Unable to download large data sets using JDBC/ODBC and Apache Thrift software framework in HDInsight

This article describes troubleshooting steps and possible resolutions for issues when using Apache Spark components in Azure HDInsight clusters.


When trying to download large data sets using JDBC/ODBC and the Apache Thrift software framework in Azure HDInsight, you receive an error message similar as follows:

org.apache.spark.SparkException: Kryo serialization failed:
Buffer overflow. Available: 0, required: 36518. To avoid this, increase spark.kryoserializer.buffer.max value.


This exception is caused by the serialization process trying to use more buffer space than is allowed. In Spark 2.0.0, the class org.apache.spark.serializer.KryoSerializer is used for serializing objects when data is accessed through the Apache Thrift software framework. A different class is used for data that will be sent over the network or cached in serialized form.


Increase the Kryoserializer buffer value. Add a key named spark.kryoserializer.buffer.max and set it to 2047 in spark2 config under Custom spark2-thrift-sparkconf. Restart all affected components.


The value for spark.kryoserializer.buffer.max must be less than 2048. Fractional values are not supported.

Next steps

If you didn't see your problem or are unable to solve your issue, visit one of the following channels for more support:

  • Get answers from Azure experts through Azure Community Support.

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