[jira] [Commented] (SPARK-35252) PartitionReaderFactory's Implemention Class of DataSourceV2: sqlConf parameter is null

["Hyukjin Kwon (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-35252?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17338302#comment-17338302 ] 

Hyukjin Kwon commented on SPARK-35252:
--------------------------------------

You can use {{SQLConf.get}} instead.

> PartitionReaderFactory's Implemention Class of DataSourceV2: sqlConf parameter is null
> --------------------------------------------------------------------------------------
>
>                 Key: SPARK-35252
>                 URL: https://issues.apache.org/jira/browse/SPARK-35252
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 3.0.2, 3.1.1
>            Reporter: lynn
>            Priority: Major
>         Attachments: spark-sqlconf-isnull.png
>
>
> The codes of "MyPartitionReaderFactory" :
> {code:scala}
> // Implemention Class
> package com.lynn.spark.sql.v2
> import org.apache.spark.internal.Logging
> import org.apache.spark.sql.catalyst.InternalRow
> import com.lynn.spark.sql.v2.MyPartitionReaderFactory.{MY_VECTORIZED_READER_BATCH_SIZE, MY_VECTORIZED_READER_ENABLED}
> import org.apache.spark.sql.connector.read.{InputPartition, PartitionReader, PartitionReaderFactory}
> import org.apache.spark.sql.internal.SQLConf
> import org.apache.spark.sql.types.StructType
> import org.apache.spark.sql.vectorized.ColumnarBatch
> import org.apache.spark.sql.internal.SQLConf.buildConf
> case class MyPartitionReaderFactory(sqlConf: SQLConf,
>                                     dataSchema: StructType,
>                                     readSchema: StructType)
>   extends PartitionReaderFactory with Logging {
>   val enableVectorized = sqlConf.getConf(MY_VECTORIZED_READER_ENABLED, false)
>   val batchSize = sqlConf.getConf(MY_VECTORIZED_READER_BATCH_SIZE, 4096)
>   override def createReader(partition: InputPartition): PartitionReader[InternalRow] = {
>     MyRowReader(batchSize, dataSchema, readSchema)
>   }
>   override def createColumnarReader(partition: InputPartition): PartitionReader[ColumnarBatch] = {
>     if(!supportColumnarReads(partition))
>       throw new UnsupportedOperationException("Cannot create columnar reader.")
>        MyColumnReader(batchSize, dataSchema, readSchema)
>   }
>   override def supportColumnarReads(partition: InputPartition) = enableVectorized
> }
> object MyPartitionReaderFactory {
>   val MY_VECTORIZED_READER_ENABLED =
>     buildConf("spark.sql.my.enableVectorizedReader")
>       .doc("Enables vectorized my source scan.")
>       .version("1.0.0")
>       .booleanConf
>       .createWithDefault(false)
>   val MY_VECTORIZED_READER_BATCH_SIZE =
>     buildConf("spark.sql.my.columnarReaderBatchSize")
>       .doc("The number of rows to include in a my source vectorized reader batch. The number should " +
>         "be carefully chosen to minimize overhead and avoid OOMs in reading data.")
>       .version("1.0.0")
>       .intConf
>       .createWithDefault(4096)
> }
> {code}
> The driver construct a RDD instance(DataSourceRDD), the sqlConf parameter pass to the MyPartitionReaderFactory  is not null.
> But when the executor deserialize the RDD, the sqlConf parameter is null.
> The codes as follows:
> {code:scala}
> // RunTask.scala
> override def runTask(context: TaskContext): U = {
>     // Deserialize the RDD and the func using the broadcast variables.
>     val threadMXBean = ManagementFactory.getThreadMXBean
>     val deserializeStartTimeNs = System.nanoTime()
>     val deserializeStartCpuTime = if (threadMXBean.isCurrentThreadCpuTimeSupported) {
>       threadMXBean.getCurrentThreadCpuTime
>     } else 0L
>     val ser = SparkEnv.get.closureSerializer.newInstance()
>    //  the rdd 
>     val (rdd, func) = ser.deserialize[(RDD[T], (TaskContext, Iterator[T]) => U)](
>       ByteBuffer.wrap(taskBinary.value), Thread.currentThread.getContextClassLoader)
>     _executorDeserializeTimeNs = System.nanoTime() - deserializeStartTimeNs
>     _executorDeserializeCpuTime = if (threadMXBean.isCurrentThreadCpuTimeSupported) {
>       threadMXBean.getCurrentThreadCpuTime - deserializeStartCpuTime
>     } else 0L
>     func(context, rdd.iterator(partition, context))
>   }
> {code}



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