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[1105] Fix generated columns to work with CDF #1173

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[1105] Fix generated columns to work with CDF #1173

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15 changes: 15 additions & 0 deletions core/src/main/scala/org/apache/spark/sql/delta/ColumnWithDefaultExprUtils.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,7 @@ package org.apache.spark.sql.delta
import scala.collection.mutable

import org.apache.spark.sql.delta.actions.{Metadata, Protocol}
import org.apache.spark.sql.delta.commands.cdc.CDCReader
import org.apache.spark.sql.delta.constraints.{Constraint, Constraints}
import org.apache.spark.sql.delta.metering.DeltaLogging
import org.apache.spark.sql.delta.schema.SchemaUtils
Expand Down Expand Up @@ -113,6 +114,20 @@ object ColumnWithDefaultExprUtils extends DeltaLogging {
SchemaUtils.fieldToColumn(f).alias(f.name)
}
}
val cdcSelectExprs = CDCReader.CDC_COLUMNS_IN_DATA.flatMap { cdcColumnName =>
topLevelOutputNames.get(cdcColumnName).flatMap { cdcField =>
if (metadataOutputNames.contains(cdcColumnName)) {
// The column is in the table schema. It's not a CDC auto generated column. Skip it since
// it's already in `selectExprs`.
None
} else {
// The column is not in the table schema,
// so it must be a column generated by CDC. Adding it back as it's not in `selectExprs`.
Some(SchemaUtils.fieldToColumn(cdcField).alias(cdcField.name))
}
}
}
selectExprs = selectExprs ++ cdcSelectExprs
val newData = queryExecution match {
case incrementalExecution: IncrementalExecution =>
selectFromStreamingDataFrame(incrementalExecution, data, selectExprs: _*)
Expand Down
86 changes: 82 additions & 4 deletions core/src/test/scala/org/apache/spark/sql/delta/GeneratedColumnSuite.scala
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Expand Up @@ -19,6 +19,7 @@ package org.apache.spark.sql.delta
// scalastyle:off import.ordering.noEmptyLine
import java.io.PrintWriter

import org.apache.spark.sql.delta.commands.cdc.CDCReader
import org.apache.spark.sql.delta.schema.{InvariantViolationException, SchemaUtils}
import org.apache.spark.sql.delta.sources.DeltaSourceUtils.GENERATION_EXPRESSION_METADATA_KEY
import org.apache.spark.sql.delta.test.DeltaSQLCommandTest
Expand All @@ -30,6 +31,7 @@ import org.apache.spark.sql.catalyst.TableIdentifier
import org.apache.spark.sql.catalyst.util.DateTimeUtils.{getZoneId, stringToDate, stringToTimestamp, toJavaDate, toJavaTimestamp}
import org.apache.spark.sql.catalyst.util.quietly
import org.apache.spark.sql.execution.streaming.MemoryStream
import org.apache.spark.sql.functions.{current_timestamp, lit}
import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.streaming.{StreamingQueryException, Trigger}
import org.apache.spark.sql.test.SharedSparkSession
Expand Down Expand Up @@ -72,7 +74,8 @@ trait GeneratedColumnTest extends QueryTest with SharedSparkSession with DeltaSQ
generatedColumns: Map[String, String],
partitionColumns: Seq[String],
notNullColumns: Set[String],
comments: Map[String, String]): DeltaTableBuilder = {
comments: Map[String, String],
properties: Map[String, String]): DeltaTableBuilder = {
val schema = if (schemaString.nonEmpty) {
StructType.fromDDL(schemaString)
} else {
Expand Down Expand Up @@ -102,6 +105,9 @@ trait GeneratedColumnTest extends QueryTest with SharedSparkSession with DeltaSQ
if (path.nonEmpty) {
builder.location(path.get)
}
properties.foreach { case (key, value) =>
builder.property(key, value)
}
builder
}

