Viz EC2 Services to Lambda - Part 2 - Rapid Onset Flooding Probability (

#558) This PR migrates the ensemble-based Rapid Onset Flooding Probability products from the Viz EC2 to the Viz Max Values lambda function (now called Python Preprocessing). It broadly encapsulates the following changes: **Changes** - New rapid_onset_flooding product script in the python_preprocessing lambda function that supports both 12 hour SRF and 5 day GFS MRF configurations. - Removal of rapid_onset_flooding pipeline and product files in the source-aws_loosa library **Deployment Considerations:** - Not sure if we should include this in the 2.1.4 release or not? I'm good to test/fix quickly and thoroughly next week if you want to include it. Otherwise, fine to go in the next one (wait to merge for now) - We will need to include a ingest schema db dump when deploying to UAT. --------- Co-authored-by: CoreyKrewson-NOAA <[email protected]>
NOAA-OWP · Dec 12, 2023 · 493f5f9 · 493f5f9
1 parent 578e439
commit 493f5f9
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diff --git a/Core/LAMBDA/layers/dask.zip b/Core/LAMBDA/layers/dask.zip
diff --git a/Core/LAMBDA/layers/main.tf b/Core/LAMBDA/layers/main.tf
@@ -269,6 +269,20 @@ resource "aws_lambda_layer_version" "yaml" {
   description         = "Python yaml module"
 }
 
+################
+## Dask Layer ##
+################
+
+resource "aws_lambda_layer_version" "dask" {
+  filename         = "${path.module}/dask.zip"
+  source_code_hash = filebase64sha256("${path.module}/dask.zip")
+
+  layer_name = "hv-vpp-${var.environment}-dask"
+
+  compatible_runtimes = ["python3.9"]
+  description         = "Python dask module"
+}
+
 #############
 ## Outputs ##
 #############
@@ -316,3 +330,7 @@ output "requests" {
 output "yaml" {
   value = resource.aws_lambda_layer_version.yaml
 }
+
+output "dask" {
+  value = resource.aws_lambda_layer_version.yaml
+}
diff --git a/Core/LAMBDA/layers/viz_lambda_shared_funcs/python/viz_lambda_shared_funcs.py b/Core/LAMBDA/layers/viz_lambda_shared_funcs/python/viz_lambda_shared_funcs.py
@@ -760,3 +760,10 @@ def gen_dict_extract(key, var):
                 for d in v:
                     for result in gen_dict_extract(key, d):
                         yield result
+
+def organize_input_files(fileset_bucket, fileset, download_subfolder):
+    local_files = []
+    for file in fileset:
+        download_path = check_if_file_exists(fileset_bucket, file, download=True, download_subfolder=download_subfolder)
+        local_files.append(download_path)
+    return local_files
diff --git a/Core/LAMBDA/viz_functions/main.tf b/Core/LAMBDA/viz_functions/main.tf
@@ -161,6 +161,10 @@ variable "yaml_layer" {
   type = string
 }
 
+variable "dask_layer" {
+  type = string
+}
+
 variable "viz_lambda_shared_funcs_layer" {
   type = string
 }
@@ -428,6 +432,7 @@ resource "aws_lambda_function" "viz_python_preprocessing" {
     var.psycopg2_sqlalchemy_layer,
     var.viz_lambda_shared_funcs_layer,
     var.requests_layer,
+    var.dask_layer,
   ]
 
