SPARKC-704 - spark 3.5.0 support

CHANGES.txt

@@ -1,3 +1,7 @@
+
+3.5.0
+ * Support for Apache Spark 3.5 (SPARKC-704)
+
 3.4.1
  * Scala 2.13 support (SPARKC-686)
 

README.md

@@ -19,7 +19,7 @@ Spark RDDs and Datasets/DataFrames to Cassandra tables, and execute arbitrary CQ
 in your Spark applications.
 
  - Compatible with Apache Cassandra version 2.1 or higher (see table below)
- - Compatible with Apache Spark 1.0 through 3.4 ([see table below](#version-compatibility))
+ - Compatible with Apache Spark 1.0 through 3.5 ([see table below](#version-compatibility))
  - Compatible with Scala 2.11, 2.12 and 2.13
  - Exposes Cassandra tables as Spark RDDs and Datasets/DataFrames
  - Maps table rows to CassandraRow objects or tuples
@@ -45,15 +45,17 @@ corresponds to the 1.6 release. The "master" branch will normally contain
 development for the next connector release in progress.
 
 Currently, the following branches are actively supported: 
-3.4.x ([master](https://github.com/datastax/spark-cassandra-connector/tree/master)),
+3.5.x ([master](https://github.com/datastax/spark-cassandra-connector/tree/master)),
+3.4.x ([b3.4](https://github.com/datastax/spark-cassandra-connector/tree/b3.4)),
 3.3.x ([b3.2](https://github.com/datastax/spark-cassandra-connector/tree/b3.3)),
 3.2.x ([b3.2](https://github.com/datastax/spark-cassandra-connector/tree/b3.2)),
 3.1.x ([b3.1](https://github.com/datastax/spark-cassandra-connector/tree/b3.1)),
 3.0.x ([b3.0](https://github.com/datastax/spark-cassandra-connector/tree/b3.0)) and 
 2.5.x ([b2.5](https://github.com/datastax/spark-cassandra-connector/tree/b2.5)).
 
 | Connector | Spark         | Cassandra             | Cassandra Java Driver | Minimum Java Version | Supported Scala Versions |
-|-----------|---------------|-----------------------| --------------------- | -------------------- |--------------------------|
+|-----------|---------------|-----------------------| --------------------- | -------------------- | -----------------------  |
+| 3.5       | 3.5           | 2.1.5*, 2.2, 3.x, 4.x | 4.13             | 8              | 2.12, 2.13              |  
 | 3.4       | 3.4           | 2.1.5*, 2.2, 3.x, 4.x | 4.13             | 8             | 2.12, 2.13               |
 | 3.3       | 3.3           | 2.1.5*, 2.2, 3.x, 4.x | 4.13             | 8             | 2.12                     |
 | 3.2       | 3.2           | 2.1.5*, 2.2, 3.x, 4.0 | 4.13             | 8             | 2.12                     |
@@ -105,7 +107,7 @@ This project is available on the Maven Central Repository.
 For SBT to download the connector binaries, sources and javadoc, put this in your project
 SBT config:
 
-    libraryDependencies += "com.datastax.spark" %% "spark-cassandra-connector" % "3.4.1"
+    libraryDependencies += "com.datastax.spark" %% "spark-cassandra-connector" % "3.5.0"
 
 * The default Scala version for Spark 3.0+ is 2.12 please choose the appropriate build. See the
 [FAQ](doc/FAQ.md) for more information.

connector/src/it/scala/com/datastax/spark/connector/SparkCassandraITFlatSpecBase.scala

