Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

fix(SelectiveMerge): Do not override non-existing entries #396

Open
wants to merge 3 commits into
base: master
Choose a base branch
from
Open

fix(SelectiveMerge): Do not override non-existing entries #396

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
315aa9f
fix(SelectiveMerge): Do not override non-existing entries
Doe-Ed Nov 26, 2020
3e88ee0
Merge branch 'master' into selective-merge-improve-v6
amirhalatzi May 26, 2021
920a72a
Merge branch 'master' into selective-merge-improve-v6
amirhalatzi May 26, 2021
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
41 changes: 36 additions & 5 deletions src/main/scala/com/yotpo/metorikku/code/steps/SelectiveMerge.scala
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -3,9 +3,11 @@ package com.yotpo.metorikku.code.steps
import com.yotpo.metorikku.exceptions.MetorikkuException
import org.apache.log4j.{LogManager, Logger}
import org.apache.spark.sql.catalyst.expressions.NamedExpression
import org.apache.spark.sql.{Column, DataFrame}
import org.apache.spark.sql.{Column, DataFrame, Row}
import org.apache.spark.sql.functions._

import scala.collection.mutable.ListBuffer

object SelectiveMerge {
private val message = "You need to send 3 parameters with the names of the dataframes to merge and the key(s) to merge on" +
"(merged df1 into df2 favoring values from df2): df1, df2, Seq[String]"
Expand Down Expand Up @@ -58,8 +60,28 @@ object SelectiveMerge {
}

def merge(df1: DataFrame, df2: DataFrame, joinKeys: Seq[String]): DataFrame = {
val mergedDf = outerJoinWithAliases(df1, df2, joinKeys)
overrideConflictingValues(df1, df2, mergedDf, joinKeys)
val df2NoStaleEntries = removeStaleEntries(df1, df2, joinKeys)
val mergedDf = outerJoinWithAliases(df1, df2NoStaleEntries, joinKeys)
overrideConflictingValues(df1, df2NoStaleEntries, mergedDf, joinKeys)
}

def removeStaleEntries(df1: DataFrame, df2: DataFrame, joinKeys: Seq[String]): DataFrame = {
var df2New = df2
for (key <- joinKeys) {
val diff = df2.select(col(key)).except(df1.select(col(key)))
var toRemoveBuff = new ListBuffer[Row]()

val localIter = diff.toLocalIterator()
while(localIter.hasNext) {
toRemoveBuff += localIter.next()
}

val toRemove = toRemoveBuff.toList.map(r => r.getAs[String](key))

df2New = df2New.filter(!df2New(key).isin(toRemove:_*))
}

df2New
}

def outerJoinWithAliases(df1: DataFrame, df2: DataFrame, joinKeys: Seq[String]): DataFrame = {
Expand Down Expand Up @@ -91,6 +113,8 @@ object SelectiveMerge {
}

def overrideConflictingValues(df1: DataFrame, df2: DataFrame, mergedDf: DataFrame, joinKeys: Seq[String]): DataFrame = {
val df1SchemaNames = df1.schema.map(f => f.name)

val mergedSchema = getMergedSchema(df1, df2, joinKeys)

mergedDf.select(
Expand All @@ -100,9 +124,16 @@ object SelectiveMerge {
val colNameArr = colName.split(colRenamePrefix)
val colNameOrig = if (colNameArr.size > 1) colNameArr(1) else colName

// Belongs to DF2, override.
// Column appears in DF2, override unless the row only belongs to DF1
if (colNameArr.size > 1) {
mergedDf(colName).alias(colNameOrig)
if (df1SchemaNames.contains(colNameOrig)) {
when(mergedDf(colName).isNotNull, mergedDf(colName).cast(df1.schema(colNameOrig).dataType))
.otherwise(df1(colNameOrig))
.alias(colNameOrig)
}
else {
mergedDf(colName).alias(colNameOrig)
}
}
// Is the join key(s)
else if (joinKeys.contains(colName)) {
Expand Down
73 changes: 28 additions & 45 deletions src/test/scala/com/yotpo/metorikku/code/steps/test/SelectiveMergeTests.scala
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -53,57 +53,46 @@ class SelectiveMergeTests extends FunSuite with BeforeAndAfterEach {
showString.invoke(df, 10.asInstanceOf[Object], 20.asInstanceOf[Object], false.asInstanceOf[Object]).asInstanceOf[String]
}