   tags = {

diff --git a/...db_postprocess_sql/products/medium_range_mem1/mrf_gfs_5day_max_high_water_probability.sql b/...db_postprocess_sql/products/medium_range_mem1/mrf_gfs_5day_max_high_water_probability.sql
@@ -1,4 +1,4 @@
-DROP TABLE IF EXISTS publish.mrf_gfs_5day_max_high_water_probability;
+DROP TABLE IF EXISTS publish.mrf_gfs_5day_max_high_water_prob;
 SELECT
     channels.feature_id,
     channels.feature_id::TEXT AS feature_id_str,
@@ -16,6 +16,6 @@ SELECT
     hwp.high_water_threshold,
     to_char(now()::timestamp without time zone, 'YYYY-MM-DD HH24:MI:SS UTC') AS update_time,
     channels.geom
-INTO publish.mrf_gfs_5day_max_high_water_probability
-FROM ingest.mrf_gfs_5day_max_high_water_probability as hwp
+INTO publish.mrf_gfs_5day_max_high_water_prob
+FROM ingest.mrf_gfs_5day_max_high_water_prob as hwp
 JOIN derived.channels_conus channels ON hwp.feature_id = channels.feature_id;
diff --git a/...tprocess_sql/products/medium_range_mem1/mrf_gfs_5day_rapid_onset_flooding_probability.sql b/...tprocess_sql/products/medium_range_mem1/mrf_gfs_5day_rapid_onset_flooding_probability.sql
@@ -0,0 +1,23 @@
+DROP TABLE IF EXISTS publish.mrf_gfs_5day_rof_prob;
+SELECT
+    channels.feature_id,
+    channels.feature_id::TEXT AS feature_id_str,
+    channels.name,
+    channels.strm_order,
+    channels.huc6,
+    channels.state,
+	rofp.nwm_vers,
+	rofp.reference_time,
+    rofp.rapid_onset_prob_day1,
+    rofp.rapid_onset_prob_day2,
+    rofp.rapid_onset_prob_day3,
+    rofp.rapid_onset_prob_day4_5,
+    rofp.rapid_onset_prob_all,
+    rf.high_water_threshold,
+    ST_LENGTH(channels.geom)*0.000621371 AS reach_length_miles,
+    to_char(now()::timestamp without time zone, 'YYYY-MM-DD HH24:MI:SS UTC') AS update_time,
+    channels.geom
+INTO publish.mrf_gfs_5day_rof_prob
+FROM ingest.mrf_gfs_5day_rof_prob as rofp
+JOIN derived.channels_conus channels ON rofp.feature_id = channels.feature_id
+JOIN derived.recurrence_flows_conus rf ON rofp.feature_id = rf.feature_id;
diff --git a/...tions/viz_db_postprocess_sql/products/short_range/srf_12hr_max_high_water_probability.sql b/...tions/viz_db_postprocess_sql/products/short_range/srf_12hr_max_high_water_probability.sql
@@ -1,4 +1,4 @@
-DROP TABLE IF EXISTS publish.srf_12hr_max_high_water_probability;
+DROP TABLE IF EXISTS publish.srf_12hr_max_high_water_prob;
 SELECT
     channels.feature_id,
     channels.feature_id::TEXT AS feature_id_str,
@@ -12,6 +12,6 @@ SELECT
     hwp.high_water_threshold,
     to_char(now()::timestamp without time zone, 'YYYY-MM-DD HH24:MI:SS UTC') AS update_time,
     channels.geom
-INTO publish.srf_12hr_max_high_water_probability
-FROM ingest.srf_12hr_max_high_water_probability as hwp
+INTO publish.srf_12hr_max_high_water_prob
+FROM ingest.srf_12hr_max_high_water_prob as hwp
 JOIN derived.channels_conus channels ON hwp.feature_id = channels.feature_id;
diff --git a/...viz_db_postprocess_sql/products/short_range/srf_12hr_rapid_onset_flooding_probability.sql b/...viz_db_postprocess_sql/products/short_range/srf_12hr_rapid_onset_flooding_probability.sql
@@ -0,0 +1,21 @@
+DROP TABLE IF EXISTS publish.srf_12hr_rof_prob;
+SELECT
+    channels.feature_id,
+    channels.feature_id::TEXT AS feature_id_str,
+    channels.name,
+    channels.strm_order,