@@ -248,7 +248,7 @@ trait SparkCassandraITSpecBase
 
   def getCassandraScan(plan: SparkPlan): CassandraScan = {
     plan.collectLeaves.collectFirst{
-      case BatchScanExec(_, cassandraScan: CassandraScan, _, _, _, _, _, _, _) => cassandraScan
+      case BatchScanExec(_, cassandraScan: CassandraScan, _, _, _, _) => cassandraScan
     }.getOrElse(throw new IllegalArgumentException("No Cassandra Scan Found"))
   }
 

connector/src/it/scala/com/datastax/spark/connector/cql/sai/SaiBaseSpec.scala

@@ -47,7 +47,7 @@ trait SaiBaseSpec extends Matchers with SparkCassandraITSpecBase {
 
   def findCassandraScan(plan: SparkPlan): CassandraScan = {
     plan match {
-      case BatchScanExec(_, scan: CassandraScan, _, _, _, _, _, _, _) => scan
+      case BatchScanExec(_, scan: CassandraScan, _, _, _, _) => scan
       case filter: FilterExec => findCassandraScan(filter.child)
       case project: ProjectExec => findCassandraScan(project.child)
       case _ => throw new NoSuchElementException("RowDataSourceScanExec was not found in the given plan")

connector/src/it/scala/com/datastax/spark/connector/sql/CassandraDataSourceSpec.scala

@@ -274,10 +274,10 @@ class CassandraDataSourceSpec extends SparkCassandraITFlatSpecBase with DefaultC
     if (pushDown)
       withClue(s"Given Dataframe plan does not contain CassandraInJoin in its predecessors.\n${df.queryExecution.sparkPlan.toString()}") {
         df.queryExecution.executedPlan.collectLeaves().collectFirst{
-          case a@BatchScanExec(_, _: CassandraInJoin, _, _, _, _, _, _, _) => a
+          case a@BatchScanExec(_, _: CassandraInJoin, _, _, _, _) => a
           case b@AdaptiveSparkPlanExec(_, _, _, _, _) =>
             b.executedPlan.collectLeaves().collectFirst{
-              case a@BatchScanExec(_, _: CassandraInJoin, _, _, _, _, _, _, _) => a
+              case a@BatchScanExec(_, _: CassandraInJoin, _, _, _, _) => a
             }
         } shouldBe defined
      }
@@ -288,7 +288,7 @@ class CassandraDataSourceSpec extends SparkCassandraITFlatSpecBase with DefaultC
   private def assertOnAbsenceOfCassandraInJoin(df: DataFrame): Unit =
     withClue(s"Given Dataframe plan contains CassandraInJoin in its predecessors.\n${df.queryExecution.sparkPlan.toString()}") {
       df.queryExecution.executedPlan.collectLeaves().collectFirst{
-        case a@BatchScanExec(_, _: CassandraInJoin, _, _, _, _, _, _, _) => a
+        case a@BatchScanExec(_, _: CassandraInJoin, _, _, _, _) => a
       } shouldBe empty
     }
 

connector/src/it/scala/com/datastax/spark/connector/util/CatalystUtil.scala

@@ -7,6 +7,6 @@ import org.apache.spark.sql.execution.datasources.v2.BatchScanExec
 object CatalystUtil {
 
   def findCassandraScan(sparkPlan: SparkPlan): Option[CassandraScan] = {
-    sparkPlan.collectFirst{ case BatchScanExec(_, scan: CassandraScan, _, _, _, _, _, _, _) => scan}
+    sparkPlan.collectFirst{ case BatchScanExec(_, scan: CassandraScan, _, _, _, _) => scan}
   }
 }

connector/src/it/scala/org/apache/spark/sql/datastax/test/empty/EmptyStreamSource.scala

@@ -1,6 +1,7 @@
 package org.apache.spark.sql.datastax.test.empty
 
 import org.apache.spark.sql.catalyst.plans.logical.LocalRelation
+import org.apache.spark.sql.catalyst.types.DataTypeUtils
 import org.apache.spark.sql.execution.streaming.{LongOffset, Offset, Source}
 import org.apache.spark.sql.sources.StreamSourceProvider
 import org.apache.spark.sql.types.{IntegerType, StructField, StructType}
@@ -33,7 +34,7 @@ class DefaultSource extends StreamSourceProvider {
     }
 
     override def getBatch(start: Option[Offset], end: Offset): DataFrame = {
-      Dataset.ofRows(sqlContext.sparkSession, LocalRelation(schema.toAttributes, isStreaming = true))
+      Dataset.ofRows(sqlContext.sparkSession, LocalRelation(DataTypeUtils.toAttributes(schema), isStreaming = true))
     }
 
     override def stop() {}

connector/src/it/scala/org/apache/spark/sql/datastax/test/monotonic/FakeStreamSource.scala