Expand All @@ -112,10 +118,11 @@ trait GeneratedColumnTest extends QueryTest with SharedSparkSession with DeltaSQ
generatedColumns: Map[String, String],
partitionColumns: Seq[String],
notNullColumns: Set[String] = Set.empty,
comments: Map[String, String] = Map.empty): Unit = {
comments: Map[String, String] = Map.empty,
properties: Map[String, String] = Map.empty): Unit = {
var tableBuilder = io.delta.tables.DeltaTable.create(spark)
buildTable(tableBuilder, tableName, path, schemaString,
generatedColumns, partitionColumns, notNullColumns, comments)
generatedColumns, partitionColumns, notNullColumns, comments, properties)
.execute()
}
}
Expand All @@ -133,14 +140,15 @@ trait GeneratedColumnSuiteBase extends GeneratedColumnTest {
partitionColumns: Seq[String],
notNullColumns: Set[String] = Set.empty,
comments: Map[String, String] = Map.empty,
properties: Map[String, String] = Map.empty,
orCreate: Option[Boolean] = None): Unit = {
var tableBuilder = if (orCreate.getOrElse(false)) {
io.delta.tables.DeltaTable.createOrReplace(spark)
} else {
io.delta.tables.DeltaTable.replace(spark)
}
buildTable(tableBuilder, tableName, path, schemaString,
generatedColumns, partitionColumns, notNullColumns, comments).execute()
generatedColumns, partitionColumns, notNullColumns, comments, properties).execute()
}

// Define the information for a default test table used by many tests.
Expand Down Expand Up @@ -1594,6 +1602,76 @@ trait GeneratedColumnSuiteBase extends GeneratedColumnTest {
}
}
}

test("generated columns with cdf") {
val tableName1 = "gcEnabledCDCOn"
val tableName2 = "gcEnabledCDCOff"
withTable(tableName1, tableName2) {

createTable(
tableName1,
None,
schemaString = "id LONG, timeCol TIMESTAMP, dateCol DATE",
generatedColumns = Map(
"dateCol" -> "CAST(timeCol AS DATE)"
),
partitionColumns = Seq("dateCol"),
properties = Map(
"delta.enableChangeDataFeed" -> "true"
)
)

spark.range(100).repartition(10)
.withColumn("timeCol", current_timestamp())
.write
.format("delta")
.mode("append")
.saveAsTable(tableName1)

spark.sql(s"DELETE FROM ${tableName1} WHERE id < 3")

val changeData = spark.read.format("delta").option("readChangeData", "true")
.option("startingVersion", "2")
.table(tableName1)
.select("id", CDCReader.CDC_TYPE_COLUMN_NAME, CDCReader.CDC_COMMIT_VERSION)

val expected = spark.range(0, 3)
.withColumn(CDCReader.CDC_TYPE_COLUMN_NAME, lit("delete"))
.withColumn(CDCReader.CDC_COMMIT_VERSION, lit(2))
checkAnswer(changeData, expected)

// Now write out the data frame of cdc to another table that has generated columns but not
// cdc enabled.
createTable(
tableName2,
None,
schemaString = "id LONG, _change_type STRING, timeCol TIMESTAMP, dateCol DATE",
generatedColumns = Map(
"dateCol" -> "CAST(timeCol AS DATE)"
),
partitionColumns = Seq("dateCol"),
properties = Map(
"delta.enableChangeDataFeed" -> "false"
)
)

val cdcRead = spark.read.format("delta").option("readChangeData", "true")
.option("startingVersion", "2")
.table(tableName1)
.select("id", CDCReader.CDC_TYPE_COLUMN_NAME, "timeCol")

cdcRead
.write
.format("delta")
.mode("append")
.saveAsTable(tableName2)

checkAnswer(
cdcRead,
spark.table(tableName2).drop("dateCol")
)
}
}
}

class GeneratedColumnSuite extends GeneratedColumnSuiteBase
Expand Down