopSwNdDPBcQTURAIwV0kcmKUsC1/KqrFU1EQPpPG/vQilLAY0o+SxdNREBfton844pSwGCcPf0aTURA8GNUqdmKUsCpQz8eC01EQA==
Staten Island9999Freshkills Parkfalse622236746168041471AQMAAAABAAAAKQAAALlJtLqljVLATwxtDEFHRECyy2pnnY1SwOz08x1FR0RA5nEUeZyNUsB6mDtmSUdEQEx0E7ihjVLA5SbidFFHREDc8I68oY1SwC+Lt25RR0RAZ42B8qGNUsBV3b8dUUdEQBLr4S6ijVLAvRVN0VBHRED9au0= (truncated)
Staten Island9999Freshkills Parkfalse622236745729441791AQMAAAABAAAARQAAAMbjowCJjVLAr6r2jrBHREBxmc3PhY1SwJ8fwaCxR0RAtk50R4GNUsC4HF55xkdEQILDmUyGjVLADwMzL85HREBCxyVMho1SwFOq+gvOR0RAB4btRoaNUsBkrEybzUdEQEuJ9T2GjVLAxewqK81HREBtW0M= (truncated)
Staten Island9999Freshkills Parkfalse622236745725771775AQMAAAABAAAACgAAAFJBCB4qjVLAnW47ZlxHREBJIIhBG41SwKhdBWFhR0RAFkXhuBaNUsCFCVQ5dkdEQGpvzgwhjVLALRXnFoZHREDEyGTpL41SwD5XExyBR0RA9FxrfTGNUsBTp1naeUdEQGAQxh8qjVLA7wfWc31HREDVZAg= (truncated)
Staten Island9999Freshkills Parkfalse622236745921495039AQMAAAABAAAADgAAAFlfhFdzjFLA98u/xeRHREBmDkG8a4xSwLzO+y/yR0RAwYsfP2iMUsD/Vnzg9kdEQG5Dez5ojFLAohZT4fZHREAf+9Y9aIxSwOI2EuL2R0RAqA5AnWSMUsC/VRtS+0dEQBSyNJxkjFLAIAxmU/tHREAbjiw= (truncated)
Staten Island9999Freshkills Parkfalse622236745692741631AQMAAAABAAAABQAAAAHypEjeilLAPfK0NdpHREDE33S73YpSwKCHSLX6R0RAHFNGruCKUsCZ1964+UdEQEKn9DjlilLAkjkO4eRHREAB8qRI3opSwD3ytDXaR0RA
Staten Island9999Freshkills Parkfalse622236745681731583AQMAAAABAAAABgAAAFXVc7nji1LAGgVez3xLREAv+yDa1ItSwLy4RMmBS0RAcUORT9CLUsD7okijlktEQKNTumjZi1LA7hZenqRLREBSUzwm6ItSwHmMAJyDS0RAVdVzueOLUsAaBV7PfEtEQA==
Staten Island9999Freshkills Parkfalse622236745673834495AQMAAAABAAAABAAAAOKa9+v6i1LAfkZ+mlFLREBOQabR94tSwMz8LtpfS0RA7geSw/yLUsAOyQGVU0tEQOKa9+v6i1LAfkZ+mlFLREA=
Staten Island9999Freshkills Parkfalse622236745673277439AQMAAAABAAAACgAAACvMfWZSjFLAqBazHb1KRECTx7aHQ4xSwGY8+BfCSkRAu76s/T6MUsAVk77x1kpEQPSifVJJjFLAABdO0eZKREC00c5LToxSwJBIEyflSkRAPBFL/U6MUsCHseZv3kpEQERbKEZRjFLAIPviJ+RKREBn51o= (truncated)
Staten Island9999Freshkills Parkfalse622236745672720383AQMAAAABAAAADAAAAMb1C2ESjFLAwV4t4OVKRECjZyCCA4xSwL2bNNrqSkRAoZXW9/6LUsBUIPqz/0pEQPs5jEwJjFLAu7vGkw9LREBzbpq/DoxSwJzt5sANS0RAx10I9RGMUsDA5h+HBUtEQOl6uNAUjFLAw0fzPAJLREARTko= (truncated)
Staten Island9999Freshkills Parkfalse622236745758015487AQMAAAABAAAABAAAACGkevmMilLAdpNQ/7JLREB+k+jbiopSwE9M1CO2S0RAW+DbZoyKUsA0AtaftUtEQCGkevmMilLAdpNQ/7JLREA=
Staten Island9999Freshkills Parkfalse622236745736552447AQMAAAABAAAAEwAAABCG53ESjVLA7uNx0EJKREBIKI6TA41SwD21cMtHSkRAz+HDFwONUsAsgW4ESkpEQNhqxDYDjVLAFwaoE0pKRECpDesZBI1SwP/FAJ1KSkRANEitAgWNUsA42e4tS0pEQIxZd6UFjVLAmzLynUtKREB/wbU= (truncated)
Staten Island9999Freshkills Parkfalse622236745743335423AQMAAAABAAAABAAAABTMGT1Vi1LAduFtzeFMRED8IWWsUItSwNkwQFTjTERA10BbHU+LUsAOw4d76kxEQBTMGT1Vi1LAduFtzeFMREA=
Staten Island9999Freshkills Parkfalse622236745742778367AQMAAAABAAAABwAAAMjQ938fi1LAVs71GgdNREDnlYqfEItSwHeVOhQMTURAGkUDFAyLUsApzsfuIE1EQFUP5A0Si1LARKI1HipNRECq0/X0KItSwD2kBAAbTURAmwD01CmLUsC0djT8Fk1EQMjQ938fi1LAVs71GgdNREA=
Staten Island9999Freshkills Parkfalse622236745682059263AQMAAAABAAAACAAAAEoLgQV1i1LAgfkcgTxMREB+WKIlZotSwFEopXpBTERAh+WMmmGLUsDtleZUVkxEQJQOau9ri1LABCuuNWZMREAXVfyqeotSwIh9R0hhTERAFEPU6XqLUsBTWqrCYExEQOmOYFp/i1LAJG7MYUxMREBKC4E= (truncated)
Staten Island9999Freshkills Parkfalse622236745692512255AQMAAAABAAAABwAAAALwKmvcilLAqbNYemJIREB2vJ853IpSwNmdr/50SERAWHcvAdyKUsBCN9QYgkhEQPOY8f7bilLAza/rj4JIREBeNuCd3opSwCw1kq+BSERAdJmqKOOKUsAqlHvXbEhEQALwKmvcilLAqbNYemJIREA=
Staten Island9999Freshkills Parkfalse622236745724428287AQMAAAABAAAABgAAAMZSGE5PjVLAaJpCITNJREB82CZnTY1SwMijbMQzSURAvNxR3kiNUsCgK7+dSElEQAxHbZdMjVLAZRebVU5JRECrqaUtTY1SwHvM1khLSURAxlIYTk+NUsBomkIhM0lEQA==
Staten Island9999Freshkills Parktrue622236745742221311null
Staten Island9999Freshkills Parkfalse622236745699295231AQMAAAABAAAACQAAAAGEYg3milLAh7X6E9tJREAZaS/H3IpSwBcHzi3eSURAuf/rg9yKUsBGXMgC6klEQPc6uO3bilLAfz1k//lJREC67Bp+24pSwLhX24ECSkRAzE8999yKUsBcG7DFBEpEQJjNyNXrilLAKAnxzP9JRECWddE= (truncated)
Staten Island9999Freshkills Parkfalse622236745680945151AQMAAAABAAAABQAAAFz96SLAi1LAv6fuC9ZLRED31iHQs4tSwLjAWSvaS0RAEzFkRa+LUsCXOoAF70tEQPqSMwqxi1LAc9VUvfFLREBc/ekiwItSwL+n7gvWS0RA
Staten Island9999Freshkills Parkfalse622236745691398143AQMAAAABAAAACAAAADbyXZAbi1LAUHp6WvlHREDU1qaYF4tSwDAqN676R0RAwUQgDhOLUsCGcySGD0hEQHg05WAdi1LAAJhaZR9IREAcETM+LItSwNxVi2waSERAqih46S+LUsBl9gOVCUhEQIlyqGAmi1LAkGwjOwJIREA28l0= (truncated)
Staten Island9999Freshkills Parkfalse622236745723314175AQMAAAABAAAAKwAAADKN8ttfjVLAUJjk78xIREBPs3k1VY1SwNZZh4HQSERA/6u+rFCNUsCn7aha5UhEQKQUpW5ZjVLAaqP9zfJIREAdsel8WY1SwFHP2pzySERAloK+AlqNUsC/MdhB8UhEQOsjZ41ajVLArDxZTPBIREBNQOs= (truncated)
Staten Island9999Freshkills Parkfalse622236745698181119AQMAAAABAAAABwAAAEwaBObtilLAFHgZ0XdJREDPsSLQ34pSwH2V0IZ8SURAbTw6+N6KUsADTpaGmElEQL3zEtDkilLArg5tgqFJREAPXl6u84pSwHArsImcSURAhv9MOfiKUsDgNP+wh0lEQEwaBObtilLAFHgZ0XdJREA=
Staten Island9999Freshkills Parkfalse622236745762013183AQMAAAABAAAACAAAAKlDKdKfilLAYkKWzZtLRECgAEmmm4pSwB7xfzKdS0RAIaR6+YyKUsB2k1D/sktEQFvg22aMilLANALWn7VLREDT9tu6lopSwGiz7YDFS0RAUASPmqWKUsCzuEiIwEtEQGu3KyaqilLA9NOVrqtLRECpQyk= (truncated)
Staten Island9999Freshkills Parkfalse622236745679831039AQMAAAABAAAABQAAAOnPVTaYjFLAmiVQE7lKREBaF51XiYxSwE3/3A2+SkRAf3rCJ4aMUsDRNUqyzEpEQKAIEl2YjFLApnjRTrlKREDpz1U2mIxSwJolUBO5SkRA
Staten Island9999Freshkills Parkfalse622236745729540095AQMAAAABAAAAKQAAALWoYbSCjVLAP1uNpuxHREBfzKk2eI1SwEr4syrwR0RAnZQ4rnONUsCW1mwDBUhEQK/0pQJ+jVLA9zj74BRIREAy0MTTho1SwM+FeewRSERAqDP8z4aNUsCKDkn/D0hEQNO6OsaGjVLA+gFRSQ9IRECKmx8= (truncated)
Staten Island9999Freshkills Parkfalse622236745736323071AQMAAAABAAAAFwAAAIGoyRJGjVLAhghTNnBJREBs9I/MP41SwEsYgFBySURAtAejQzuNUsDufO4ph0lEQFwy2K1AjVLAX3L/eo9JREDjJ6yvQI1SwEDIwS2PSURAKCQp/ECNUsCZuHejjElEQDpT429BjVLA+8AvVItJRECuUCM= (truncated)
Staten Island9999Freshkills Parkfalse622236745921593343AQMAAAABAAAABgAAAE9c1DKEjFLAFRksC8dHREBZX4RXc4xSwPfLv8XkR0RASZJXfnSMUsBAZMeK5kdEQGDnR1uDjFLAFsGbkOFHRECYG4Tkh4xSwO3OR7jMR0RAT1zUMoSMUsAVGSwLx0dEQA==
Staten Island9999Freshkills Parkfalse622236746167582719AQMAAAABAAAABgAAAE02J9mMjVLAjH4gNU1HREDTiTlhcY1SwPV8haFaR0RAFsj/N3qNUsCVSRI1aEdEQHg6dBSJjVLAMJzlOWNHRECjlbOcjY1SwBiZeWFOR0RATTYn2YyNUsCMfiA1TUdEQA==
Staten Island9999Freshkills Parkfalse622236745725313023AQMAAAABAAAACAAAAKmCacK3jFLAJQi4Ym9HREDEmav/s4xSwCv2LqVwR0RAOggkCKeMUsAoi2mciUdEQB+VN+mljFLAHNlvlotHREBgsmCwroxSwKzyKBOZR0RAHUoWjb2MUsDCSskYlEdEQFPAEBbCjFLAbK2JQH9HRECpgmk= (truncated)
Staten Island9999Freshkills Parkfalse622236745921036287AQMAAAABAAAADAAAACj9D6ZEjFLASZNCgQBIRECd6uHiQIxSwKd1+6IASERAsP9vKT2MUsBo2DU7AUhEQN7N6oI5jFLA86gvRgJIREALTGHqNoxSwC+sruUDSERA6dS0bzSMUsCkpNQMBkhEQNFvTSQyjFLASmvOsghIRECqQZk= (truncated)
Staten Island9999Freshkills Parkfalse622236745681829887AQMAAAABAAAABAAAADqjtwbNi1LAQF7MZr5LRECU2Fk6x4tSwFFJbFfAS0RA89LTEsSLUsBCCgbTzktEQDqjtwbNi1LAQF7MZr5LREA=
Staten Island9999Freshkills Parktrue622236745673932799null
Staten Island9999Freshkills Parkfalse622236745698508799AQMAAAABAAAACAAAAOwKhlXiilLAAzlNYC5JRECY1qId4IpSwMenLx4vSURAojQ9VuCKUsCemTlNNElEQCGXDLvgilLAyTTvOEVJREBRTn3L4IpSwJM6VYtVSURAsv67HeiKUsAhJ6MYU0lEQDSJpqjsilLAw1ocQD5JREDsCoY= (truncated)
Staten Island9999Freshkills Parkfalse622236746168467455AQMAAAABAAAABQAAAF3ydb1fjVLAay1OQGNHREAmxFgtSI1SwOMmG8RuR0RAuIiAok2NUsAnYz8md0dEQBjvBX9cjVLAIy0/K3JHREBd8nW9X41SwGstTkBjR0RA
Staten Island9999Freshkills Parkfalse622236745672818687AQMAAAABAAAACAAAAPvMF8oljFLAZv5VDMxKREA31z/rFoxSwIGabgbRSkRAxvULYRKMUsDBXi3g5UpEQFLyw7UcjFLAadrhv/VKREArQQmiJ4xSwFXvABjySkRAsHDnACyMUsCsmrvU7kpEQHAh0h4wjFLAWVry69tKRED7zBc= (truncated)
Staten Island9999Freshkills Parkfalse622236745758113791AQMAAAABAAAADQAAAP+Cb7V5ilLAZdUVkNBLREDS+7j2eIpSwIjMzMfTS0RAcQsE0XiKUsDcdJ9q1EtEQJE1R9x3ilLA4cEU4NlLRED8yekvd4pSwJt2BnPfS0RAbF7jzXaKUsAmLEsW5UtEQF9QvLZ2ilLA0RtOvOpLREBJd6Y= (truncated)
Staten Island9999Freshkills Parkfalse622236745679601663AQMAAAABAAAAIQAAACzMfz75jFLACcGj7DdKRECfEilg6oxSwC5oh+c8SkRA6TTabOmMUsC/y8lFQUpEQEvVcqTpjFLA1/1jR0FKRED+DH1K6oxSwE5D04ZBSkRArUzC/OqMUsAfZjgpQkpEQAgR94vrjFLApwFgu0JKRECaQlU= (truncated)
Staten Island9999Freshkills Parkfalse622236745696837631AQMAAAABAAAACAAAAHpj38Rzi1LAr3/MeDxIREBR46zxaItSwLz28BdASERAfuxfZ2SLUsBWVR7wVEhEQKGzfLpui1LAClk5z2RIREBoy+iXfYtSwIHgDtZfSERArN8hIoKLUsCHLdP9SkhEQIvvORt9i1LAUjWXQ0NIREB6Y98= (truncated)
Staten Island9999Freshkills Parkfalse622236745742876671AQMAAAABAAAACAAAALVpaxXtilLAe1PASvFMREDZhwM13opSwAy7zkP2TERA8GNUqdmKUsCpQz8eC01EQF+2ifzjilLAYJw9/RpNREClgCsC5IpSwAfxVf4aTURAATOf3vKKUsDajJcGFk1EQH9tOmr3ilLADqwYLAFNREC1aWs= (truncated)
