[
https://issues.apache.org/jira/browse/SPARK-50570?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sakthi updated SPARK-50570:
---------------------------
Description:
Writing data to a DynamoDB table using PySpark results in the following error:
{code:java}
Caused by: java.lang.ClassCastException: org.apache.hadoop.io.MapWritable
cannot be cast to org.apache.hadoop.dynamodb.DynamoDBItemWritable
at
org.apache.hadoop.dynamodb.write.DefaultDynamoDBRecordWriter.convertValueToDynamoDBItem(DefaultDynamoDBRecordWriter.java:22){code}
However, when using the same logic written in Scala, the write operation works
as expected.
This indicates a potential issue in the PySpark logic responsible for
converting RDD elements before they are written to DynamoDB via
`DefaultDynamoDBRecordWriter`. This prevents users from leveraging PySpark for
integration with DynamoDb.
* Potential area of interest:
[https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/api/python/PythonHadoopUtil.scala#L183-L186]
*Broad steps to reproduce the issue:*
* Create a DynamoDB table with the required schema.
* Load some data into S3 to serve as the source data.
* Read from S3 and write to the DynamoDB table using PySpark.
** You should encounter the error mentioned above.
* Repeat the same steps using Scala.
** This time, the data will be successfully written to the DynamoDB table with
no errors encountered.
was:
Writing data to a DynamoDB table using PySpark results in the following error:
{code:java}
Caused by: java.lang.ClassCastException: org.apache.hadoop.io.MapWritable
cannot be cast to org.apache.hadoop.dynamodb.DynamoDBItemWritable
at
org.apache.hadoop.dynamodb.write.DefaultDynamoDBRecordWriter.convertValueToDynamoDBItem(DefaultDynamoDBRecordWriter.java:22){code}
However, when using the same logic written in Scala, the write operation works
as expected.
This indicates a potential issue in the PySpark logic responsible for
converting RDD elements before they are written to DynamoDB via
`DefaultDynamoDBRecordWriter`. This prevents users from leveraging PySpark for
integration with DynamoDb.
* Potential area of interest:
[https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/api/python/PythonHadoopUtil.scala#L183-L186]
*Broad steps to reproduce the issue:*
* Create a DynamoDB table with the required schema.
* Load some data into S3 to serve as the source data.
* Read from S3 and write to the DynamoDB table using PySpark.
** You should encounter the error mentioned above.
* Repeat the same steps using Scala.
** This time, the data will be successfully written to the DynamoDB table with
no errors encountered.
> ClassCastException in PySpark when writing to DynamoDB (MapWritable to
> DynamoDBItemWritable)
> --------------------------------------------------------------------------------------------
>
> Key: SPARK-50570
> URL: https://issues.apache.org/jira/browse/SPARK-50570
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 3.5.2
> Reporter: Sakthi
> Priority: Major
>
> Writing data to a DynamoDB table using PySpark results in the following error:
> {code:java}
> Caused by: java.lang.ClassCastException: org.apache.hadoop.io.MapWritable
> cannot be cast to org.apache.hadoop.dynamodb.DynamoDBItemWritable
> at
> org.apache.hadoop.dynamodb.write.DefaultDynamoDBRecordWriter.convertValueToDynamoDBItem(DefaultDynamoDBRecordWriter.java:22){code}
> However, when using the same logic written in Scala, the write operation
> works as expected.
> This indicates a potential issue in the PySpark logic responsible for
> converting RDD elements before they are written to DynamoDB via
> `DefaultDynamoDBRecordWriter`. This prevents users from leveraging PySpark
> for integration with DynamoDb.
> * Potential area of interest:
> [https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/api/python/PythonHadoopUtil.scala#L183-L186]
>
> *Broad steps to reproduce the issue:*
> * Create a DynamoDB table with the required schema.
> * Load some data into S3 to serve as the source data.
> * Read from S3 and write to the DynamoDB table using PySpark.
> ** You should encounter the error mentioned above.
> * Repeat the same steps using Scala.
> ** This time, the data will be successfully written to the DynamoDB table
> with no errors encountered.
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