test("Selective merge") {
test("Equal number of columns") {
val sparkSession = SparkSession.builder.appName("test").getOrCreate()
val sqlContext= sparkSession.sqlContext
val sqlContext= new SQLContext(sparkSession.sparkContext)
import sqlContext.implicits._

val employeeData1 = Seq(
("James", 1, 11, 111, 1111),
("Maria", 2, 22, 222, 2222)
("James", 20, 10000),
("Maria", 30, 20000)
)
val df1 = employeeData1.toDF("employee_name", "salary", "age", "fake", "fake2")
val df1 = employeeData1.toDF("employee_name", "age", "salary")

val employeeData2 = Seq(
("James", 1, 33, 333),
("Jen", 4, 44, 444),
("Jeff", 5, 55, 555)
("James", 21, 1),
("Jen", 40, 2)
)
val df2 = employeeData2.toDF("employee_name", "salary", "age", "bonus")
val df2 = employeeData2.toDF("employee_name", "age", "new_formula")

val simpleDataExpectedAfterMerge = Seq(
("James", Integer.valueOf(1) /* Salary */, Integer.valueOf(33) /* age */, Integer.valueOf(111) /* fake */,
Integer.valueOf(1111) /* fake2 */, Integer.valueOf(333) /* bonus */),
("Maria", null.asInstanceOf[Integer] /* Salary */, null.asInstanceOf[Integer] /* age */, Integer.valueOf(222) /* fake */,
Integer.valueOf(2222) /* fake2 */, null.asInstanceOf[Integer] /* bonus */),
("Jen", Integer.valueOf(4) /* Salary */, Integer.valueOf(44) /* age */, null.asInstanceOf[Integer] /* fake */,
null.asInstanceOf[Integer] /* fake2 */, Integer.valueOf(444) /* bonus */),
("Jeff", Integer.valueOf(5) /* Salary */, Integer.valueOf(55) /* age */, null.asInstanceOf[Integer] /* fake */,
null.asInstanceOf[Integer] /* fake2 */, Integer.valueOf(555) /* bonus */)
("James", new Integer(21) /* age */, new Integer(10000) /* salary */, new Integer(1) /* new formula */),
("Maria", new Integer(30) /* age */, new Integer(20000) /* salary */, null.asInstanceOf[Integer] /* new_formula */)
)
val expectedDf = simpleDataExpectedAfterMerge.toDF("employee_name", "salary", "age", "fake", "fake2", "bonus")
val expectedDf = simpleDataExpectedAfterMerge.toDF("employee_name", "age", "salary", "new_formula")

val simpleDataNotExpectedAfterMerge = Seq(
("James", Integer.valueOf(10) /* Salary */, Integer.valueOf(33) /* age */, Integer.valueOf(111) /* fake */,
Integer.valueOf(1111) /* fake2 */, Integer.valueOf(333) /* bonus */),
("Maria", Integer.valueOf(20) /* Salary */, Integer.valueOf(22) /* age */, Integer.valueOf(222) /* fake */,
Integer.valueOf(2222) /* fake2 */, null.asInstanceOf[Integer] /* bonus */),
("Jen", Integer.valueOf(40) /* Salary */, Integer.valueOf(44) /* age */, null.asInstanceOf[Integer] /* fake */,
null.asInstanceOf[Integer] /* fake2 */, Integer.valueOf(444) /* bonus */),
("Jeff", Integer.valueOf(50) /* Salary */, Integer.valueOf(55) /* age */, null.asInstanceOf[Integer] /* fake */,
null.asInstanceOf[Integer] /* fake2 */, Integer.valueOf(555) /* bonus */)
("James", new Integer(10) /* age */, new Integer(33) /* salary */, new Integer(111) /* new formula */),
("Maria", new Integer(20) /* age */, new Integer(22) /* salary */, new Integer(222) /* new formula */),
("Jen", new Integer(40) /* age */, new Integer(44) /* salary */, null.asInstanceOf[Integer] /* new formula */),
("Jeff", new Integer(50) /* age */, new Integer(55) /* salary */, null.asInstanceOf[Integer] /* new formula */)
)
val notExpectedDf = simpleDataNotExpectedAfterMerge.toDF("employee_name", "salary", "age", "fake", "fake2", "bonus")
val notExpectedDf = simpleDataNotExpectedAfterMerge.toDF("employee_name", "age", "salary", "new_formula")

val mergedDf = merge(df1, df2, Seq("employee_name"))

assertSuccess(mergedDf, expectedDf, isEqual = true)
assertSuccess(mergedDf, notExpectedDf, isEqual = false)
}