+    channels.huc6,
+    channels.state,
+	rofp.nwm_vers,
+	rofp.reference_time,
+    rofp.rapid_onset_prob_1_6,
+    rofp.rapid_onset_prob_7_12,
+    rofp.rapid_onset_prob_all,
+    rf.high_water_threshold,
+    ST_LENGTH(channels.geom)*0.000621371 AS reach_length_miles,
+    to_char(now()::timestamp without time zone, 'YYYY-MM-DD HH24:MI:SS UTC') AS update_time,
+    channels.geom
+INTO publish.srf_12hr_rof_prob
+FROM ingest.srf_12hr_rof_prob as rofp
+JOIN derived.channels_conus channels ON rofp.feature_id = channels.feature_id
+JOIN derived.recurrence_flows_conus rf ON rofp.feature_id = rf.feature_id;
diff --git a/...nctions/viz_db_postprocess_sql/summaries/mrf_gfs_5day_max_high_water_probability/hucs.sql b/...nctions/viz_db_postprocess_sql/summaries/mrf_gfs_5day_max_high_water_probability/hucs.sql
@@ -1,5 +1,5 @@
 -- HUC8 Hotpsot Layer
-DROP TABLE IF EXISTS publish.mrf_gfs_5day_max_high_water_probability_hucs;
+DROP TABLE IF EXISTS publish.mrf_gfs_5day_max_high_water_prob_hucs;
 SELECT
 	hucs.huc8,
 	TO_CHAR(hucs.huc8, 'fm00000000') AS huc8_str,
@@ -9,8 +9,8 @@ SELECT
 	to_char('1900-01-01 00:00:00'::timestamp without time zone, 'YYYY-MM-DD HH24:MI:SS UTC') AS reference_time,
 	to_char(now()::timestamp without time zone, 'YYYY-MM-DD HH24:MI:SS UTC') AS update_time,
 	hucs.geom
-INTO publish.mrf_gfs_5day_max_high_water_probability_hucs
+INTO publish.mrf_gfs_5day_max_high_water_prob_hucs
 FROM derived.huc8s_conus AS hucs
 JOIN derived.featureid_huc_crosswalk AS crosswalk ON hucs.huc8 = crosswalk.huc8
-JOIN publish.mrf_gfs_5day_max_high_water_probability AS hwp ON crosswalk.feature_id = hwp.feature_id
-GROUP BY hucs.huc8, total_nwm_features, hucs.geom
+JOIN publish.mrf_gfs_5day_max_high_water_prob AS hwp ON crosswalk.feature_id = hwp.feature_id
+GROUP BY hucs.huc8, hucs.total_nwm_features, hucs.geom;
diff --git a/...rapid_onset_flooding_probability_hucs.sql → ...rapid_onset_flooding_probability/hucs.sql b/...rapid_onset_flooding_probability_hucs.sql → ...rapid_onset_flooding_probability/hucs.sql
@@ -1,4 +1,4 @@
-DROP TABLE IF EXISTS publish.mrf_gfs_5day_rapid_onset_flooding_probability_hucs;
+DROP TABLE IF EXISTS publish.mrf_gfs_5day_rof_prob_hucs;
 SELECT
 	hucs.huc8,
 	TO_CHAR(hucs.huc8, 'fm00000000') AS huc8_str,
@@ -13,8 +13,8 @@ SELECT
 	to_char(CAST(max(rofp.reference_time) AS timestamp) , 'YYYY-MM-DD HH24:MI:SS UTC') AS reference_time,
 	to_char(now()::timestamp without time zone, 'YYYY-MM-DD HH24:MI:SS UTC') AS update_time,
 	hucs.geom
-INTO publish.mrf_gfs_5day_rapid_onset_flooding_probability_hucs
+INTO publish.mrf_gfs_5day_rof_prob_hucs
 FROM derived.huc8s_conus AS hucs
 JOIN derived.featureid_huc_crosswalk AS crosswalk ON hucs.huc8 = crosswalk.huc8
-JOIN publish.mrf_gfs_5day_rapid_onset_flooding_probability AS rofp ON crosswalk.feature_id = rofp.feature_id
+JOIN publish.mrf_gfs_5day_rof_prob AS rofp ON crosswalk.feature_id = rofp.feature_id
 GROUP BY hucs.huc8, hucs.low_order_reach_count, hucs.total_low_order_reach_length, hucs.total_low_order_reach_miles, hucs.geom
diff --git a/...z_functions/viz_db_postprocess_sql/summaries/srf_12hr_max_high_water_probability/hucs.sql b/...z_functions/viz_db_postprocess_sql/summaries/srf_12hr_max_high_water_probability/hucs.sql
@@ -1,5 +1,5 @@
