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for bigquery table spark jobs, add transient to unblock serialization issues and do not create table when attempting to insert #174

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Merged
merged 10 commits into from
Jan 8, 2025
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for bigquery table spark jobs, add transient to unblock serialization issues and do not create table when attempting to insert #174

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d9f0834
Add transient to TableFormatProvider because it contains BigQueryImpl…
david-zlai Jan 7, 2025
aac350a
more notes.
david-zlai Jan 7, 2025
d770011
add some tests
david-zlai Jan 7, 2025
e1137db
add some notes.
david-zlai Jan 7, 2025
fe164cf
Add altertable plus expand to createTable
david-zlai Jan 7, 2025
9a33536
commit coderabbit.
david-zlai Jan 7, 2025
945c635
fix
david-zlai Jan 7, 2025
7958562
format imports.
david-zlai Jan 7, 2025
fe28953
pr comments.
david-zlai Jan 8, 2025
3fd9e08
add a todo.
david-zlai Jan 8, 2025
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69 changes: 43 additions & 26 deletions spark/src/main/scala/ai/chronon/spark/TableUtils.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -88,7 +88,9 @@ class TableUtils(@transient val sparkSession: SparkSession) extends Serializable
private val blockingCacheEviction: Boolean =
sparkSession.conf.get("spark.chronon.table_write.cache.blocking", "false").toBoolean

private[spark] lazy val tableFormatProvider: FormatProvider = {
// Add transient here because it can contain BigQueryImpl during reflection with bq flavor
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@piyush-zlai piyush-zlai Jan 8, 2025

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maybe swap the 'BigqueryImpl' with the generic phrase - concrete format provider which might not be serializable? (As this isn't restricted to BQ)

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@david-zlai david-zlai Jan 8, 2025

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removing

// and that can't be serialized by Spark
@transient private[spark] lazy val tableFormatProvider: FormatProvider = {
val clazzName =
sparkSession.conf.get("spark.chronon.table.format_provider.class", classOf[DefaultFormatProvider].getName)
val mirror = runtimeMirror(getClass.getClassLoader)
Expand Down Expand Up @@ -261,6 +263,35 @@ class TableUtils(@transient val sparkSession: SparkSession) extends Serializable
def firstAvailablePartition(tableName: String, subPartitionFilters: Map[String, String] = Map.empty): Option[String] =
partitions(tableName, subPartitionFilters).reduceOption((x, y) => Ordering[String].min(x, y))

def createTable(df: DataFrame,
tableName: String,
partitionColumns: Seq[String] = Seq.empty,
writeFormatTypeString: String = "",
tableProperties: Map[String, String] = null,
fileFormat: String = "PARQUET",
autoExpand: Boolean = false): Unit = {
// create table sql doesn't work for bigquery here. instead of creating the table explicitly, we can rely on the
// bq connector to indirectly create the table and eventually write the data
if (!tableExists(tableName) && writeFormatTypeString.toUpperCase != "BIGQUERY") {
val creationSql = createTableSql(tableName, df.schema, partitionColumns, tableProperties, fileFormat)
try {
sql(creationSql)
} catch {
case _: TableAlreadyExistsException =>
logger.info(s"Table $tableName already exists, skipping creation")
case e: Exception =>
logger.error(s"Failed to create table $tableName", e)
throw e
}
}
if (tableProperties != null && tableProperties.nonEmpty) {
sql(alterTablePropertiesSql(tableName, tableProperties))
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@tchow-zlai tchow-zlai Jan 8, 2025

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I think we actually want to persist some of these table properties though. The behavior here isn't quite equivalent for bigquery in that any custom properties we pass through here ultimately don't make it to the bigquery table. That might be problematic down the line.

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@tchow-zlai tchow-zlai Jan 8, 2025

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@david-zlai mind just adding a TODO here so we can take care of it for BigQuery?

}
if (autoExpand) {
expandTable(tableName, df.schema)
}
}

// Needs provider
def insertPartitions(df: DataFrame,
tableName: String,
Expand All @@ -279,25 +310,15 @@ class TableUtils(@transient val sparkSession: SparkSession) extends Serializable
df
}

if (!tableExists(tableName)) {
val creationSql = createTableSql(tableName, dfRearranged.schema, partitionColumns, tableProperties, fileFormat)
try {
sql(creationSql)
} catch {
case _: TableAlreadyExistsException =>
logger.info(s"Table $tableName already exists, skipping creation")
case e: Exception =>
logger.error(s"Failed to create table $tableName", e)
throw e
}
}
if (tableProperties != null && tableProperties.nonEmpty) {
sql(alterTablePropertiesSql(tableName, tableProperties))
}
val writeFormatTypeString = tableFormatProvider.writeFormat(tableName).createTableTypeString

if (autoExpand) {
expandTable(tableName, dfRearranged.schema)
}
createTable(dfRearranged,
tableName,
partitionColumns,
writeFormatTypeString,
tableProperties,
fileFormat,
autoExpand)

val finalizedDf = if (autoExpand) {
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@tchow-zlai tchow-zlai Jan 7, 2025

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the chain of logic here doesn't match the original then - in this if branch we are trying to retrieve the schema from the table, but it's possible it doesn't yet exist, since autoExpand may be set true for a BigQuery table. getSchemaFromTable will probably throw an exception if the table doesn't exist. So we probably need to pull this df logic into createTable as well.