Staten Island9999Freshkills Parkfalse622236745735536639AQMAAAABAAAACQAAAFVerKgtjVLA+GJxtsVJREAQrqbKHo1SwBhKf7HKSURAPuKLQRqNUsB0UBCL30lEQEqvipYkjVLAmr+hae9JREBpnKZ0M41SwOsIim7qSURAxGj8tjeNUsBl9+jZ1klEQBupNLw3jVLAlaqSz9VJREBS+/w= (truncated)
Staten Island9999Freshkills Parkfalse622236745763782655AQMAAAABAAAABQAAAGNgliHLilLAj5WO2+NKREDBzi5tyIpSwG9it+oGS0RAu1bxgc6KUsCuVUziBEtEQKIMRg3TilLAKNzsCPBKREBjYJYhy4pSwI+VjtvjSkRA
Staten Island9999Freshkills Parkfalse622236745742319615AQMAAAABAAAACAAAAI8a3MJZi1LAZMc/n7lMREB5rKniSotSwMfAuJi+TERARTtkV0aLUsAXyjFz00xEQPwhZaxQi1LA2TBAVONMREAUzBk9VYtSwHbhbc3hTERAhFTWEWOLUsBEdtUyzkxEQE1c3xdki1LAZg02gMlMRECPGtw= (truncated)
Staten Island9999Freshkills Parkfalse622236745699393535AQMAAAABAAAABgAAABZXx+bZilLAXJ/C5BtKREDY2MHI2IpSwGK2GsgpSkRAXnUAJteKUsAGwsezQEpEQCTefjTeilLAaUjOVz5KRED0gZ+/4opSwAiY0H4pSkRAFlfH5tmKUsBcn8LkG0pEQA==
Staten Island9999Freshkills Parkfalse622236745695723519AQMAAAABAAAACwAAAMdPtWDDi1LAoZytz1tIREDlLc9/wYtSwALEm3BcSERA8V9t4LyLUsCXZJYwX0hEQLhP40u5i1LA8J8uq2BIREAdbySWtYtSwIHEuqdhSERAkOASSrSLUsC60xrQYUhEQGgqRvmvi1LAXRV4oXVIREBplqY= (truncated)
Staten Island9999Freshkills Parkfalse622236745770565631AQMAAAABAAAABgAAAL+M8Qu7ilLABVI6N8BMRED3i+BMuopSwKqQ99/HTERAau9xW7iKUsDrU7c/3ExEQAYORKu6ilLA97vqedtMREBuDgU3v4pSwIGdnZ/GTERAv4zxC7uKUsAFUjo3wExEQA==
Staten Island9999Freshkills Parkfalse622236745692053503AQMAAAABAAAACAAAALI/Y7tIi1LAUxWdKxZIRECMFF9uRYtSwABFylIlSERABR1RwU+LUsAry+YxNUhEQJlOpJ5ei1LAYUDhODBIREBFjZ+WX4tSwIAsZcYrSERATCsLel2LUsDt3mQjKUhEQF2Yfk9Ni1LAbw26ShhIRECyP2M= (truncated)
Staten Island9999Freshkills Parktrue622236745691496447null
Staten Island9999Freshkills Parkfalse622236745762668543AQMAAAABAAAADQAAAMnMvqDSilLAgrRmC4BKREBM92Bw0opSwNJWGbGCSkRApebsSdKKUsAXBA/MhEpEQABiZi3SilLAPll8WYZKRECduvzL0YpSwMTZ76eLSkRA5LxJsNGKUsAQ+JMpjUpEQAzII43RilLAL38yF49KREAmVOM= (truncated)
Staten Island9999Freshkills Parkfalse622236745698279423AQMAAAABAAAACAAAAAdjDkXgilLAksMkW7ZJREBJ23gM3opSwJNMQBm3SURAKLotRd2KUsBYv2fx0ElEQHze3N7cilLA+ZyQA9pJREAZaS/H3IpSwBcHzi3eSURAAYRiDeaKUsCHtfoT20lEQGEgaZjqilLA2ustO8ZJREAHYw4= (truncated)
Staten Island9999Freshkills Parkfalse622236745769451519AQMAAAABAAAABQAAAOaTaHXEilLAzKLeUl9MRECiHMIJwopSwI4IEFl4TERAnkmchcKKUsDQhaoveExEQNM7QxHHilLAvESOVWNMREDmk2h1xIpSwMyi3lJfTERA
Staten Island9999Freshkills Parkfalse622236745736421375AQMAAAABAAAAKgAAAPYNYtkljVLAoMGf+yhKRED1SRz7Fo1SwK7tr/YtSkRAEIbncRKNUsDu43HQQkpEQMJl/UgVjVLAWxMyLUdKREBindMnF41SwDO4waRGSkRAAF87kheNUsBzHJ6iRkpEQKRTDvsXjVLAkmamhkZKREBYXJ4= (truncated)
Staten Island9999Freshkills Parktrue622236745921691647null
Staten Island9999Freshkills Parkfalse622236745681928191AQMAAAABAAAACQAAAE+kS3CIi1LAkbVIrSJMRECXioCQeYtSwDdI4qYnTERASguBBXWLUsCB+RyBPExEQOmOYFp/i1LAJG7MYUxMREAgk2Z1hYtSwMLhAVdKTERAEo+1M4qLUsBorzhBQExEQBOkhXCRi1LA14/F3TBMREAqAHo= (truncated)
Staten Island9999Freshkills Parktrue622236745696051199null
Staten Island9999Freshkills Parkfalse622236745692381183AQMAAAABAAAACAAAADRnJz7silLALShqJ0NIREBDE7Vg3YpSwMOM+x9ISERAKxvcqNyKUsClj6hrS0hEQALwKmvcilLAqLNYemJIREB0maoo44pSwCqUe9dsSERAeyozBvKKUsBHaODeZ0hEQJGg55D2ilLAR4fQBlNIREA0Zyc= (truncated)
Staten Island9999Freshkills Parkfalse622236745763553279AQMAAAABAAAACQAAAIkt8fzjilLAYDokEWNKREAlmiUe1YpSwJ565QloSkRA9Y6J9tOKUsAS1TZWbUpEQOeGhijTilLAx5TjnHhKREDJzL6g0opSwIK0ZguASkRAydGT5tqKUsDclGXDjEpEQFSmdcXpilLA34yayodKRECnYZo= (truncated)
Staten Island9999Freshkills Parkfalse622236746169122815AQMAAAABAAAAHwAAAHg6dBSJjVLAMJzlOWNHREAWyP83eo1SwJVJEjVoR0RATISqr3WNUsAIF4UNfUdEQDCY3QOAjVLAz4TZ6oxHREBvQmjgjo1SwDoHo++HR0RAzcxrl4+NUsAGAuGlhEdEQKUCd7+PjVLA2zRwoINHREALQHY= (truncated)
Staten Island9999Freshkills Parkfalse622236745680257023AQMAAAABAAAACAAAAMv1sAJ/jFLAcpOKLq5KREBk4/ojcIxSwBpC/CizSkRAH7MammuMUsD+KcoCyEpEQP19BO91jFLAoLU04tdKREBbrDJFfoxSwI5/sxfVSkRAf3rCJ4aMUsDRNUqyzEpEQFoXnVeJjFLATf/cDb5KREDL9bA= (truncated)
Staten Island9999Freshkills Parkfalse622236745672916991AQMAAAABAAAACAAAAHNumr8OjFLAnO3mwA1LRED7OYxMCYxSwLu7xpMPS0RAaicA9gaMUsAFuptQGktEQDmF8sQHjFLAJ/EeZRlLRECgGY+oCYxSwPpCVQAXS0RATQaFdguMUsAxYeF1FEtEQNcrki0NjFLAOGqIxxFLREBzbpo= (truncated)
Staten Island9999Freshkills Parkfalse622236745690710015AQMAAAABAAAABQAAACb5OGLcilLAURRXke1IREDfA6Iq3YpSwAHiVIL9SERAjlqPpN2KUsD/cP+mBElEQAWySBjhilLAZwy7z/RIREAm+Thi3IpSwFEUV5HtSERA
Staten Island9999Freshkills Parkfalse622236745761882111AQMAAAABAAAACgAAALIdTT2zilLA7ddL+4FLREDRx5ceqYpSwBqAPl2FS0RAlwJC5qiKUsDU7QnLhUtEQCcu9q2iilLAtVg/M5FLREAdq0/NoYpSwCvYN7eSS0RAqUMp0p+KUsBiQpbNm0tEQGu3KyaqilLA9NOVrqtLRECiLss= (truncated)
Staten Island9999Freshkills Parkfalse622236745750872063AQMAAAABAAAABgAAAAYORKu6ilLA97vqedtMREBq73FbuIpSwOtTtz/cTERAQv5NjLSKUsDKYGcwBE1EQFzYInTAilLAKfO+NQBNREBr5eX/xIpSwATDXFvrTERABg5Eq7qKUsD3u+p520xEQA==
Brooklyn133133Kensingtontrue622236751937470463null
Brooklyn133133Kensingtontrue622236751857385471null
Brooklyn133133Kensingtontrue622236751873212415null
Brooklyn133133Kensingtontrue622236751936913407null
Brooklyn133133Kensingtontrue622236751933079551null
Brooklyn133133Kensingtontrue622236751873376255null
Brooklyn133133Kensingtontrue622236751937077247null
Brooklyn133133Kensingtontrue622236751872098303null
Brooklyn133133Kensingtontrue622236751872819199null
Brooklyn133133Kensingtontrue622236751937241087null
Brooklyn133133Kensingtontrue622236751936684031null
Brooklyn133133Kensingtontrue622236751871705087null
Brooklyn133133Kensingtontrue622236751938125823null
Brooklyn133133Kensingtontrue622236751873146879null
Brooklyn133133Kensingtontrue622236751937568767null
Brooklyn133133Kensingtontrue622236751872589823null
Brooklyn133133Kensingtontrue622236751933014015null
Brooklyn133133Kensingtontrue622236751873310719null
Brooklyn133133Kensingtontrue622236751937011711null
Brooklyn133133Kensingtontrue622236751872032767null
Brooklyn133133Kensingtontrue622236751872753663null
Brooklyn133133Kensingtontrue622236751933177855null
Brooklyn133133Kensingtontrue622236751937175551null
Brooklyn133133Kensingtontrue622236751933341695null
Brooklyn133133Kensingtontrue622236751871639551null
Brooklyn133133Kensingtontrue622236751937339391null
Brooklyn133133Kensingtontrue622236751938060287null
Brooklyn133133Kensingtontrue622236751873081343null
Brooklyn133133Kensingtontrue622236751871803391null
Brooklyn133133Kensingtontrue622236751873245183null
Brooklyn133133Kensingtontrue622236751936946175null
Brooklyn133133Kensingtontrue622236751871967231null
Brooklyn133133Kensingtontrue622236751872688127null
Brooklyn133133Kensingtontrue622236751873409023null
Brooklyn133133Kensingtontrue622236751937110015null
Brooklyn133133Kensingtontrue622236751872851967null
Brooklyn133133Kensingtontrue622236751937273855null
Brooklyn133133Kensingtontrue622236751872294911null
Brooklyn133133Kensingtontrue622236751937994751null
Brooklyn133133Kensingtontrue622236751873015807null
Brooklyn133133Kensingtontrue622236751936716799null
Brooklyn133133Kensingtontrue622236751937437695null
Brooklyn133133Kensingtontrue622236751871901695null
Brooklyn133133Kensingtontrue622236751937601535null
Brooklyn133133Kensingtontrue622236751933046783null
Brooklyn133133Kensingtontrue622236751938322431null
Brooklyn133133Kensingtontrue622236751873343487null
Brooklyn133133Kensingtontrue622236751937044479null
Brooklyn133133Kensingtontrue622236751872786431null
Brooklyn133133Kensingtontrue622236751937208319null
Brooklyn133133Kensingtontrue622236751871672319null
Brooklyn133133Kensingtontrue622236751937372159null
Brooklyn133133Kensingtontrue622236751936815103null
Brooklyn133133Kensingtontrue622236751871836159null
Brooklyn133133Kensingtontrue622236751872557055null
Brooklyn133133Kensingtontrue622236751932981247null
Brooklyn133133Kensingtontrue622236751938256895null
Brooklyn133133Kensingtontrue622236751873277951null
Brooklyn133133Kensingtontrue622236751936978943null
Brooklyn133133Kensingtontrue622236751872720895null
Brooklyn133133Kensingtontrue622236751872884735null
Brooklyn133133Kensingtontrue622236751933308927null
Brooklyn133133Kensingtontrue622236751937306623null
Brooklyn133133Kensingtontrue622236751857221631null
Brooklyn133133Kensingtontrue622236751873048575null
Brooklyn133133Kensingtontrue622236751936749567null
Brooklyn133133Kensingtontrue622236751871770623null
Brooklyn133133Kensingtonfalse622236751617425407AQMAAAABAAAABwAAAFuk1FT4fVLAaMHh5nxRRECVVYdY9H1SwD3Fi8d9UURADxBsX/d9UsBOjuzxklFEQAULzkP5fVLAuN//AaBRRECTVndQ/H1SwNAtCQCfUURAb3JF6AB+UsBq1q8nilFEQFuk1FT4fVLAaMHh5nxRREA=
Brooklyn133133Kensingtonfalse622236751877046271AQMAAAABAAAABwAAAEGj2xvoflLAoddU7BdSRECDgRJf4H5SwCrlDPAdUkRAYSTMy9l+UsBwJFt5I1JEQO2jvNjTflLA02SqbChSREDWWrny1X5SwGVRuqsrUkRAHANr2OR+UsBt5Ja+JlJEQEGj2xvoflLAoddU7BdSREA=