 -- HUC10 Hotpsot Layer
-DROP TABLE IF EXISTS publish.srf_12hr_max_high_water_probability_hucs;
+DROP TABLE IF EXISTS publish.srf_12hr_max_high_water_prob_hucs;
 SELECT
 	hucs.huc10,
 	TO_CHAR(hucs.huc10, 'fm0000000000') AS huc10_str,
@@ -9,8 +9,8 @@ SELECT
 	to_char('1900-01-01 00:00:00'::timestamp without time zone, 'YYYY-MM-DD HH24:MI:SS UTC') AS reference_time,
 	to_char(now()::timestamp without time zone, 'YYYY-MM-DD HH24:MI:SS UTC') AS update_time,
 	hucs.geom
-INTO publish.srf_12hr_max_high_water_probability_hucs
+INTO publish.srf_12hr_max_high_water_prob_hucs
 FROM derived.huc10s_conus AS hucs
 JOIN derived.featureid_huc_crosswalk AS crosswalk ON hucs.huc10 = crosswalk.huc10
-JOIN publish.srf_12hr_max_high_water_probability AS hwp ON crosswalk.feature_id = hwp.feature_id
-GROUP BY hucs.huc10, total_nwm_features, hucs.geom
+JOIN publish.srf_12hr_max_high_water_prob AS hwp ON crosswalk.feature_id = hwp.feature_id
+GROUP BY hucs.huc10, hucs.total_nwm_features, hucs.geom;
diff --git a/...rapid_onset_flooding_probability_hucs.sql → ...rapid_onset_flooding_probability/hucs.sql b/...rapid_onset_flooding_probability_hucs.sql → ...rapid_onset_flooding_probability/hucs.sql
@@ -1,4 +1,4 @@
-DROP TABLE IF EXISTS publish.srf_12hr_rapid_onset_flooding_probability_hucs;
+DROP TABLE IF EXISTS publish.srf_12hr_rof_prob_hucs;
 SELECT
 	hucs.huc10,
 	TO_CHAR(hucs.huc10, 'fm0000000000') AS huc10_str,
@@ -13,8 +13,8 @@ SELECT
 	to_char(CAST(max(rofp.reference_time) AS timestamp) , 'YYYY-MM-DD HH24:MI:SS UTC') AS reference_time,
 	to_char(now()::timestamp without time zone, 'YYYY-MM-DD HH24:MI:SS UTC') AS update_time,
 	hucs.geom
-INTO publish.srf_12hr_rapid_onset_flooding_probability_hucs
+INTO publish.srf_12hr_rof_prob_hucs
 FROM derived.huc10s_conus AS hucs
 JOIN derived.featureid_huc_crosswalk AS crosswalk ON hucs.huc10 = crosswalk.huc10
-JOIN publish.srf_12hr_rapid_onset_flooding_probability AS rofp ON crosswalk.feature_id = rofp.feature_id
+JOIN publish.srf_12hr_rof_prob AS rofp ON crosswalk.feature_id = rofp.feature_id
 GROUP BY hucs.huc10, hucs.low_order_reach_count, hucs.total_low_order_reach_length, hucs.total_low_order_reach_miles, hucs.geom
diff --git a/Core/LAMBDA/viz_functions/viz_initialize_pipeline/lambda_function.py b/Core/LAMBDA/viz_functions/viz_initialize_pipeline/lambda_function.py
@@ -201,6 +201,7 @@ def __init__(self, start_event, print_init=True):
             self.organize_rename_dict() #This method organizes input table metadata based on the admin.pipeline_data_flows db table, and updates the sql_rename_dict dictionary if/when needed for past events.
             for word, replacement in self.sql_rename_dict.items():
                 self.configuration.configuration_data_flow = json.loads(json.dumps(self.configuration.configuration_data_flow).replace(word, replacement))
+                self.configuration.db_ingest_groups = json.loads(json.dumps(self.configuration.db_ingest_groups).replace(word, replacement))
                 self.pipeline_products = json.loads(json.dumps(self.pipeline_products).replace(word, replacement))      
             self.sql_rename_dict.update({'1900-01-01 00:00:00': self.reference_time.strftime("%Y-%m-%d %H:%M:%S")}) #Add a reference time for placeholders in sql files
 