@@ -1,6 +1,7 @@
 package org.apache.spark.sql.datastax.test.monotonic
 
 import org.apache.spark.sql.{DataFrame, Dataset, SQLContext}
+import org.apache.spark.sql.catalyst.types.DataTypeUtils
 import org.apache.spark.sql.catalyst.expressions.GenericInternalRow
 import org.apache.spark.sql.catalyst.plans.logical.LocalRelation
 import org.apache.spark.sql.execution.streaming.{LongOffset, Offset, SerializedOffset, Source}
@@ -43,7 +44,7 @@ class DefaultSource extends StreamSourceProvider {
         }
         val rows = (startValue.toInt to endValue.toInt).map( value =>
           new GenericInternalRow(values = Array(value)))
-        Dataset.ofRows(spark.sparkSession, LocalRelation(schema.toAttributes, rows, isStreaming = true))
+        Dataset.ofRows(spark.sparkSession, LocalRelation(DataTypeUtils.toAttributes(schema), rows, isStreaming = true))
       }
 
       override def stop() {}

connector/src/main/scala/com/datastax/spark/connector/datasource/CassandraWriteBuilder.scala

@@ -113,6 +113,8 @@ case class CassandraBulkWrite(
 
   override def createStreamingWriterFactory(info: PhysicalWriteInfo): StreamingDataWriterFactory = getWriterFactory()
 
+  override def useCommitCoordinator(): Boolean = super.useCommitCoordinator()
+
   private def getWriterFactory(): CassandraDriverDataWriterFactory = {
     CassandraDriverDataWriterFactory(
       connector,

connector/src/main/scala/com/datastax/spark/connector/package.scala

@@ -3,7 +3,7 @@ package com.datastax.spark
 import com.datastax.spark.connector.rdd.{CassandraTableScanRDD, SparkPartitionLimit}
 import org.apache.spark.SparkContext
 import org.apache.spark.rdd.RDD
-import org.apache.spark.sql.catalyst.encoders.RowEncoder
+import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder
 import org.apache.spark.sql.{DataFrame, Dataset, Encoder, Row}
 
 import scala.language.implicitConversions
@@ -65,7 +65,7 @@ package object connector {
     new CassandraTableScanRDDFunctions(rdd)
 
   implicit def toDataFrameFunctions(dataFrame: DataFrame): DatasetFunctions[Row] =
-    new DatasetFunctions[Row](dataFrame)(RowEncoder(dataFrame.schema))
+    new DatasetFunctions[Row](dataFrame)(ExpressionEncoder(dataFrame.schema))
 
   implicit def toDatasetFunctions[K: Encoder](dataset: Dataset[K]): DatasetFunctions[K] =
     new DatasetFunctions[K](dataset)

connector/src/main/scala/org/apache/spark/sql/cassandra/execution/CassandraDirectJoinStrategy.scala

@@ -147,7 +147,7 @@ object CassandraDirectJoinStrategy extends Logging {
     */
   def getScanExec(plan: SparkPlan): Option[BatchScanExec] = {
     plan.collectFirst {
-      case exec @ BatchScanExec(_, _: CassandraScan, _, _, _, _, _, _, _) => exec
+      case exec @ BatchScanExec(_, _: CassandraScan, _, _, _, _) => exec
     }
   }
 
@@ -205,7 +205,7 @@ object CassandraDirectJoinStrategy extends Logging {
   def hasCassandraChild[T <: QueryPlan[T]](plan: T): Boolean = {
     plan.children.size == 1 && plan.children.exists {
       case DataSourceV2ScanRelation(DataSourceV2Relation(_: CassandraTable, _, _, _, _), _, _, _, _) => true
-      case BatchScanExec(_, _: CassandraScan, _, _, _, _, _, _, _) => true
+      case BatchScanExec(_, _: CassandraScan, _, _, _, _) => true
       case _ => false
     }
   }
@@ -238,7 +238,7 @@ object CassandraDirectJoinStrategy extends Logging {
       originalOutput: Seq[Attribute]): SparkPlan = {
     val reordered = plan match {
       //This may be the only node in the Plan
-      case BatchScanExec(_, _: CassandraScan, _, _, _, _, _, _, _) => directJoin
+      case BatchScanExec(_, _: CassandraScan, _, _, _, _) => directJoin
       // Plan has children
       case normalPlan => normalPlan.transform {
         case penultimate if hasCassandraChild(penultimate) =>

doc/0_quick_start.md

@@ -15,15 +15,15 @@ Configure a new Scala project with the Apache Spark and dependency.
 