Brooklyn133133Kensingtonfalse622236751872458751AQMAAAABAAAABwAAANEgXKx6flLAQcX68e1QREAZnLrUdX5SwEXm0YvvUERAs7lwPXF+UsCcDwRkBFFEQCyjM4t7flLAtKykTxRRREA4YGM/fn5SwLNpy2oTUURAhY2b4n1+UsA3GTSeD1FEQNEgXKx6flLAQcX68e1QREA=
Brooklyn133133Kensingtontrue622236751871999999null
Brooklyn133133Kensingtonfalse622236751933276159AQMAAAABAAAABgAAAJNWd1D8fVLA0C0JAJ9RREAFC85D+X1SwLjf/wGgUURAky60m/59UsDJ767lxFFEQA27WgYCflLAhN+oxMNRREDdCiueBn5SwAyAOuyuUURAk1Z3UPx9UsDQLQkAn1FEQA==
Brooklyn133133Kensingtonfalse622236751876882431AQMAAAABAAAACAAAAAyzeGDpflLAYhwA8BZSREBBo9sb6H5SwKHXVOwXUkRAHANr2OR+UsBt5Ja+JlJEQFBI/ybvflLAlUNhqjZSREC0zLMM/n5SwFigIr0xUkRALIZ1i/5+UsAfvWh9L1JEQLRsbafuflLAqiI0+RtSREAMs3g= (truncated)
Brooklyn133133Kensingtonfalse622236751938158591AQMAAAABAAAABgAAAPOiYf1QflLAByZ+nZFSRECuJFQXQn5SwDEvE4qWUkRA3uhx7D5+UsBjMLvqpFJEQNvH5kpHflLAoYs4I55SREDgVFj3Un5SwHEgOquUUkRA86Jh/VB+UsAHJn6dkVJEQA==
Brooklyn133133Kensingtonfalse622236751875506175AQMAAAABAAAACAAAAH/eC4drflLAF7Q8oN9QREB2wvSuYH5SwIGh+jXjUERAkiKR8Vt+UsDtGiWu51BEQAgOuApYflLAfDblZPlQREBvQ2RYYn5SwKmGklAJUURAs7lwPXF+UsCcDwRkBFFEQBmcutR1flLARebRi+9QREB/3gs= (truncated)
Brooklyn133133Kensingtonfalse622236751936782335AQMAAAABAAAACQAAACzUaK99flLAJ2tl14JSREDP+mvJbn5SwO5DJ8SHUkRAbjHMMWp+UsCSTSqdnFJEQBH63i9uflLAX9E8yKJSREAE7b91dX5SwNFT2jGhUkRAA4jWq4R+UsBX1BnYnVJEQML7W5iFflLAOCL0pJ1SREB7Rdw= (truncated)
Brooklyn133133Kensingtonfalse622236751857319935AQMAAAABAAAABgAAAIIjIicff1LA7++ImFdSREDtoN/4HH9SwI1HWoBhUkRAIoC1Ryd/UsDInhZscVJEQHrUUoUxf1LA1/bvCG5SREBqbveYJn9SwM4+8qFgUkRAgiMiJx9/UsDv74iYV1JEQA==
Brooklyn133133Kensingtonfalse622236751933112319AQMAAAABAAAACAAAANq8cCgTflLAyqZKEzJSRECf3uGPDn5SwDhJFpgzUkRAdwxdVg9+UsBaq8O4OFJEQHrwDZcSflLA1fkX0U5SREBdN7n3E35SwB2yGndYUkRAUgWc3hh+UsBXI2zYVlJEQIwkdXYdflLA4aSp/0FSREDavHA= (truncated)
Brooklyn133133Kensingtonfalse622236751937535999AQMAAAABAAAABwAAAGXD31O5flLAxhigJftRREB2j2sHt35SwFTBM+j7UURAJSUmcLJ+UsC2pQfBEFJEQFD/jL68flLANHLrrCBSREBwl37cvH5SwMO9BKMgUkRATYF/ibl+UsAGpXM0/VFEQGXD31O5flLAxhigJftRREA=
Brooklyn133133Kensingtontrue622236751877013503null
Brooklyn133133Kensingtonfalse622236751938289663AQMAAAABAAAABwAAAH87dgTPflLA3aFLmshSREC9aFoewH5SwG2/aIfNUkRAAUFvPb1+UsATCp2Z2lJEQHJVohfOflLAbw1c2dZSREDBgg/m1X5SwLyEbhXVUkRAiBumsNZ+UsAgQ1l01FJEQH87dgTPflLA3aFLmshSREA=
Brooklyn133133Kensingtonfalse622236751858368511AQMAAAABAAAABgAAAGCGxjMPf1LAAyT6C6BSREDi4M5NAH9SwB2oVfmkUkRAcztnW/x+UsBh+V3mtlJEQMbBKOUOf1LA6EEXhqhSREBc+TC8En9SwBuE4IClUkRAYIbGMw9/UsADJPoLoFJEQA==
Brooklyn133133Kensingtonfalse622236751872425983AQMAAAABAAAACAAAADhgYz9+flLAs2nLahNRREAsozOLe35SwLSspE8UUURAT47n83Z+UsDh3usnKVFEQO+jvkGBflLAneaXEzlRREBzq4fSgX5SwP17ueM4UURAxlGhNoF+UsDFpImBMlFEQN9+Qs5/flLAsfwLwCNRREA4YGM= (truncated)
Brooklyn133133Kensingtonfalse622236751933243391AQMAAAABAAAACQAAAA27WgYCflLAhN+oxMNRRECTLrSb/n1SwMnvruXEUURAHMxUi/99UsCnHwVcy1FEQCnT7qsAflLAFwFvI9NRREAct22yAn5SwGnKB5DjUURACQfUowN+UsC3++Dj6VFEQAoYULwHflLAgARpiehRREDDmyI= (truncated)
Brooklyn133133Kensingtonfalse622236751877308415AQMAAAABAAAABwAAANA9HiyyflLAKsS9MrBRREDto16Zq35SwKGyJV+yUURAhJ0dAqd+UsC+hs83x1FEQMcbXFCxflLAWIGcI9dRRECMc4qvtX5SwBZSjLHVUURADJleB7N+UsDJ0u02uVFEQNA9HiyyflLAKsS9MrBRREA=
Brooklyn133133Kensingtonfalse622236751857287167AQMAAAABAAAACAAAAHrUUoUxf1LA1/bvCG5SREAigLVHJ39SwMieFmxxUkRAEBm7sCJ/UsCFj05FhlJEQM4FhrQqf1LAw2pIppJSREAOYLMgP39SwI/dAZaCUkRAm3Zi0j9/UsDikdVuf1JEQLpltTAzf1LA50pRFXBSREB61FI= (truncated)
Brooklyn133133Kensingtonfalse622236751931244543AQMAAAABAAAABQAAADYY5W4yflLA+hE0C69SREBFdWmZLn5SwM6tkU+wUkRAITioFS5+UsA1gJKlslJEQI2xqw0xflLAhlAUKrBSREA2GOVuMn5SwPoRNAuvUkRA
Brooklyn133133Kensingtontrue622236751937961983null
Brooklyn133133Kensingtonfalse622236751937503231AQMAAAABAAAACgAAAHCXfty8flLAw70EoyBSREBQ/4y+vH5SwDRy66wgUkRAG2NFJ7h+UsCDXtSFNVJEQKdrwHXCflLAmJPDcUVSRECsl4Vb0X5SwEi9sYRAUkRA1lq58tV+UsBlUbqrK1JEQO2jvNjTflLA02SqbChSRED7TwA= (truncated)
Brooklyn133133Kensingtonfalse622236751875309567AQMAAAABAAAABQAAAI/Jx15tflLAtVNtQtdQRED0ZJE1aX5SwF5T4ivbUERAdsL0rmB+UsCBofo141BEQH/eC4drflLAF7Q8oN9QRECPycdebX5SwLVTbULXUERA
Brooklyn133133Kensingtonfalse622236751857876991AQMAAAABAAAABAAAAJt2YtI/f1LA4pHVbn9SREANYLMgP39SwJDdAZaCUkRAUfHMH0F/UsCnG/8DgVJEQJt2YtI/f1LA4pHVbn9SREA=
Brooklyn133133Kensingtonfalse622236751857418239AQMAAAABAAAABgAAABAZu7Aif1LAhY9ORYZSRECM+NbKE39SwFmquzKLUkRAYIbGMw9/UsADJPoLoFJEQFz5MLwSf1LAGoTggKVSREDOBYa0Kn9SwMNqSKaSUkRAEBm7sCJ/UsCFj05FhlJEQA==
Brooklyn133133Kensingtonfalse622236751934128127AQMAAAABAAAABwAAAFIFnN4YflLAVyNs2FZSREBdN7n3E35SwB2yGndYUkRADq4U8BV+UsAv3oBDZlJEQC/lyEIZflLAn0XIX31SRECdR9mUHn5SwKwRrp17UkRAlZq0LCN+UsDHi9bEZlJEQFIFnN4YflLAVyNs2FZSREA=
Brooklyn133133Kensingtonfalse622236751871934463AQMAAAABAAAACwAAADNjLjFHflLA9ZPyS/tQRED5HWuIQn5SwLU1S73/UERAk673Ezx+UsCJ8yHiBVFEQGxUb1k6flLA491zgQdRREBoSLPkN35SwMl0Nc0JUURAYLL4rTN+UsBQSQivDVFEQPPOX70wflLA7G05exBRREBxmx0= (truncated)
Brooklyn133133Kensingtonfalse622236751877275647AQMAAAABAAAACQAAAItziq+1flLAFlKMsdVRREDHG1xQsX5SwFiBnCPXUURAZOMYuax+UsCpXVv861FEQHaPawe3flLAVMEz6PtRREBlw99TuX5SwMYYoCX7UURA45/9brh+UsArw/hc8lFEQPNdute2flLASqcZPuFRREBTxsU= (truncated)
Brooklyn133133Kensingtonfalse622236751938093055AQMAAAABAAAACQAAAC+qEMk3flLA3xGqnYZSREC3CgbjKH5SwDjkI4qLUkRACYQoSyR+UsBmcRBjoFJEQEV1aZkuflLAzq2RT7BSREA2GOVuMn5SwPoRNAuvUkRAVSQkpzZ+UsDuy92dq1JEQN7ocew+flLAYzC76qRSRECuJFQ= (truncated)
Brooklyn133133Kensingtontrue622236751937634303null
Brooklyn133133Kensingtonfalse622236751875440639AQMAAAABAAAABwAAAJIikfFbflLA7BolrudQREDoDGM9W35SwES4C1joUERAz+nU8Eh+UsBaYBih+VBEQDNjLjFHflLA9pPyS/tQREC0da4lSX5SwF56WFH+UERACA64Clh+UsB8NuVk+VBEQJIikfFbflLA7BolrudQREA=
Brooklyn133133Kensingtonfalse622236751857254399AQMAAAABAAAACAAAAOPvGj0Mf1LAIyI1YEBSREBJx15bCH9SwCxI4KhBUkRACrdSxAN/UsBhsvSBVlJEQLjgERMOf1LAu8G9bWZSREDtoN/4HH9SwI1HWoBhUkRAgiMiJx9/UsDv74iYV1JEQBohZ+0Yf1LALNL4CVBSREDj7xo= (truncated)
Brooklyn133133Kensingtonfalse622236751938387967AQMAAAABAAAABgAAAMIN7pqcflLAddQKnLJSREDu5sdWln5SwAzhW660UkRAuy2L6pl+UsAEur0o2lJEQLEbElKiflLAqip2YddSREDiZIzppn5SwKAYQYjCUkRAwg3umpx+UsB11AqcslJEQA==
Brooklyn133133Kensingtonfalse622236751872983039AQMAAAABAAAABgAAAGxjw5QdflLAy2ycskZRREAJHTUFFX5SwNam5YZJUURAJly2lxh+UsDDCRsAb1FEQNj2xUojflLA0GDedmtRRECD/mfiJ35SwCUXkp5WUURAbGPDlB1+UsDLbJyyRlFEQA==
Brooklyn133133Kensingtonfalse622236751872065535AQMAAAABAAAABwAAAPPOX70wflLA7G05exBRRECTTLzTIn5SwPmVk7gdUURALiBBVRp+UsAHwLS8JVFEQJY3YywiflLAkytl2jFRREC70JMRMX5SwLATFe4sUURAcZsdqTV+UsATWuQVGFFEQPPOX70wflLA7G05exBRREA=
Brooklyn133133Kensingtonfalse622236751876947967AQMAAAABAAAACAAAACyGdYv+flLAH71ofS9SREC0zLMM/n5SwFigIr0xUkRAScdeWwh/UsAsSOCoQVJEQOPvGj0Mf1LAIyI1YEBSREASkbjMC39SwL1netU/UkRAb6UCegN/UsBMUi+kNVJEQBeAuNH+flLA6ayz0y9SREAshnU= (truncated)
Brooklyn133133Kensingtonfalse622236751938224127AQMAAAABAAAACQAAAK9apc+1flLApTI/m71SREDiZIzppn5SwKAYQYjCUkRAsRsSUqJ+UsCqKnZh11JEQHGZHYanflLAy/Mza99SREByYXbfqX5SwPFANuzeUkRAGdIcF71+UsDgpCSi2lJEQAFBbz29flLAEwqdmdpSREC9aFo= (truncated)
Brooklyn133133Kensingtonfalse622236751936847871AQMAAAABAAAACAAAAJj82+OWflLA4O2/1o1SREB7Rdz9h35SwJL9nMOSUkRAwvtbmIV+UsA4IvSknVJEQPTpldiTflLAIjoIkJpSREDu5sdWln5SwAzhW660UkRAwg3umpx+UsB11AqcslJEQK4kZjKhflLAuMnqwp1SRECY/Ns= (truncated)
Brooklyn133133Kensingtonfalse622236751858302975AQMAAAABAAAACAAAAEMO/v71flLAFRJpDZVSREC9RAkZ535SwNdeqfqZUkRAA+3OgeJ+UsC/4d/TrlJEQOs4ndDsflLAOpfkv75SREAAuqtD9n5SwMiy65+7UkRAcztnW/x+UsBh+V3mtlJEQOLgzk0Af1LAHahV+aRSREBDDv4= (truncated)
Brooklyn133133Kensingtonfalse622236751934095359AQMAAAABAAAACAAAAJ1H2ZQeflLArBGunXtSREAv5chCGX5SwJ9FyF99UkRAHo2Dqxl+UsAb0CA4gFJEQHuwDmsdflLAyU+QvJlSREB0mRmfHn5SwKi26EKiUkRACYQoSyR+UsBmcRBjoFJEQLcKBuMoflLAOOQjiotSRECdR9k= (truncated)
Brooklyn133133Kensingtonfalse622236751872360447AQMAAAABAAAACAAAAAaMDJquflLAcwfuuIpRRECZJ3PipX5SwItVz5qNUURAM1M0S6F+UsBYIWRzolFEQO2jXpmrflLAobIlX7JRREDQPR4ssn5SwCrEvTKwUURATgz9BLF+UsDnFL0PpFFEQID6xbuvflLAgunWWZdRREAGjAw= (truncated)
Brooklyn133133Kensingtonfalse622236751873114111AQMAAAABAAAABgAAACvdMOoSflLAIaZiHHdRRED7Shf9CX5SwHF8jAN5UURAW6TUVPh9UsBoweHmfFFEQG9yRegAflLAatavJ4pRREAlbLPND35SwKlPeTuFUURAK90w6hJ+UsAhpmIcd1FEQA==
Brooklyn133133Kensingtonfalse622236751872196607AQMAAAABAAAABgAAAIhy58SpflLArzZOHFZRREA/9d3nl35SwGcifcpZUURAs3mJnJZ+UsAMBfARWlFEQHammSugflLAemqZ1mhRRECi9nweq35SwN4W1DdlUURAiHLnxKl+UsCvNk4cVlFEQA==
Brooklyn133133Kensingtonfalse622236751871737855AQMAAAABAAAACgAAAKVccKp8flLAgyH0601RREDlKDfFbX5SwJDUldhSUURALtjSLWl+UsDll/iwZ1FEQC+Su3tzflLAYCjInHdRREALJQthgn5SwCTXHLByUURAtp5b+IZ+UsCpk6vXXVFEQAD4Rr6GflLAmcTufV1RRED2F9A= (truncated)