@@ -464,7 +465,7 @@ def generate_ingest_groups_file_list(self, file_groups, data_origin="raw"):
             ingest_file = target_table_metadata["s3_keys"][0]
             if "rnr" in ingest_file:
                 bucket=os.environ['RNR_DATA_BUCKET']
-            elif "max" in ingest_file:
+            elif "viz_ingest" in ingest_file:
                 bucket=os.environ['PYTHON_PREPROCESSING_BUCKET']
             else:
                 bucket = self.input_bucket

diff --git a/...ze_pipeline/product_configs/medium_range_mem1/mrf_gfs_5day_max_high_water_probability.yml b/...ze_pipeline/product_configs/medium_range_mem1/mrf_gfs_5day_max_high_water_probability.yml
@@ -9,17 +9,17 @@ python_preprocessing:
     file_window: None
     product: high_water_probability
     output_file: viz_ingest/medium_range_mem1/{{datetime:%Y%m%d}}/{{datetime:%H}}_mrf_gfs_5day_max_high_water_probability.csv
-    target_table: ingest.mrf_gfs_5day_max_high_water_probability
+    target_table: ingest.mrf_gfs_5day_max_high_water_prob
     target_keys: (feature_id)
 
 postprocess_sql:
   - sql_file: mrf_gfs_5day_max_high_water_probability
-    target_table: publish.mrf_gfs_5day_max_high_water_probability
+    target_table: publish.mrf_gfs_5day_max_high_water_prob
 
 product_summaries:
   - sql_file:  hucs
     target_table:
-      - publish.mrf_gfs_5day_max_high_water_probability_hucs
+      - publish.mrf_gfs_5day_max_high_water_prob_hucs
 
 services:
   - mrf_gfs_5day_max_high_water_probability
diff --git a/...eline/product_configs/medium_range_mem1/mrf_gfs_5day_rapid_onset_flooding_probability.yml b/...eline/product_configs/medium_range_mem1/mrf_gfs_5day_rapid_onset_flooding_probability.yml
@@ -0,0 +1,25 @@
+product: mrf_gfs_5day_rapid_onset_flooding_probability
+configuration: medium_range_mem1
+product_type: "vector"
+run: true
+
+python_preprocessing:
+  - file_format: common/data/model/com/nwm/{{variable:NWM_DATAFLOW_VERSION}}/nwm.{{datetime:%Y%m%d}}/medium_range_mem{{range:1,7,1,%01d}}/nwm.t{{datetime:%H}}z.medium_range.channel_rt_{{range:1,7,1,%01d}}.f{{range:3,121,3,%03d}}.conus.nc
+    file_step: None
+    file_window: None
+    product: rapid_onset_flooding_probability
+    output_file: viz_ingest/medium_range_mem1/{{datetime:%Y%m%d}}/{{datetime:%H}}_mrf_gfs_5day_rapid_onset_flooding_probability.csv
+    target_table: ingest.mrf_gfs_5day_rof_prob
+    target_keys: (feature_id)
+
+postprocess_sql:
+  - sql_file: mrf_gfs_5day_rapid_onset_flooding_probability
+    target_table: publish.mrf_gfs_5day_rof_prob
+
+product_summaries:
+  - sql_file:  hucs
+    target_table:
+      - publish.mrf_gfs_5day_rof_prob_hucs
+
+services:
+  - mrf_gfs_5day_rapid_onset_flooding_probability
diff --git a/...z_initialize_pipeline/product_configs/short_range/srf_12hr_max_high_water_probability.yml b/...z_initialize_pipeline/product_configs/short_range/srf_12hr_max_high_water_probability.yml
@@ -9,17 +9,17 @@ python_preprocessing:
     file_window: PT7H
     product: high_water_probability
     output_file: viz_ingest/short_range/{{datetime:%Y%m%d}}/{{datetime:%H}}_srf_12hr_max_high_water_probability.csv
-    target_table: ingest.srf_12hr_max_high_water_probability
+    target_table: ingest.srf_12hr_max_high_water_prob
     target_keys: (feature_id)
 