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@david-zlai david-zlai Jan 7, 2025

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great catch

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@david-zlai david-zlai Jan 7, 2025

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weird this piece of code is only in insertPartitions but not at all in insertUnPartitioned 🙃

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@david-zlai david-zlai Jan 7, 2025

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oh...insertUnpartitioned doesn't even have autoExpand in it

// reselect the columns so that an deprecated columns will be selected as NULL before write
Expand Down Expand Up @@ -362,13 +383,9 @@ class TableUtils(@transient val sparkSession: SparkSession) extends Serializable
saveMode: SaveMode = SaveMode.Overwrite,
fileFormat: String = "PARQUET"): Unit = {

if (!tableExists(tableName)) {
sql(createTableSql(tableName, df.schema, Seq.empty[String], tableProperties, fileFormat))
} else {
if (tableProperties != null && tableProperties.nonEmpty) {
sql(alterTablePropertiesSql(tableName, tableProperties))
}
}
val writeFormatTypeString = tableFormatProvider.writeFormat(tableName).createTableTypeString

createTable(df, tableName, Seq.empty[String], writeFormatTypeString, tableProperties, fileFormat)

repartitionAndWrite(df, tableName, saveMode, None)
}
Expand Down
51 changes: 49 additions & 2 deletions spark/src/test/scala/ai/chronon/spark/test/TableUtilsTest.scala
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Expand Up @@ -31,8 +31,7 @@ import org.apache.spark.sql.Row
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.functions.col
import org.apache.spark.sql.types
import org.junit.Assert.assertEquals
import org.junit.Assert.assertTrue
import org.junit.Assert.{assertEquals, assertFalse, assertTrue}
import org.junit.Test

import scala.util.Try
Expand Down Expand Up @@ -431,4 +430,52 @@ class TableUtilsTest {
tableUtils.sql("CREATE TEMPORARY FUNCTION test AS 'ai.chronon.spark.test.SimpleAddUDF'")
}

@Test
def testCreateTable(): Unit = {
val tableName = "db.test_create_table"
spark.sql("CREATE DATABASE IF NOT EXISTS db")

val columns = Array(
StructField("long_field", LongType),
StructField("int_field", IntType),
StructField("string_field", StringType)
)
val df = makeDf(
spark,
StructType(
tableName,
columns
),
List(
Row(1L, 2, "3")
)
)
tableUtils.createTable(df, tableName)
assertTrue(spark.catalog.tableExists(tableName))
}
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@coderabbitai coderabbitai bot Jan 7, 2025

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🛠️ Refactor suggestion

Add table cleanup and data verification.

The test should:

  1. Clean up the table after the test
  2. Verify the schema and data, not just table existence
 @Test
 def testCreateTable(): Unit = {
   val tableName = "db.test_create_table"
   spark.sql("CREATE DATABASE IF NOT EXISTS db")
+  try {
     val columns = Array(
       StructField("long_field", LongType),
       StructField("int_field", IntType),
       StructField("string_field", StringType)
     )
     val df = makeDf(
       spark,
       StructType(
         tableName,
         columns
       ),
       List(
         Row(1L, 2, "3")
       )
     )
     tableUtils.createTable(df, tableName)
     assertTrue(spark.catalog.tableExists(tableName))
+    val createdTable = spark.table(tableName)
+    assertEquals(df.schema, createdTable.schema)
+    assertEquals(df.collect().toSeq, createdTable.collect().toSeq)
+  } finally {
+    spark.sql(s"DROP TABLE IF EXISTS $tableName")
+  }
 }
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Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change
@Test
def testCreateTable(): Unit = {
val tableName = "db.test_create_table"
spark.sql("CREATE DATABASE IF NOT EXISTS db")
val columns = Array(
StructField("long_field", LongType),
StructField("int_field", IntType),
StructField("string_field", StringType)
)
val df = makeDf(
spark,
StructType(
tableName,
columns
),
List(
Row(1L, 2, "3")
)
)
tableUtils.createTable(df, tableName)
assertTrue(spark.catalog.tableExists(tableName))
}
@Test
def testCreateTable(): Unit = {
val tableName = "db.test_create_table"
spark.sql("CREATE DATABASE IF NOT EXISTS db")
try {
val columns = Array(
StructField("long_field", LongType),
StructField("int_field", IntType),
StructField("string_field", StringType)
)
val df = makeDf(
spark,
StructType(
tableName,
columns
),
List(
Row(1L, 2, "3")
)
)
tableUtils.createTable(df, tableName)
assertTrue(spark.catalog.tableExists(tableName))
val createdTable = spark.table(tableName)
assertEquals(df.schema, createdTable.schema)
assertEquals(df.collect().toSeq, createdTable.collect().toSeq)
} finally {
spark.sql(s"DROP TABLE IF EXISTS $tableName")
}
}


@Test
def testCreateTableBigQuery(): Unit = {
val tableName = "db.test_create_table_bigquery"
spark.sql("CREATE DATABASE IF NOT EXISTS db")

val columns = Array(
StructField("long_field", LongType),
StructField("int_field", IntType),
StructField("string_field", StringType)
)
val df = makeDf(
spark,
StructType(
tableName,
columns
),
List(
Row(1L, 2, "3")
)
)
tableUtils.createTable(df, tableName, writeFormatTypeString = "BIGQUERY")
assertFalse(spark.catalog.tableExists(tableName))
}

}
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