Brooklyn133133Kensingtonfalse622236751931179007AQMAAAABAAAABwAAAAmEKEskflLAZnEQY6BSREB0mRmfHn5SwKm26EKiUkRAK9x9FyF+UsChkx/Ds1JEQIdU3kIiflLAz6NziLxSREAhOKgVLn5SwDaAkqWyUkRARXVpmS5+UsDOrZFPsFJEQAmEKEskflLAZnEQY6BSREA=
Brooklyn133133Kensingtontrue622236751877079039null
Brooklyn133133Kensingtonfalse622236751938355199AQMAAAABAAAABQAAALEbElKiflLAqip2YddSREC7LYvqmX5SwAS6vSjaUkRAsa5ZrZp+UsCNebch4lJEQHGZHYanflLAy/Mza99SRECxGxJSon5SwKoqdmHXUkRA
Brooklyn133133Kensingtontrue622236751937437695null
Brooklyn133133Kensingtonfalse622236751858434047AQMAAAABAAAACQAAAAPtzoHiflLAv+Hf065SREDbnsab035SwCCXDsGzUkRAfzt2BM9+UsDdoUuayFJEQIgbprDWflLAIENZdNRSRECpvTwo3n5SwGeIZYTOUkRAMLeyrOp+UsCOpsWcxFJEQAZ957LrflLA4zNv0cNSREDrOJ0= (truncated)
Brooklyn133133Kensingtonfalse622236751872950271AQMAAAABAAAACQAAANj2xUojflLA0GDedmtRREAlXLaXGH5SwMQJGwBvUURAeRq/PBl+UsDgx1LDdVFEQCvdMOoSflLAIaZiHHdRREAlbLPND35SwKlPeTuFUURAAappGxp+UsCcg5InlVFEQN+C2gApflLAhshAO5BRRED9vX4= (truncated)
Brooklyn133133Kensingtonfalse622236751616376831AQMAAAABAAAABgAAAC4gQVUaflLAB8C0vCVRREBUdiNUEn5SwAI2hkotUURACR01BRV+UsDWpuWGSVFEQGxjw5QdflLAy2ycskZRRECWN2MsIn5SwJMrZdoxUURALiBBVRp+UsAHwLS8JVFEQA==
Brooklyn133133Kensingtonfalse622236751937732607AQMAAAABAAAABQAAAG4xzDFqflLAkk0qnZxSRECWOp/3Yn5SwL1ktwCfUkRAeOOJkmN+UsCItVYZpVJEQBH63i9uflLAX9E8yKJSREBuMcwxan5SwJJNKp2cUkRA
Brooklyn133133Kensingtonfalse622236751858270207AQMAAAABAAAABAAAAAG6q0P2flLAyLLrn7tSREDrOJ3Q7H5SwDqX5L++UkRABn3nsut+UsDjM2/Rw1JEQAG6q0P2flLAyLLrn7tSREA=
Brooklyn133133Kensingtontrue622236751857352703null
Brooklyn133133Kensingtonfalse622236751872327679AQMAAAABAAAACAAAALN5iZyWflLADAXwEVpRRECwEMFxin5SwD/XnbFcUURAtp5b+IZ+UsCpk6vXXVFEQAslC2GCflLAJNccsHJRREDVkwqvjH5SwHKz35uCUURAHARdlJt+UsDULRmvfVFEQHammSugflLAemqZ1mhRRECzeYk= (truncated)
Brooklyn133133Kensingtonfalse622236751933145087AQMAAAABAAAACAAAAN1tV3INflLAYpxJTg1SREBY0l8hCX5SwMZUbLsOUkRAy7o7ogp+UsAo5urRGFJEQI63eQkMflLA6OQA5SJSRECf3uGPDn5SwDhJFpgzUkRA2rxwKBN+UsDKpkoTMlJEQEioR8AXflLA4C+dOh1SREDdbVc= (truncated)
Brooklyn133133Kensingtonfalse622236751938027519AQMAAAABAAAADQAAAGJAD3tkflLAWfvi13dSREAiRRWVVX5SwFmdicR8UkRA86Jh/VB+UsAHJn6dkVJEQOBUWPdSflLAcSA6q5RSREAwJStPWH5SwDUwwVWQUkRAT4sy9Vx+UsAFeOWCjFJEQM3k3YlgflLADNFTPYlSREAgm+s= (truncated)
Brooklyn133133Kensingtonfalse622236751875375103AQMAAAABAAAABgAAAC7muJd3flLA2IIdps1QRECPycdebX5SwLVTbULXUERAf94Lh2t+UsAXtDyg31BEQBmcutR1flLARebRi+9QREDRIFysen5SwEHF+vHtUERALua4l3d+UsDYgh2mzVBEQA==
Brooklyn133133Kensingtontrue622236751936651263null
Brooklyn133133Kensingtonfalse622236751872622591AQYAAAACAAAAAQMAAAABAAAABQAAAHOrh9KBflLA/Xu54zhRREDvo75BgX5SwJ3mlxM5UURApVxwqnx+UsCDIfTrTVFEQHJxMRGFflLArfH55lpRREBzq4fSgX5SwP17ueM4UURAAQMAAAABAAAABAAAALAQwXGKflLAP9edsVw= (truncated)
Brooklyn133133Kensingtonfalse622236751872163839AQMAAAABAAAACAAAAKL2fB6rflLA3hbUN2VRREB2ppkroH5SwHpqmdZoUURAHARdlJt+UsDULRmvfVFEQJknc+KlflLAi1XPmo1RREAGjAyarn5SwHMH7riKUURApgB+RK5+UsBx7Tz+hlFEQKy81p6sflLATfgyBXZRRECi9nw= (truncated)
Brooklyn133133Kensingtonfalse622236751933439999AQMAAAABAAAABgAAAAoYULwHflLAgARpiehRREAJB9SjA35SwLf74OPpUURAWNJfIQl+UsDGVGy7DlJEQN1tV3INflLAYpxJTg1SREB1JSwKEn5SwCctsXX4UURAChhQvAd+UsCABGmJ6FFEQA==
Manhattan236236Upper East Side Northtrue622236722201296895null
Manhattan236236Upper East Side Northtrue622236722202345471null
Manhattan236236Upper East Side Northtrue622236722201591807null
Manhattan236236Upper East Side Northtrue622236722202116095null
Manhattan236236Upper East Side Northtrue622236722202640383null
Manhattan236236Upper East Side Northtrue622236722210209791null
Manhattan236236Upper East Side Northtrue622236722210504703null
Manhattan236236Upper East Side Northtrue622236722201133055null
Manhattan236236Upper East Side Northtrue622236722202181631null
Manhattan236236Upper East Side Northtrue622236722204803071null
Manhattan236236Upper East Side Northtrue622236722201952255null
Manhattan236236Upper East Side Northtrue622236722210045951null
Manhattan236236Upper East Side Northtrue622236722201493503null
Manhattan236236Upper East Side Northtrue622236722202017791null
Manhattan236236Upper East Side Northtrue622236722202542079null
Manhattan236236Upper East Side Northtrue622236722201264127null
Manhattan236236Upper East Side Northtrue622236722202312703null
Manhattan236236Upper East Side Northtrue622236722210406399null
Manhattan236236Upper East Side Northtrue622236722202083327null
Manhattan236236Upper East Side Northtrue622236722210177023null
Manhattan236236Upper East Side Northtrue622236722201329663null
Manhattan236236Upper East Side Northtrue622236722202378239null
Manhattan236236Upper East Side Northtrue622236722204999679null
Manhattan236236Upper East Side Northtrue622236722210242559null
Manhattan236236Upper East Side Northtrue622236722201395199null
Manhattan236236Upper East Side Northtrue622236722201919487null
Manhattan236236Upper East Side Northtrue622236722202443775null
Manhattan236236Upper East Side Northtrue622236722201165823null
Manhattan236236Upper East Side Northtrue622236722202214399null
Manhattan236236Upper East Side Northtrue622236722210308095null
Manhattan236236Upper East Side Northtrue622236722201460735null
Manhattan236236Upper East Side Northtrue622236722202509311null
Manhattan236236Upper East Side Northtrue622236722210078719null
Manhattan236236Upper East Side Northtrue622236722201231359null
Manhattan236236Upper East Side Northtrue622236722202279935null
Manhattan236236Upper East Side Northtrue622236722210373631null
Manhattan236236Upper East Side Northtrue622236722202050559null
Manhattan236236Upper East Side Northtrue622236722209619967null
Manhattan236236Upper East Side Northtrue622236722210144255null
Manhattan236236Upper East Side Northfalse622236722202476543AQMAAAABAAAACQAAAP+f8/YZfVLA8JO5MJhjREBrKmJ/Fn1SwMBMVVWZY0RASm2uPBZ9UsC69joMmmNEQGVAqBEOfVLA+OxhcbBjRED4yyvzCn1SwOJopQC5Y0RANK6ovhB9UsBSi3bzwWNEQDoh0K8ffVLAqGtmBr1jRECEoOs= (truncated)
Manhattan236236Upper East Side Northfalse622236722214010879AQMAAAABAAAABwAAAFlqf9difVLAzzwixkFkREBAHOl2VH1SwNN+woNGZERA36nY2k99UsC1pIplW2REQCWD/h5WfVLAU/pDEmVkRECsbjoEWX1SwNVJZE9dZERA0QvFUGB9UsB/BPqnSGREQFlqf9difVLAzzwixkFkREA=
Manhattan236236Upper East Side Northfalse622236722201985023AQMAAAABAAAACQAAANVekW+gfVLAgSja2GtjREDskrJ+kX1SwHgIaMZwY0RATIEB44x9UsB2o9enhWNEQGwvQziXfVLAqenHm5VjREC+95UYo31SwIuG/LCRY0RAiigaj6V9UsBy2+XrimNEQHTdfzWqfVLArD06Vn5jREDqm9U= (truncated)
Manhattan236236Upper East Side Northfalse622236722201821183AQMAAAABAAAACQAAACjlj5ySfVLAE3tMfapjREC4+Iarg31SwPA60mqvY0RAmoG9D399UsA7N11MxGNEQBXrEGWJfVLAHf9wQNRjREB2AA0Di31SwMfO57fTY0RAJrmEwo59UsAejzBqyWNEQNrP5mGWfVLAiDRhibRjREDq/a8= (truncated)
Manhattan236236Upper East Side Northfalse622236722210340863AQMAAAABAAAACAAAAIcX9JT4fFLAoKhTo/BjREBuepBj9nxSwG8xYFzxY0RAR2JAke98UsBKfc56BGREQOufj07qfFLADa11mBJkREBW+ktc73xSwBUvVGYaZERAUyuxTf58UsDa9V15FWREQChA++kCfVLA+GvWlwBkRECHF/Q= (truncated)
Manhattan236236Upper East Side Northfalse622236722208505855AQMAAAABAAAABQAAACdLlxO3fVLAIgROBkRjRECtcvf7s31SwNpZ0QlSY0RAPeXACLh9UsDu+mVKWGNEQFteC3C9fVLAJ7n5YkljREAnS5cTt31SwCIETgZEY0RA
Manhattan236236Upper East Side Northfalse622236722215190527AQMAAAABAAAABwAAAFTpiHgufVLAfpVN2rNkREAqu8aGH31SwNOnhce4ZERAgfdTLBt9UsBeyQ5/zGREQFvKzHQrfVLASNILXdpkREBvJaJiM31SwJCKHbjDZERAsniXUzV9UsD28R1wvmREQFTpiHgufVLAfpVN2rNkREA=
Manhattan236236Upper East Side Northfalse622236722204835839AQMAAAABAAAABwAAAAJLPg5UfVLAl601h/BiREBJMmN+TH1SwODmSFIFY0RAWgScR0x9UsCgxivoBWNEQFTqeYBTfVLAJQIDDxFjREBw5SVxYn1SwJAdvyEMY0RAnyHuT2V9UsDXNKAg/2JEQAJLPg5UfVLAl601h/BiREA=
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Showing the first 1000 rows.
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "from mosaic import displayMosaic\n", + "displayMosaic(mosaic_neighbourhoods)" + ] }, { "cell_type": "markdown", - "source": [ - "This also extends to plotting maps inside the notebook using the kepler.gl visualisation library using a notebook magic `%%mosaic_kepler`." - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "a304589f-36a7-4bef-8cd2-932ddd3acba4" + "nuid": "a304589f-36a7-4bef-8cd2-932ddd3acba4", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "This also extends to plotting maps inside the notebook using the kepler.gl visualisation library using a notebook magic `%%mosaic_kepler`." + ] }, { "cell_type": "code", - "source": [ - "from mosaic import st_aswkt\n(\n mosaic_neighbourhoods\n .select(st_aswkt(col(\"index.wkb\")).alias(\"wkt\"), col(\"index.index_id\").alias(\"h3\"))\n).createOrReplaceTempView(\"kepler_df\")" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "3be96bd5-e14d-40bd-9fc7-00dea16cb096" + "nuid": "3be96bd5-e14d-40bd-9fc7-00dea16cb096", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "from mosaic import st_aswkt\n", + "(\n", + " mosaic_neighbourhoods\n", + " .select(st_aswkt(col(\"index.wkb\")).alias(\"wkt\"), col(\"index.index_id\").alias(\"h3\"))\n", + ").createOrReplaceTempView(\"kepler_df\")" + ] }, { "cell_type": "code", - "source": [ - "%%mosaic_kepler\n\"kepler_df\" \"h3\" \"h3\"" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "ffe429bb-de6f-4118-8d7b-6484b6b2d678" + "nuid": "ffe429bb-de6f-4118-8d7b-6484b6b2d678", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