 postprocess_sql:
   - sql_file: srf_12hr_max_high_water_probability
-    target_table: publish.srf_12hr_max_high_water_probability
+    target_table: publish.srf_12hr_max_high_water_prob
 
 product_summaries:
   - sql_file:  hucs
     target_table:
-      - publish.srf_12hr_max_high_water_probability_hucs
+      - publish.srf_12hr_max_high_water_prob_hucs
 
 services:
   - srf_12hr_max_high_water_probability
diff --git a/...ialize_pipeline/product_configs/short_range/srf_12hr_rapid_onset_flooding_probability.yml b/...ialize_pipeline/product_configs/short_range/srf_12hr_rapid_onset_flooding_probability.yml
@@ -0,0 +1,25 @@
+product: srf_12hr_rapid_onset_flooding_probability
+configuration: short_range
+product_type: "vector"
+run: true
+
+python_preprocessing:
+  - file_format: common/data/model/com/nwm/{{variable:NWM_DATAFLOW_VERSION}}/nwm.{{datetime:%Y%m%d}}/short_range/nwm.t{{datetime:%H}}z.short_range.channel_rt.f{{range:1,19,1,%03d}}.conus.nc
+    file_step: 1H
+    file_window: PT7H
+    product: rapid_onset_flooding_probability
+    output_file: viz_ingest/short_range/{{datetime:%Y%m%d}}/{{datetime:%H}}_srf_12hr_rapid_onset_flooding_probability.csv
+    target_table: ingest.srf_12hr_rof_prob
+    target_keys: (feature_id)
+
+postprocess_sql:
+  - sql_file: srf_12hr_rapid_onset_flooding_probability
+    target_table: publish.srf_12hr_rof_prob
+
+product_summaries:
+  - sql_file:  hucs
+    target_table:
+      - publish.srf_12hr_rof_prob_hucs
+
+services:
+  - srf_12hr_rapid_onset_flooding_probability
diff --git a/...z_publish_service/services/medium_range_mem1/mrf_gfs_5day_max_high_water_probability.mapx b/...z_publish_service/services/medium_range_mem1/mrf_gfs_5day_max_high_water_probability.mapx
@@ -413,7 +413,7 @@
           "workspaceFactory" : "SDE",
           "dataset" : "hydrovis.services.%Day 1 Bankfull Probability (%)_6",
           "datasetType" : "esriDTFeatureClass",
-          "sqlQuery" : "select strm_order,name,huc6,nwm_vers,geom,hours_3_to_24,high_water_threshold,reference_time,feature_id_str AS feature_id,update_time,oid from hydrovis.services.mrf_gfs_5day_max_high_water_probability",
+          "sqlQuery" : "select strm_order,name,huc6,nwm_vers,geom,hours_3_to_24,high_water_threshold,reference_time,feature_id_str AS feature_id,update_time,oid from hydrovis.services.mrf_gfs_5day_max_high_water_prob",
           "srid" : "3857",
           "spatialReference" : {
             "wkid" : 102100,
@@ -1174,7 +1174,7 @@
           "workspaceFactory" : "SDE",
           "dataset" : "hydrovis.services.%Day 1 Bankfull Probability (%)_1_5",
           "datasetType" : "esriDTFeatureClass",
-          "sqlQuery" : "select strm_order,name,huc6,nwm_vers,geom,hours_27_to_48,high_water_threshold,reference_time,feature_id_str AS feature_id,update_time,oid from hydrovis.services.mrf_gfs_5day_max_high_water_probability",
+          "sqlQuery" : "select strm_order,name,huc6,nwm_vers,geom,hours_27_to_48,high_water_threshold,reference_time,feature_id_str AS feature_id,update_time,oid from hydrovis.services.mrf_gfs_5day_max_high_water_prob",