test("String and numbers mixed fields") {
test("Df2 has more columns") {
val sparkSession = SparkSession.builder.appName("test").getOrCreate()
val sqlContext= sparkSession.sqlContext
val sqlContext= new SQLContext(sparkSession.sparkContext)
import sqlContext.implicits._

val employeeData1 = Seq(
Expand All @@ -120,14 +109,10 @@ class SelectiveMergeTests extends FunSuite with BeforeAndAfterEach {
val df2 = employeeData2.toDF("employee_name", "salary", "age", "bonus")

val simpleDataExpectedAfterMerge = Seq(
("James", "Sharon" /* Last Name */, Integer.valueOf(1) /* Salary */, Integer.valueOf(33) /* age */,
Integer.valueOf(111) /* fake */, Integer.valueOf(1111) /* fake2 */, Integer.valueOf(333) /* bonus */),
("Maria", "Bob" /* Last Name */, null.asInstanceOf[Integer] /* Salary */, null.asInstanceOf[Integer] /* age */,
Integer.valueOf(222) /* fake */, Integer.valueOf(2222) /* fake2 */, null.asInstanceOf[Integer] /* bonus */),
("Jen", null.asInstanceOf[String] /* Last Name */, Integer.valueOf(4) /* Salary */, Integer.valueOf(44) /* age */,
null.asInstanceOf[Integer] /* fake */, null.asInstanceOf[Integer] /* fake2 */, Integer.valueOf(444) /* bonus */),
("Jeff", null.asInstanceOf[String] /* Last Name */, Integer.valueOf(5) /* Salary */, Integer.valueOf(55) /* age */,
null.asInstanceOf[Integer] /* fake */, null.asInstanceOf[Integer] /* fake2 */, Integer.valueOf(555) /* bonus */)
("James", "Sharon" /* Last Name */, new Integer(1) /* Salary */, new Integer(33) /* age */,
new Integer(111) /* fake */, new Integer(1111) /* fake2 */, new Integer(333) /* bonus */),
("Maria", "Bob" /* Last Name */, null.asInstanceOf[Integer] /* Salary */, new Integer(22) /* age */,
new Integer(222) /* fake */, new Integer(2222) /* fake2 */, null.asInstanceOf[Integer] /* bonus */)
)
val expectedDf = simpleDataExpectedAfterMerge.toDF("employee_name", "last_name", "salary", "age", "fake", "fake2", "bonus")

Expand All @@ -136,9 +121,9 @@ class SelectiveMergeTests extends FunSuite with BeforeAndAfterEach {
assertSuccess(mergedDf, expectedDf, isEqual = true)
}

test("df2 has more columns") {
test("df1 has more columns") {
val sparkSession = SparkSession.builder.appName("test").getOrCreate()
val sqlContext= sparkSession.sqlContext
val sqlContext= new SQLContext(sparkSession.sparkContext)
import sqlContext.implicits._

val employeeData1 = Seq(
Expand All @@ -155,13 +140,11 @@ class SelectiveMergeTests extends FunSuite with BeforeAndAfterEach {
val df2 = employeeData2.toDF("employee_name", "salary", "age", "bonus", "fake")

val simpleDataExpectedAfterMerge = Seq(
("James", Integer.valueOf(10) /* Salary */, Integer.valueOf(33) /* age */,
Integer.valueOf(333) /* Bonus */, Integer.valueOf(3333) /* fake */),
("Maria", null.asInstanceOf[Integer] /* Salary */, null.asInstanceOf[Integer] /* age */,
("James", new Integer(10) /* Salary */, new Integer(33) /* age */,
new Integer(333) /* Bonus */, new Integer(3333) /* fake */),
("Maria", new Integer(2) /* Salary */, new Integer(22) /* age */,
null.asInstanceOf[Integer] /* Bonus */, null.asInstanceOf[Integer] /* fake */),
("Jen", Integer.valueOf(4) /* Salary */, Integer.valueOf(44) /* age */,
Integer.valueOf(444) /* Bonus */, Integer.valueOf(4444) /* fake */),
("Albert", null.asInstanceOf[Integer] /* Salary */, null.asInstanceOf[Integer] /* age */,
("Albert", new Integer(3) /* Salary */, new Integer(33) /* age */,
null.asInstanceOf[Integer] /* Bonus */, null.asInstanceOf[Integer] /* fake */)
)
val expectedDf = simpleDataExpectedAfterMerge.toDF("employee_name", "salary", "age", "bonus", "fake")
Expand Down