User Guide: https://docs.kepler.gl/docs/keplergl-jupyter\n
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
User Guide: https://docs.kepler.gl/docs/keplergl-jupyter\n
" - ] - } - }, - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "", - "textData": null, - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "htmlSandbox", - "arguments": {} - } - }, - "data": { - "text/html": [ - "" - ] - } - }, - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "Kepler.gl
", - "textData": null, - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "htmlSandbox", - "arguments": {} - } - }, - "data": { - "text/html": [ - "Kepler.gl
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "%%mosaic_kepler\n", + "\"kepler_df\" \"h3\" \"h3\"" + ] }, { "cell_type": "markdown", - "source": [ - "![mosaic kepler map example](../images/kepler-example.png)" - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "4323fa2c-8495-43c6-afb2-9e239e5fb6fc" + "nuid": "4323fa2c-8495-43c6-afb2-9e239e5fb6fc", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "![mosaic kepler map example](../images/kepler-example.png)" + ] }, { "cell_type": "markdown", - "source": [ - "Now the two datasets can be joined first on H3 index, with any false positives removed through a contains filter on a much simpler geometry." - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "11933dab-085c-4503-8ba1-06365caa335c" + "nuid": "11933dab-085c-4503-8ba1-06365caa335c", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "Now the two datasets can be joined first on H3 index, with any false positives removed through a contains filter on a much simpler geometry." + ] }, { "cell_type": "code", - "source": [ - "mosaic_joined_df = (\n trips_with_geom.alias(\"t\")\n .join(mosaic_neighbourhoods.alias(\"n\"), on=expr(\"t.pickup_h3 = n.index.index_id\"), how=\"inner\")\n .where(\n ~col(\"index.is_core\") | \n st_contains(\"index.wkb\", \"pickup_geom\")\n )\n)\n\nmosaic_joined_df.show()" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "98514998-1fe7-4a0c-b4f9-eebf38fb9d81" + "nuid": "98514998-1fe7-4a0c-b4f9-eebf38fb9d81", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+------------------+------------------+---------+-----------+--------+--------------------+-------+------------------+--------------------+\n|vendor_id| pickup_datetime| dropoff_datetime|passenger_count|trip_distance|pickup_longitude|pickup_latitude|rate_code_id|dropoff_longitude|dropoff_latitude|fare_amount|extra|mta_tax|tip_amount|tolls_amount|total_amount| pickup_geom| dropoff_geom| bounds| pickup_h3| dropoff_h3| borough|location_id|objectid| zone|is_core| h3| wkb|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+------------------+------------------+---------+-----------+--------+--------------------+-------+------------------+--------------------+\n| CMT|2009-11-28 13:00:00|2009-11-28 13:01:57| 1| 0.5| -73.999666| 40.733384| null| -73.991751| 40.730273| 3.3| 0.0| 0.5| 0.0| 0.0| 3.8|{1, [[[-73.999666...|{1, [[[-73.991751...|{5, [[[-80.0, 35....|622236723433046015|622236750715092991|Manhattan| 114| 114|Greenwich Village...| false|622236723433046015|[01 03 00 00 00 0...|\n| CMT|2009-11-28 13:00:00|2009-11-28 13:01:57| 1| 0.5| -73.999666| 40.733384| null| -73.991751| 40.730273| 3.3| 0.0| 0.5| 0.0| 0.0| 3.8|{1, [[[-73.999666...|{1, [[[-73.991751...|{5, [[[-80.0, 35....|622236723433046015|622236750715092991|Manhattan| 249| 249| West Village| false|622236723433046015|[01 03 00 00 00 0...|\n| CMT|2009-11-28 13:00:00|2009-11-28 13:01:57| 1| 0.5| -73.999666| 40.733384| null| -73.991751| 40.730273| 3.3| 0.0| 0.5| 0.0| 0.0| 3.8|{1, [[[-73.999666...|{1, [[[-73.991751...|{5, [[[-80.0, 35....|622236723433046015|622236750715092991|Manhattan| 113| 113|Greenwich Village...| false|622236723433046015|[01 03 00 00 00 0...|\n| CMT|2009-11-30 07:49:13|2009-11-30 08:12:38| 1| 12.9| -74.007033| 40.734931| null| -73.87277| 40.774319| 29.7| 0.0| 0.5| 6.04| 0.0| 36.24|{1, [[[-74.007033...|{1, [[[-73.87277,...|{5, [[[-80.0, 35....|622236750719975423|622236724015759359|Manhattan| 249| 249| West Village| false|622236750719975423|[01 03 00 00 00 0...|\n| CMT|2009-11-30 07:49:13|2009-11-30 08:12:38| 1| 12.9| -74.007033| 40.734931| null| -73.87277| 40.774319| 29.7| 0.0| 0.5| 6.04| 0.0| 36.24|{1, [[[-74.007033...|{1, [[[-73.87277,...|{5, [[[-80.0, 35....|622236750719975423|622236724015759359|Manhattan| 158| 158|Meatpacking/West ...| false|622236750719975423|[01 03 00 00 00 0...|\n| VTS|2009-01-03 01:55:00|2009-01-03 02:04:00| 5| 2.09| -73.993217| 40.72416| null| -73.9944| 40.74624| 7.7| 0.5| null| 0.0| 0.0| 8.2|{1, [[[-73.993217...|{1, [[[-73.9944, ...|{5, [[[-80.0, 35....|622236750717878271|622236723431276543|Manhattan| 114| 114|Greenwich Village...| false|622236750717878271|[01 03 00 00 00 0...|\n| VTS|2009-01-03 01:55:00|2009-01-03 02:04:00| 5| 2.09| -73.993217| 40.72416| null| -73.9944| 40.74624| 7.7| 0.5| null| 0.0| 0.0| 8.2|{1, [[[-73.993217...|{1, [[[-73.9944, ...|{5, [[[-80.0, 35....|622236750717878271|622236723431276543|Manhattan| 144| 144| Little Italy/NoLiTa| false|622236750717878271|[01 03 00 00 00 0...|\n| CMT|2009-12-07 10:36:06|2009-12-07 10:42:26| 1| 1.3| -73.99067| 40.73065| null| -73.975539| 40.741353| 6.1| 0.0| 0.5| 0.0| 0.0| 6.6|{1, [[[-73.99067,...|{1, [[[-73.975539...|{5, [[[-80.0, 35....|622236750715092991|622236723437502463|Manhattan| 113| 113|Greenwich Village...| false|622236750715092991|[01 03 00 00 00 0...|\n| CMT|2009-12-07 10:36:06|2009-12-07 10:42:26| 1| 1.3| -73.99067| 40.73065| null| -73.975539| 40.741353| 6.1| 0.0| 0.5| 0.0| 0.0| 6.6|{1, [[[-73.99067,...|{1, [[[-73.975539...|{5, [[[-80.0, 35....|622236750715092991|622236723437502463|Manhattan| 79| 79| East Village| false|622236750715092991|[01 03 00 00 00 0...|\n| CMT|2010-06-27 17:27:25|2010-06-27 17:47:44| 2| 5.0| -74.008459| 40.712233| 1| -73.9516| 40.718877| 15.7| 0.0| 0.5| 3.0| 0.0| 19.2|{1, [[[-74.008459...|{1, [[[-73.9516, ...|{5, [[[-80.0, 35....|622236750648639487|622236723415482367|Manhattan| 231| 231|TriBeCa/Civic Center| false|622236750648639487|[01 03 00 00 00 0...|\n| CMT|2010-06-27 17:27:25|2010-06-27 17:47:44| 2| 5.0| -74.008459| 40.712233| 1| -73.9516| 40.718877| 15.7| 0.0| 0.5| 3.0| 0.0| 19.2|{1, [[[-74.008459...|{1, [[[-73.9516, ...|{5, [[[-80.0, 35....|622236750648639487|622236723415482367|Manhattan| 261| 261| World Trade Center| false|622236750648639487|[01 03 00 00 00 0...|\n| CMT|2010-06-27 17:27:25|2010-06-27 17:47:44| 2| 5.0| -74.008459| 40.712233| 1| -73.9516| 40.718877| 15.7| 0.0| 0.5| 3.0| 0.0| 19.2|{1, [[[-74.008459...|{1, [[[-73.9516, ...|{5, [[[-80.0, 35....|622236750648639487|622236723415482367|Manhattan| 209| 209| Seaport| false|622236750648639487|[01 03 00 00 00 0...|\n| CMT|2009-11-17 16:50:35|2009-11-17 17:01:34| 1| 1.6| -74.00679| 40.730546| null| -73.9904| 40.73815| 7.7| 1.0| 0.5| 1.5| 0.0| 10.7|{1, [[[-74.00679,...|{1, [[[-73.9904, ...|{5, [[[-80.0, 35....|622236750718894079|622236723426754559|Manhattan| 249| 249| West Village| false|622236750718894079|[01 03 00 00 00 0...|\n| CMT|2009-11-17 16:50:35|2009-11-17 17:01:34| 1| 1.6| -74.00679| 40.730546| null| -73.9904| 40.73815| 7.7| 1.0| 0.5| 1.5| 0.0| 10.7|{1, [[[-74.00679,...|{1, [[[-73.9904, ...|{5, [[[-80.0, 35....|622236750718894079|622236723426754559|Manhattan| 158| 158|Meatpacking/West ...| false|622236750718894079|[01 03 00 00 00 0...|\n| CMT|2009-11-30 23:30:43|2009-11-30 23:42:54| 2| 2.9| -74.009605| 40.710155| null| -73.993875| 40.741554| 10.1| 0.5| 0.5| 2.22| 0.0| 13.32|{1, [[[-74.009605...|{1, [[[-73.993875...|{5, [[[-80.0, 35....|622236750646968319|622236723430490111|Manhattan| 87| 87|Financial Distric...| false|622236750646968319|[01 03 00 00 00 0...|\n| CMT|2009-11-30 23:30:43|2009-11-30 23:42:54| 2| 2.9| -74.009605| 40.710155| null| -73.993875| 40.741554| 10.1| 0.5| 0.5| 2.22| 0.0| 13.32|{1, [[[-74.009605...|{1, [[[-73.993875...|{5, [[[-80.0, 35....