           "srid" : "3857",
           "spatialReference" : {
             "wkid" : 102100,
@@ -1935,7 +1935,7 @@
           "workspaceFactory" : "SDE",
           "dataset" : "hydrovis.services.%Day 1 Bankfull Probability (%)_1_2_4",
           "datasetType" : "esriDTFeatureClass",
-          "sqlQuery" : "select strm_order,name,huc6,nwm_vers,geom,hours_51_to_72,high_water_threshold,reference_time,feature_id_str AS feature_id,update_time,oid from hydrovis.services.mrf_gfs_5day_max_high_water_probability",
+          "sqlQuery" : "select strm_order,name,huc6,nwm_vers,geom,hours_51_to_72,high_water_threshold,reference_time,feature_id_str AS feature_id,update_time,oid from hydrovis.services.mrf_gfs_5day_max_high_water_prob",
           "srid" : "3857",
           "spatialReference" : {
             "wkid" : 102100,
@@ -2696,7 +2696,7 @@
           "workspaceFactory" : "SDE",
           "dataset" : "hydrovis.services.%Day 1 Bankfull Probability (%)_1_2_3_3",
           "datasetType" : "esriDTFeatureClass",
-          "sqlQuery" : "select strm_order,name,huc6,nwm_vers,geom,hours_75_to_120, high_water_threshold,reference_time,feature_id_str AS feature_id,update_time,oid from hydrovis.services.mrf_gfs_5day_max_high_water_probability",
+          "sqlQuery" : "select strm_order,name,huc6,nwm_vers,geom,hours_75_to_120, high_water_threshold,reference_time,feature_id_str AS feature_id,update_time,oid from hydrovis.services.mrf_gfs_5day_max_high_water_prob",
           "srid" : "3857",
           "spatialReference" : {
             "wkid" : 102100,
@@ -3447,7 +3447,7 @@
           "workspaceFactory" : "SDE",
           "dataset" : "hydrovis.services.%Day 1 Bankfull Probability (%)_1_2_3_1_1_2",
           "datasetType" : "esriDTFeatureClass",
-          "sqlQuery" : "select strm_order,name,huc6,nwm_vers,geom,hours_3_to_120,high_water_threshold,reference_time,feature_id_str AS feature_id,update_time,oid from hydrovis.services.mrf_gfs_5day_max_high_water_probability",
+          "sqlQuery" : "select strm_order,name,huc6,nwm_vers,geom,hours_3_to_120,high_water_threshold,reference_time,feature_id_str AS feature_id,update_time,oid from hydrovis.services.mrf_gfs_5day_max_high_water_prob",
           "srid" : "3857",
           "spatialReference" : {
             "wkid" : 102100,
@@ -4182,7 +4182,7 @@
           "workspaceFactory" : "SDE",
           "dataset" : "hydrovis.hydrovis.%hucs",
           "datasetType" : "esriDTFeatureClass",
-          "sqlQuery" : "select huc8_str, total_nwm_features, nwm_features_flooded_percent, avg_prob, reference_time, update_time, geom, oid from hydrovis.services.mrf_gfs_5day_max_high_water_probability_hucs",
+          "sqlQuery" : "select huc8_str, total_nwm_features, nwm_features_flooded_percent, avg_prob, reference_time, update_time, geom, oid from hydrovis.services.mrf_gfs_5day_max_high_water_prob_hucs",
           "srid" : "3857",
           "spatialReference" : {
             "wkid" : 102100,