 The dependencies are easily retrieved via Maven Central 
 
-    libraryDependencies += "com.datastax.spark" % "spark-cassandra-connector_2.12" % "3.4.1"
+    libraryDependencies += "com.datastax.spark" % "spark-cassandra-connector_2.12" % "3.5.0"
 
 The spark-packages libraries can also be used with spark-submit and spark shell, these
 commands will place the connector and all of its dependencies on the path of the
 Spark Driver and all Spark Executors.
 
-    $SPARK_HOME/bin/spark-shell --packages com.datastax.spark:spark-cassandra-connector_2.12:3.4.1
-    $SPARK_HOME/bin/spark-submit --packages com.datastax.spark:spark-cassandra-connector_2.12:3.4.1
-   
+    $SPARK_HOME/bin/spark-shell --packages com.datastax.spark:spark-cassandra-connector_2.12:3.5.0
+    $SPARK_HOME/bin/spark-submit --packages com.datastax.spark:spark-cassandra-connector_2.12:3.5.0
+
 For the list of available versions, see:
 - https://repo1.maven.org/maven2/com/datastax/spark/spark-cassandra-connector_2.12/
 
@@ -42,7 +42,7 @@ and *all* of its dependencies on the Spark Class PathTo configure
 the default Spark Configuration pass key value pairs with `--conf`
 
     $SPARK_HOME/bin/spark-shell --conf spark.cassandra.connection.host=127.0.0.1 \
-                                --packages com.datastax.spark:spark-cassandra-connector_2.12:3.4.1
+                                --packages com.datastax.spark:spark-cassandra-connector_2.12:3.5.0
                                 --conf spark.sql.extensions=com.datastax.spark.connector.CassandraSparkExtensions
 
 This command would set the Spark Cassandra Connector parameter 

doc/13_spark_shell.md

@@ -18,7 +18,7 @@ Find additional versions at [Spark Packages](https://repo1.maven.org/maven2/com/
 ```bash
 cd spark/install/dir
 #Include the --master if you want to run against a spark cluster and not local mode
-./bin/spark-shell [--master sparkMasterAddress] --jars yourAssemblyJar --packages com.datastax.spark:spark-cassandra-connector_2.12:3.4.1 --conf spark.cassandra.connection.host=yourCassandraClusterIp
+./bin/spark-shell [--master sparkMasterAddress] --jars yourAssemblyJar --packages com.datastax.spark:spark-cassandra-connector_2.12:3.5.0 --conf spark.cassandra.connection.host=yourCassandraClusterIp
 ```
 
 By default spark will log everything to the console and this may be a bit of an overload. To change this copy and modify the `log4j.properties` template file

doc/15_python.md

@@ -14,7 +14,7 @@ shell similarly to how the spark shell is started. The preferred method is now t
 
 ```bash
 ./bin/pyspark \
-  --packages com.datastax.spark:spark-cassandra-connector_2.12:3.4.1 \
+  --packages com.datastax.spark:spark-cassandra-connector_2.12:3.5.0 \
   --conf spark.sql.extensions=com.datastax.spark.connector.CassandraSparkExtensions
 ```
 

project/Versions.scala

@@ -13,8 +13,8 @@ object Versions {
   val JUnitInterface  = "0.11"
   val Mockito         = "1.10.19"
 
-  val ApacheSpark     = "3.4.1"
-  val SparkJetty      = "9.4.50.v20221201"
+  val ApacheSpark     = "3.5.0"
+  val SparkJetty      = "9.4.51.v20230217"
   val SolrJ           = "8.3.0"
 
   val ScalaCompat         = "2.11.0"