|622236750646968319|622236723430490111|Manhattan| 261| 261| World Trade Center| false|622236750646968319|[01 03 00 00 00 0...|\n| CMT|2010-09-21 07:44:41|2010-09-21 08:07:03| 1| 4.2| -74.008626| 40.7042| 1| -73.981636| 40.758581| 14.5| 0.0| 0.5| 1.2| 0.0| 16.2|{1, [[[-74.008626...|{1, [[[-73.981636...|{5, [[[-80.0, 35....|622236750650671103|622236723500384255|Manhattan| 87| 87|Financial Distric...| false|622236750650671103|[01 03 00 00 00 0...|\n| CMT|2010-09-21 07:44:41|2010-09-21 08:07:03| 1| 4.2| -74.008626| 40.7042| 1| -73.981636| 40.758581| 14.5| 0.0| 0.5| 1.2| 0.0| 16.2|{1, [[[-74.008626...|{1, [[[-73.981636...|{5, [[[-80.0, 35....|622236750650671103|622236723500384255|Manhattan| 88| 88|Financial Distric...| false|622236750650671103|[01 03 00 00 00 0...|\n| VTS|2010-10-10 08:56:00|2010-10-10 09:01:00| 1| 1.96| -74.012115| 40.707623| 1| -73.999272| 40.734073| 6.5| 0.0| 0.5| 0.0| 0.0| 7.0|{1, [[[-74.012115...|{1, [[[-73.999272...|{5, [[[-80.0, 35....|622236750639693823|622236723433013247|Manhattan| 87| 87|Financial Distric...| false|622236750639693823|[01 03 00 00 00 0...|\n| VTS|2010-10-10 08:56:00|2010-10-10 09:01:00| 1| 1.96| -74.012115| 40.707623| 1| -73.999272| 40.734073| 6.5| 0.0| 0.5| 0.0| 0.0| 7.0|{1, [[[-74.012115...|{1, [[[-73.999272...|{5, [[[-80.0, 35....|622236750639693823|622236723433013247|Manhattan| 261| 261| World Trade Center| false|622236750639693823|[01 03 00 00 00 0...|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+------------------+------------------+---------+-----------+--------+--------------------+-------+------------------+--------------------+\nonly showing top 20 rows\n\n
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+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+------------------+------------------+---------+-----------+--------+--------------------+-------+------------------+--------------------+\nvendor_id| pickup_datetime| dropoff_datetime|passenger_count|trip_distance|pickup_longitude|pickup_latitude|rate_code_id|dropoff_longitude|dropoff_latitude|fare_amount|extra|mta_tax|tip_amount|tolls_amount|total_amount| pickup_geom| dropoff_geom| bounds| pickup_h3| dropoff_h3| borough|location_id|objectid| zone|is_core| h3| wkb|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+------------------+------------------+---------+-----------+--------+--------------------+-------+------------------+--------------------+\n CMT|2009-11-28 13:00:00|2009-11-28 13:01:57| 1| 0.5| -73.999666| 40.733384| null| -73.991751| 40.730273| 3.3| 0.0| 0.5| 0.0| 0.0| 3.8|{1, [[[-73.999666...|{1, [[[-73.991751...|{5, [[[-80.0, 35....|622236723433046015|622236750715092991|Manhattan| 114| 114|Greenwich Village...| false|622236723433046015|[01 03 00 00 00 0...|\n CMT|2009-11-28 13:00:00|2009-11-28 13:01:57| 1| 0.5| -73.999666| 40.733384| null| -73.991751| 40.730273| 3.3| 0.0| 0.5| 0.0| 0.0| 3.8|{1, [[[-73.999666...|{1, [[[-73.991751...|{5, [[[-80.0, 35....|622236723433046015|622236750715092991|Manhattan| 249| 249| West Village| false|622236723433046015|[01 03 00 00 00 0...|\n CMT|2009-11-28 13:00:00|2009-11-28 13:01:57| 1| 0.5| -73.999666| 40.733384| null| -73.991751| 40.730273| 3.3| 0.0| 0.5| 0.0| 0.0| 3.8|{1, [[[-73.999666...|{1, [[[-73.991751...|{5, [[[-80.0, 35....|622236723433046015|622236750715092991|Manhattan| 113| 113|Greenwich Village...| false|622236723433046015|[01 03 00 00 00 0...|\n CMT|2009-11-30 07:49:13|2009-11-30 08:12:38| 1| 12.9| -74.007033| 40.734931| null| -73.87277| 40.774319| 29.7| 0.0| 0.5| 6.04| 0.0| 36.24|{1, [[[-74.007033...|{1, [[[-73.87277,...|{5, [[[-80.0, 35....|622236750719975423|622236724015759359|Manhattan| 249| 249| West Village| false|622236750719975423|[01 03 00 00 00 0...|\n CMT|2009-11-30 07:49:13|2009-11-30 08:12:38| 1| 12.9| -74.007033| 40.734931| null| -73.87277| 40.774319| 29.7| 0.0| 0.5| 6.04| 0.0| 36.24|{1, [[[-74.007033...|{1, [[[-73.87277,...|{5, [[[-80.0, 35....|622236750719975423|622236724015759359|Manhattan| 158| 158|Meatpacking/West ...| false|622236750719975423|[01 03 00 00 00 0...|\n VTS|2009-01-03 01:55:00|2009-01-03 02:04:00| 5| 2.09| -73.993217| 40.72416| null| -73.9944| 40.74624| 7.7| 0.5| null| 0.0| 0.0| 8.2|{1, [[[-73.993217...|{1, [[[-73.9944, ...|{5, [[[-80.0, 35....|622236750717878271|622236723431276543|Manhattan| 114| 114|Greenwich Village...| false|622236750717878271|[01 03 00 00 00 0...|\n VTS|2009-01-03 01:55:00|2009-01-03 02:04:00| 5| 2.09| -73.993217| 40.72416| null| -73.9944| 40.74624| 7.7| 0.5| null| 0.0| 0.0| 8.2|{1, [[[-73.993217...|{1, [[[-73.9944, ...|{5, [[[-80.0, 35....|622236750717878271|622236723431276543|Manhattan| 144| 144| Little Italy/NoLiTa| false|622236750717878271|[01 03 00 00 00 0...|\n CMT|2009-12-07 10:36:06|2009-12-07 10:42:26| 1| 1.3| -73.99067| 40.73065| null| -73.975539| 40.741353| 6.1| 0.0| 0.5| 0.0| 0.0| 6.6|{1, [[[-73.99067,...|{1, [[[-73.975539...|{5, [[[-80.0, 35....|622236750715092991|622236723437502463|Manhattan| 113| 113|Greenwich Village...| false|622236750715092991|[01 03 00 00 00 0...|\n CMT|2009-12-07 10:36:06|2009-12-07 10:42:26| 1| 1.3| -73.99067| 40.73065| null| -73.975539| 40.741353| 6.1| 0.0| 0.5| 0.0| 0.0| 6.6|{1, [[[-73.99067,...|{1, [[[-73.975539...|{5, [[[-80.0, 35....|622236750715092991|622236723437502463|Manhattan| 79| 79| East Village| false|622236750715092991|[01 03 00 00 00 0...|\n CMT|2010-06-27 17:27:25|2010-06-27 17:47:44| 2| 5.0| -74.008459| 40.712233| 1| -73.9516| 40.718877| 15.7| 0.0| 0.5| 3.0| 0.0| 19.2|{1, [[[-74.008459...|{1, [[[-73.9516, ...|{5, [[[-80.0, 35....|622236750648639487|622236723415482367|Manhattan| 231| 231|TriBeCa/Civic Center| false|622236750648639487|[01 03 00 00 00 0...|\n CMT|2010-06-27 17:27:25|2010-06-27 17:47:44| 2| 5.0| -74.008459| 40.712233| 1| -73.9516| 40.718877| 15.7| 0.0| 0.5| 3.0| 0.0| 19.2|{1, [[[-74.008459...|{1, [[[-73.9516, ...|{5, [[[-80.0, 35....|622236750648639487|622236723415482367|Manhattan| 261| 261| World Trade Center| false|622236750648639487|[01 03 00 00 00 0...|\n CMT|2010-06-27 17:27:25|2010-06-27 17:47:44| 2| 5.0| -74.008459| 40.712233| 1| -73.9516| 40.718877| 15.7| 0.0| 0.5| 3.0| 0.0| 19.2|{1, [[[-74.008459...|{1, [[[-73.9516, ...|{5, [[[-80.0, 35....|622236750648639487|622236723415482367|Manhattan| 209| 209| Seaport| false|622236750648639487|[01 03 00 00 00 0...|\n CMT|2009-11-17 16:50:35|2009-11-17 17:01:34| 1| 1.6| -74.00679| 40.730546| null| -73.9904| 40.73815| 7.7| 1.0| 0.5| 1.5| 0.0| 10.7|{1, [[[-74.00679,...|{1, [[[-73.9904, ...|{5, [[[-80.0, 35....|622236750718894079|622236723426754559|Manhattan| 249| 249| West Village| false|622236750718894079|[01 03 00 00 00 0...|\n CMT|2009-11-17 16:50:35|2009-11-17 17:01:34| 1| 1.6| -74.00679| 40.730546| null| -73.9904| 40.73815| 7.7| 1.0| 0.5| 1.5| 0.0| 10.7|{1, [[[-74.00679,...|{1, [[[-73.9904, ...|{5, [[[-80.0, 35....|622236750718894079|622236723426754559|Manhattan| 158| 158|Meatpacking/West ...| false|622236750718894079|[01 03 00 00 00 0...|\n CMT|2009-11-30 23:30:43|2009-11-30 23:42:54| 2| 2.9| -74.009605| 40.710155| null| -73.993875| 40.741554| 10.1| 0.5| 0.5| 2.22| 0.0| 13.32|{1, [[[-74.009605...|{1, [[[-73.993875...|{5, [[[-80.0, 35....|622236750646968319|622236723430490111|Manhattan| 87| 87|Financial Distric...| false|622236750646968319|[01 03 00 00 00 0...|\n CMT|2009-11-30 23:30:43|2009-11-30 23:42:54| 2| 2.9| -74.009605| 40.710155| null| -73.993875| 40.741554| 10.1| 0.5| 0.5| 2.22| 0.0| 13.32|{1, [[[-74.009605...|{1, [[[-73.993875...|{5, [[[-80.0, 35....|622236750646968319|622236723430490111|Manhattan| 261| 261| World Trade Center| false|622236750646968319|[01 03 00 00 00 0...|\n CMT|2010-09-21 07:44:41|2010-09-21 08:07:03| 1| 4.2| -74.008626| 40.7042| 1| -73.981636| 40.758581| 14.5| 0.0| 0.5| 1.2| 0.0| 16.2|{1, [[[-74.008626...|{1, [[[-73.981636...|{5, [[[-80.0, 35....|622236750650671103|622236723500384255|Manhattan| 87| 87|Financial Distric...| false|622236750650671103|[01 03 00 00 00 0...|\n CMT|2010-09-21 07:44:41|2010-09-21 08:07:03| 1| 4.2| -74.008626| 40.7042| 1| -73.981636| 40.758581| 14.5| 0.0| 0.5| 1.2| 0.0| 16.2|{1, [[[-74.008626...|{1, [[[-73.981636...|{5, [[[-80.0, 35....|622236750650671103|622236723500384255|Manhattan| 88| 88|Financial Distric...| false|622236750650671103|[01 03 00 00 00 0...|\n VTS|2010-10-10 08:56:00|2010-10-10 09:01:00| 1| 1.96| -74.012115| 40.707623| 1| -73.999272| 40.734073| 6.5| 0.0| 0.5| 0.0| 0.0| 7.0|{1, [[[-74.012115...|{1, [[[-73.999272...|{5, [[[-80.0, 35....|622236750639693823|622236723433013247|Manhattan| 87| 87|Financial Distric...