I am using Apache Spark 2.0.1 for processing the Grid HDFS Avro file, however I don't see spark distributing the job into different tasks instead it uses single task and all the operations (read, load, filter, show ) are done in a sequence using same task.
This means I am not able to leverage distributed parallel processing.
I tried the same operation on JSON file on HDFS, it works good, means the job gets distributed into multiple tasks and partition. I see parallelism.
I then tested the same on Spark 1.6, there it does the partitioning. Looks like there is a bug in Spark 2.* version. If not can some one help me know how to achieve the same on Avro file, do I need to do something special for Avro files ?
I explored spark setting: "spark.default.parallelism", "spark.sql.files.maxPartitionBytes", "--num-executors" and "spark.sql.shuffle.partitions". These were not of much help. "spark.default.parallelism", ensured to have multiple tasks however a single task ended up performing all the operation.
I am using com.databricks.spark.avro (3.0.1) for Spark 2.0.1.