ES/Spark RDD Partitioning Strangeness

Elastic Stack Elasticsearch
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We're using the es-hadoop connector to dump data from an ES index to spark (w/ pyspark, newAPIHadoopRDD). The issue we're seeing is that the RDD that is returned is skewed in terms of partitions - it always returns 9 partitions, with only 3 of them being populated.

Is there any way to have newAPIHadoopRDD return more evenly distributed partitions from the ES data? I realize that I can repartition them after the fact, but the initial set of partitions is causing some performance headaches.

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Welcome, Ivan.
You can control the number of documents per partition by set es.input.max.docs.per.partition value.

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Thanks Wang! That sounds like exactly what I need. I'll give it a shot.

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I can confirm that es.input.max.docs.per.partition works well and solved my issue. Thanks again!

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