| false|622236750639693823|[01 03 00 00 00 0...|\n VTS|2010-10-10 08:56:00|2010-10-10 09:01:00| 1| 1.96| -74.012115| 40.707623| 1| -73.999272| 40.734073| 6.5| 0.0| 0.5| 0.0| 0.0| 7.0|{1, [[[-74.012115...|{1, [[[-73.999272...|{5, [[[-80.0, 35....|622236750639693823|622236723433013247|Manhattan| 261| 261| World Trade Center| false|622236750639693823|[01 03 00 00 00 0...|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+------------------+------------------+---------+-----------+--------+--------------------+-------+------------------+--------------------+\nonly showing top 20 rows\n\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "mosaic_joined_df = (\n", + " trips_with_geom.alias(\"t\")\n", + " .join(mosaic_neighbourhoods.alias(\"n\"), on=expr(\"t.pickup_h3 = n.index.index_id\"), how=\"inner\")\n", + " .where(\n", + " ~col(\"index.is_core\") | \n", + " st_contains(\"index.wkb\", \"pickup_geom\")\n", + " )\n", + ")\n", + "\n", + "mosaic_joined_df.show()" + ] }, { "cell_type": "markdown", - "source": [ - "## MosaicFrame abstraction for simple indexing and joins" - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "6ad416fa-3a36-4946-98f9-b8d306d31dc5" + "nuid": "6ad416fa-3a36-4946-98f9-b8d306d31dc5", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "## MosaicFrame abstraction for simple indexing and joins" + ] }, { "cell_type": "markdown", - "source": [ - "By wrapping our Spark DataFrames with `MosaicFrame`, we can simplify the join process. For example:" - ], "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "aba08cb2-fbbb-4de7-acdc-5eac0c12b91b" + "nuid": "aba08cb2-fbbb-4de7-acdc-5eac0c12b91b", + "showTitle": false, + "title": "" } - } + }, + "source": [ + "By wrapping our Spark DataFrames with `MosaicFrame`, we can simplify the join process. For example:" + ] }, { "cell_type": "code", - "source": [ - "from mosaic import MosaicFrame" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "54194240-dc88-42dc-a7e0-8b4a97a496f8" + "nuid": "54194240-dc88-42dc-a7e0-8b4a97a496f8", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "from mosaic import MosaicFrame" + ] }, { "cell_type": "code", - "source": [ - "trips_mdf = MosaicFrame(trips, \"pickup_geom\")\nneighbourhoods_mdf = MosaicFrame(geoJsonDF, \"geometry\")" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "94730cc1-afc1-4227-9c91-709a18bb6eec" + "nuid": "94730cc1-afc1-4227-9c91-709a18bb6eec", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
", - "removedWidgets": [], - "addedWidgets": {}, - "metadata": {}, - "type": "html", - "arguments": {} - } - }, - "data": { - "text/html": [ - "\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "trips_mdf = MosaicFrame(trips, \"pickup_geom\")\n", + "neighbourhoods_mdf = MosaicFrame(geoJsonDF, \"geometry\")" + ] }, { "cell_type": "code", - "source": [ - "(\n trips_mdf\n .set_index_resolution(10)\n .apply_index()\n .join(\n neighbourhoods_mdf\n .set_index_resolution(10)\n .apply_index()\n )\n).show()" - ], + "execution_count": 0, "metadata": { "application/vnd.databricks.v1+cell": { - "title": "", - "showTitle": false, + "cellMetadata": {}, "inputWidgets": {}, - "nuid": "a33782bb-3d4f-44e8-a33b-faeb11d0de46" + "nuid": "a33782bb-3d4f-44e8-a33b-faeb11d0de46", + "showTitle": false, + "title": "" } }, - "outputs": [ - { - "output_type": "display_data", - "metadata": { - "application/vnd.databricks.v1+output": { - "datasetInfos": [], - "data": "
+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+\n|vendor_id| pickup_datetime| dropoff_datetime|passenger_count|trip_distance|pickup_longitude|pickup_latitude|rate_code_id|dropoff_longitude|dropoff_latitude|fare_amount|extra|mta_tax|tip_amount|tolls_amount|total_amount| pickup_geom| dropoff_geom| bounds|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+\n| CMT|2009-10-12 19:35:21|2009-10-12 19:44:36| 1| 1.4| -74.000018| 40.720534| null| -73.995008| 40.734112| 6.5| 0.0| null| 0.0| 0.0| 6.5|{1, [[[-74.000018...|{1, [[[-73.995008...|{5, [[[-80.0, 35....|\n| CMT|2010-09-02 07:37:40|2010-09-02 07:53:17| 1| 6.8| -74.016477| 40.70971| 1| -73.97509| 40.759392| 17.3| 0.0| 0.5| 1.0| 0.0| 18.8|{1, [[[-74.016477...|{1, [[[-73.97509,...|{5, [[[-80.0, 35....|\n| CMT|2009-11-28 13:00:00|2009-11-28 13:01:57| 1| 0.5| -73.999666| 40.733384| null| -73.991751| 40.730273| 3.3| 0.0| 0.5| 0.0| 0.0| 3.8|{1, [[[-73.999666...|{1, [[[-73.991751...|{5, [[[-80.0, 35....|\n| CMT|2009-11-30 07:49:13|2009-11-30 08:12:38| 1| 12.9| -74.007033| 40.734931| null| -73.87277| 40.774319| 29.7| 0.0| 0.5| 6.04| 0.0| 36.24|{1, [[[-74.007033...|{1, [[[-73.87277,...|{5, [[[-80.0, 35....|\n| VTS|2009-01-03 01:55:00|2009-01-03 02:04:00| 5| 2.09| -73.993217| 40.72416| null| -73.9944| 40.74624| 7.7| 0.5| null| 0.0| 0.0| 8.2|{1, [[[-73.993217...|{1, [[[-73.9944, ...|{5, [[[-80.0, 35....|\n| VTS|2009-11-09 17:21:00|2009-11-09 17:32:00| 1| 5.19| -74.010003| 40.707022| null| -73.963853| 40.75677| 13.3| 1.0| 0.5| 0.0| 0.0| 14.8|{1, [[[-74.010003...|{1, [[[-73.963853...|{5, [[[-80.0, 35....|\n| VTS|2010-06-09 01:13:00|2010-06-09 01:27:00| 1| 8.09| -74.008697| 40.707335| 1| -73.949605| 40.78761| 19.7| 0.5| 0.5| 0.0| 0.0| 20.7|{1, [[[-74.008697...|{1, [[[-73.949605...|{5, [[[-80.0, 35....|\n| VTS|2009-01-28 18:36:00|2009-01-28 18:50:00| 1| 2.92| -74.008823| 40.72089| null| -73.994055| 40.747588| 10.1| 1.0| null| 3.0| 0.0| 14.1|{1, [[[-74.008823...|{1, [[[-73.994055...|{5, [[[-80.0, 35....|\n| CMT|2010-06-02 14:21:05|2010-06-02 14:28:43| 1| 5.0| -74.011653| 40.702604| 1| -73.971851| 40.749807| 12.5| 0.0| 0.5| 2.6| 0.0| 15.6|{1, [[[-74.011653...|{1, [[[-73.971851...|{5, [[[-80.0, 35....|\n| VTS|2009-11-26 15:38:00|2009-11-26 15:47:00| 5| 2.36| -73.997208| 40.722108| null| -73.99647| 40.748185| 8.1| 0.0| 0.5| 2.0| 0.0| 10.6|{1, [[[-73.997208...|{1, [[[-73.99647,...|{5, [[[-80.0, 35....|\n| CMT|2009-12-07 10:36:06|2009-12-07 10:42:26| 1| 1.3| -73.99067| 40.73065| null| -73.975539| 40.741353| 6.1| 0.0| 0.5| 0.0| 0.0| 6.6|{1, [[[-73.99067,...|{1, [[[-73.975539...|{5, [[[-80.0, 35....|\n| CMT|2009-11-15 09:11:42|2009-11-15 09:26:34| 1| 3.7| -73.990065| 40.687341| null| -73.999566| 40.730219| 12.1| 0.0| 0.5| 0.0| 0.0| 12.6|{1, [[[-73.990065...|{1, [[[-73.999566...|{5, [[[-80.0, 35....|\n| CMT|2010-06-27 17:27:25|2010-06-27 17:47:44| 2| 5.0| -74.008459| 40.712233| 1| -73.9516| 40.718877| 15.7| 0.0| 0.5| 3.0| 0.0| 19.2|{1, [[[-74.008459...|{1, [[[-73.9516, ...|{5, [[[-80.0, 35....|\n| VTS|2009-01-30 21:05:00|2009-01-30 21:34:00| 1| 5.99| -73.994397| 40.694843| null| -73.921257| 40.685107| 18.9| 0.5| null| 0.6| 0.0| 20.0|{1, [[[-73.994397...|{1, [[[-73.921257...|{5, [[[-80.0, 35....|\n| CMT|2009-01-14 07:43:53|2009-01-14 07:55:14| 2| 2.9| -74.007602| 40.725098| null| -73.977846| 40.751608| 9.3| 0.0| null| 0.0| 0.0| 9.3|{1, [[[-74.007602...|{1, [[[-73.977846...|{5, [[[-80.0, 35....|\n| VTS|2010-05-11 16:33:00|2010-05-11 16:41:00| 1| 0.99| -74.011205| 40.715468| 1| -74.011072| 40.708882| 5.7| 1.0| 0.5| 0.0| 0.0| 7.2|{1, [[[-74.011205...|{1, [[[-74.011072...|{5, [[[-80.0, 35....|\n| VTS|2009-01-19 09:43:00|2009-01-19 09:47:00| 1| 0.56| -73.991123| 40.731297| null| -73.98681| 40.736703| 4.1| 0.0| null| 0.0| 0.0| 4.1|{1, [[[-73.991123...|{1, [[[-73.98681,...|{5, [[[-80.0, 35....|\n| CMT|2009-11-14 15:46:36|2009-11-14 15:51:01| 2| 1.2| -74.008448| 40.734271| null| -74.006075| 40.720237| 4.9| 0.0| 0.5| 0.0| 0.0| 5.4|{1, [[[-74.008448...|{1, [[[-74.006075...|{5, [[[-80.0, 35....|\n| CMT|2009-11-17 16:50:35|2009-11-17 17:01:34| 1| 1.6| -74.00679| 40.730546| null| -73.9904| 40.73815| 7.7| 1.0| 0.5| 1.5| 0.0| 10.7|{1, [[[-74.00679,...|{1, [[[-73.9904, ...|{5, [[[-80.0, 35....|\n| CMT|2009-11-30 23:30:43|2009-11-30 23:42:54| 2| 2.9| -74.009605| 40.710155| null| -73.993875| 40.741554| 10.1| 0.5| 0.5| 2.22| 0.0| 13.32|{1, [[[-74.009605...|{1, [[[-73.993875...|{5, [[[-80.0, 35....|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+\nonly showing top 20 rows\n\n
