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https://issues.apache.org/jira/browse/SPARK-26532?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-26532.
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Resolution: Not A Problem
> repartitionByRange reads source files twice
> -------------------------------------------
>
> Key: SPARK-26532
> URL: https://issues.apache.org/jira/browse/SPARK-26532
> Project: Spark
> Issue Type: Bug
> Components: SQL, Structured Streaming
> Affects Versions: 2.3.2, 2.4.0
> Reporter: Mike Dias
> Priority: Minor
> Attachments: repartition Stages.png, repartitionByRange Stages.png
>
>
> When using repartitionByRange in Structured Stream API for reading then write
> files, it reads the source files twice.
> Example:
> {code:java}
> val ds = spark.readStream.
> format("text").
> option("path", "data/streaming").
> load
> val q = ds.
> repartitionByRange(10, $"value").
> writeStream.
> format("parquet").
> option("path", "/tmp/output").
> option("checkpointLocation", "/tmp/checkpoint").
> start()
> {code}
> This execution creates 3 stages: 2 for reading and 1 for writing, reading the
> source twice. It's easy to see it in a large dataset where the reading
> process time is doubled.
>
> {code:java}
> $ curl -s -XGET
> http://localhost:4040/api/v1/applications/<shell_app_id>/stages
> {code}
>
>
> This is very different from the repartition strategy, which creates 2 stages:
> 1 for reading and 1 for writing.
> {code:java}
> val ds = spark.readStream.
> format("text").
> option("path", "data/streaming").
> load
> val q = ds.
> repartition(10, $"value").
> writeStream.
> format("parquet").
> option("path", "/tmp/output").
> option("checkpointLocation", "/tmp/checkpoint").
> start(){code}
>
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