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+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+\nvendor_id| pickup_datetime| dropoff_datetime|passenger_count|trip_distance|pickup_longitude|pickup_latitude|rate_code_id|dropoff_longitude|dropoff_latitude|fare_amount|extra|mta_tax|tip_amount|tolls_amount|total_amount| pickup_geom| dropoff_geom| bounds|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+\n CMT|2009-10-12 19:35:21|2009-10-12 19:44:36| 1| 1.4| -74.000018| 40.720534| null| -73.995008| 40.734112| 6.5| 0.0| null| 0.0| 0.0| 6.5|{1, [[[-74.000018...|{1, [[[-73.995008...|{5, [[[-80.0, 35....|\n CMT|2010-09-02 07:37:40|2010-09-02 07:53:17| 1| 6.8| -74.016477| 40.70971| 1| -73.97509| 40.759392| 17.3| 0.0| 0.5| 1.0| 0.0| 18.8|{1, [[[-74.016477...|{1, [[[-73.97509,...|{5, [[[-80.0, 35....|\n CMT|2009-11-28 13:00:00|2009-11-28 13:01:57| 1| 0.5| -73.999666| 40.733384| null| -73.991751| 40.730273| 3.3| 0.0| 0.5| 0.0| 0.0| 3.8|{1, [[[-73.999666...|{1, [[[-73.991751...|{5, [[[-80.0, 35....|\n CMT|2009-11-30 07:49:13|2009-11-30 08:12:38| 1| 12.9| -74.007033| 40.734931| null| -73.87277| 40.774319| 29.7| 0.0| 0.5| 6.04| 0.0| 36.24|{1, [[[-74.007033...|{1, [[[-73.87277,...|{5, [[[-80.0, 35....|\n VTS|2009-01-03 01:55:00|2009-01-03 02:04:00| 5| 2.09| -73.993217| 40.72416| null| -73.9944| 40.74624| 7.7| 0.5| null| 0.0| 0.0| 8.2|{1, [[[-73.993217...|{1, [[[-73.9944, ...|{5, [[[-80.0, 35....|\n VTS|2009-11-09 17:21:00|2009-11-09 17:32:00| 1| 5.19| -74.010003| 40.707022| null| -73.963853| 40.75677| 13.3| 1.0| 0.5| 0.0| 0.0| 14.8|{1, [[[-74.010003...|{1, [[[-73.963853...|{5, [[[-80.0, 35....|\n VTS|2010-06-09 01:13:00|2010-06-09 01:27:00| 1| 8.09| -74.008697| 40.707335| 1| -73.949605| 40.78761| 19.7| 0.5| 0.5| 0.0| 0.0| 20.7|{1, [[[-74.008697...|{1, [[[-73.949605...|{5, [[[-80.0, 35....|\n VTS|2009-01-28 18:36:00|2009-01-28 18:50:00| 1| 2.92| -74.008823| 40.72089| null| -73.994055| 40.747588| 10.1| 1.0| null| 3.0| 0.0| 14.1|{1, [[[-74.008823...|{1, [[[-73.994055...|{5, [[[-80.0, 35....|\n CMT|2010-06-02 14:21:05|2010-06-02 14:28:43| 1| 5.0| -74.011653| 40.702604| 1| -73.971851| 40.749807| 12.5| 0.0| 0.5| 2.6| 0.0| 15.6|{1, [[[-74.011653...|{1, [[[-73.971851...|{5, [[[-80.0, 35....|\n VTS|2009-11-26 15:38:00|2009-11-26 15:47:00| 5| 2.36| -73.997208| 40.722108| null| -73.99647| 40.748185| 8.1| 0.0| 0.5| 2.0| 0.0| 10.6|{1, [[[-73.997208...|{1, [[[-73.99647,...|{5, [[[-80.0, 35....|\n CMT|2009-12-07 10:36:06|2009-12-07 10:42:26| 1| 1.3| -73.99067| 40.73065| null| -73.975539| 40.741353| 6.1| 0.0| 0.5| 0.0| 0.0| 6.6|{1, [[[-73.99067,...|{1, [[[-73.975539...|{5, [[[-80.0, 35....|\n CMT|2009-11-15 09:11:42|2009-11-15 09:26:34| 1| 3.7| -73.990065| 40.687341| null| -73.999566| 40.730219| 12.1| 0.0| 0.5| 0.0| 0.0| 12.6|{1, [[[-73.990065...|{1, [[[-73.999566...|{5, [[[-80.0, 35....|\n CMT|2010-06-27 17:27:25|2010-06-27 17:47:44| 2| 5.0| -74.008459| 40.712233| 1| -73.9516| 40.718877| 15.7| 0.0| 0.5| 3.0| 0.0| 19.2|{1, [[[-74.008459...|{1, [[[-73.9516, ...|{5, [[[-80.0, 35....|\n VTS|2009-01-30 21:05:00|2009-01-30 21:34:00| 1| 5.99| -73.994397| 40.694843| null| -73.921257| 40.685107| 18.9| 0.5| null| 0.6| 0.0| 20.0|{1, [[[-73.994397...|{1, [[[-73.921257...|{5, [[[-80.0, 35....|\n CMT|2009-01-14 07:43:53|2009-01-14 07:55:14| 2| 2.9| -74.007602| 40.725098| null| -73.977846| 40.751608| 9.3| 0.0| null| 0.0| 0.0| 9.3|{1, [[[-74.007602...|{1, [[[-73.977846...|{5, [[[-80.0, 35....|\n VTS|2010-05-11 16:33:00|2010-05-11 16:41:00| 1| 0.99| -74.011205| 40.715468| 1| -74.011072| 40.708882| 5.7| 1.0| 0.5| 0.0| 0.0| 7.2|{1, [[[-74.011205...|{1, [[[-74.011072...|{5, [[[-80.0, 35....|\n VTS|2009-01-19 09:43:00|2009-01-19 09:47:00| 1| 0.56| -73.991123| 40.731297| null| -73.98681| 40.736703| 4.1| 0.0| null| 0.0| 0.0| 4.1|{1, [[[-73.991123...|{1, [[[-73.98681,...|{5, [[[-80.0, 35....|\n CMT|2009-11-14 15:46:36|2009-11-14 15:51:01| 2| 1.2| -74.008448| 40.734271| null| -74.006075| 40.720237| 4.9| 0.0| 0.5| 0.0| 0.0| 5.4|{1, [[[-74.008448...|{1, [[[-74.006075...|{5, [[[-80.0, 35....|\n CMT|2009-11-17 16:50:35|2009-11-17 17:01:34| 1| 1.6| -74.00679| 40.730546| null| -73.9904| 40.73815| 7.7| 1.0| 0.5| 1.5| 0.0| 10.7|{1, [[[-74.00679,...|{1, [[[-73.9904, ...|{5, [[[-80.0, 35....|\n CMT|2009-11-30 23:30:43|2009-11-30 23:42:54| 2| 2.9| -74.009605| 40.710155| null| -73.993875| 40.741554| 10.1| 0.5| 0.5| 2.22| 0.0| 13.32|{1, [[[-74.009605...|{1, [[[-73.993875...|{5, [[[-80.0, 35....|\n+---------+-------------------+-------------------+---------------+-------------+----------------+---------------+------------+-----------------+----------------+-----------+-----+-------+----------+------------+------------+--------------------+--------------------+--------------------+\nonly showing top 20 rows\n\n
" - ] - } - } - ], - "execution_count": 0 + "outputs": [], + "source": [ + "(\n", + " trips_mdf\n", + " .set_index_resolution(10)\n", + " .apply_index()\n", + " .join(\n", + " neighbourhoods_mdf\n", + " .set_index_resolution(10)\n", + " .apply_index()\n", + " )\n", + ").show()" + ] } ], "metadata": { "application/vnd.databricks.v1+notebook": { - "notebookName": "quickstart", "dashboards": [], + "language": "python", "notebookMetadata": { "pythonIndentUnit": 2 }, - "language": "python", - "widgets": {}, - "notebookOrigID": 1935524762305611 + "notebookName": "quickstart", + "notebookOrigID": 2666786534675592, + "widgets": {} } }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/docs/source/usage/usage.rst b/docs/source/usage/usage.rst index d7c8c3e10..79dd1ea04 100644 --- a/docs/source/usage/usage.rst +++ b/docs/source/usage/usage.rst @@ -5,7 +5,6 @@ Usage :maxdepth: 2 installation - install-gdal grid-indexes grid-indexes-bng quickstart diff --git a/notebooks/examples/R/QuickstartNotebook.r b/notebooks/examples/R/QuickstartNotebook.r index 2bbadec2d..41aa14798 100644 --- a/notebooks/examples/R/QuickstartNotebook.r +++ b/notebooks/examples/R/QuickstartNotebook.r @@ -24,14 +24,18 @@ print(paste0("The raw data is stored in ", raw_path)) # COMMAND ---------- -dbutils.fs.ls('dbfs:/databricks/mosaic/sparkrMosaic_0.3.4.tar.gz') - +mosaic_lib <- dbutils.fs.ls('dbfs:/databricks/mosaic/sparkrMosaic_0.3.4.tar.gz') +lib_path <- sapply(mosaic_lib, function(obj) obj$path) +lib_path <- lapply(lib_path, function(path) gsub('dbfs:/ml', '/dbfs/ml', path)) +lib_path + # COMMAND ---------- library(tidyverse) library(SparkR) -sparkr_mosaic_package_path = '/dbfs/databricks/mosaic/sparkrMosaic_0.3.4.tar.gz' +sparkr_mosaic_package_path = '/dbfs/databricks/mosaic/sparkrMosaic_0.3.4.tar.gz' # extract from above cell +# sparkr_mosaic_package_path = lib_path install.packages(sparkr_mosaic_package_path, repos=NULL) library(sparkrMosaic) sparkrMosaic::enableMosaic() diff --git a/notebooks/examples/python/Mosaic + Sedona Raster 1.2.x Example.py b/notebooks/examples/python/Mosaic + Sedona Raster 1.2.x Example.py index cd695ec01..11dbafbaa 100644 --- a/notebooks/examples/python/Mosaic + Sedona Raster 1.2.x Example.py +++ b/notebooks/examples/python/Mosaic + Sedona Raster 1.2.x Example.py @@ -1,6 +1,6 @@ # Databricks notebook source # MAGIC %md # Mosaic + Apache Sedona Raster 1.2.x Example -# MAGIC +# MAGIC # MAGIC * Assumes DBR 10.4 which is Spark 3.2.1 # COMMAND ---------- @@ -52,11 +52,13 @@ # COMMAND ---------- # MAGIC %md _For DBR, install python bindings_ -# MAGIC +# MAGIC # MAGIC > Instead of `%pip install apache-sedona==1.2.0` using WHL built from Sedona master (1.2.1) # COMMAND ---------- +# MAGIC %md +# MAGIC # MAGIC %pip install /dbfs/FileStore/jars/sedona/1.2.1-incubating/apache_sedona-1.2.1-py3-none-any.whl # COMMAND ---------- @@ -128,9 +130,9 @@ # MAGIC %md # MAGIC # Geotiff Loader -# MAGIC +# MAGIC # MAGIC > __Note: if using 1.2.0 JAR (Maven) the spec uses `wkt` instead of `geometry` as name of column (1.2.1 JAR from Master uses `geometry`)__ -# MAGIC +# MAGIC # MAGIC 1. Loader takes as input a path to directory which contains geotiff files or a parth to particular geotiff file # MAGIC 2. Loader will read geotiff image in a struct named image which contains multiple fields as shown in the schema below which can be extracted using spark SQL @@ -378,7 +380,7 @@ # MAGIC %md # MAGIC ## Visualising Geotiff Images -# MAGIC +# MAGIC # MAGIC 1. Normalize the bands in range [0-255] if values are greater than 255 # MAGIC 2. Process image using RS_Base64() which converts in into a base64 string # MAGIC 3. Embedd results of RS_Base64() in RS_HTML() to embedd into IPython notebook @@ -611,7 +613,7 @@ # COMMAND ---------- # MAGIC %md -# MAGIC +# MAGIC # MAGIC > Get the normalized difference index between the extracted bands # COMMAND ---------- @@ -650,9 +652,9 @@ # COMMAND ---------- # MAGIC %md _Could write GeoTiff DataFrame as GeoTiff image similar as before_ -# MAGIC +# MAGIC # MAGIC Example -# MAGIC +# MAGIC # MAGIC ``` # MAGIC ( # MAGIC df_append.coalesce(1) @@ -673,7 +675,7 @@ # COMMAND ---------- # MAGIC %md -# MAGIC +# MAGIC # MAGIC > Sample UDF calculates sum of all the values in a band which are greater than 1000.0 # COMMAND ----------