[email protected] created SPARK-24974:
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Summary: Spark put all file's paths into SharedInMemoryCache even
for unused partitions.
Key: SPARK-24974
URL: https://issues.apache.org/jira/browse/SPARK-24974
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 2.2.1
Reporter: [email protected]
SharedInMemoryCache has all filestatus no matter whether you specify partition
columns or not. It causes long load time for queries that use only couple
partitions because Spark loads file's paths for files from all partitions.
I partitioned files by type and i has directory structure like
{code}
{{report_date=2018-07-24/type=A/file_1}}
{code}
I am trying to execute
{code}
{{val count = spark.read.parquet("/custom_path/report_date=2018-07-24").filter(
"type == 'A'").count}}
{code}
In my query i need to load only files of type A and it is just couple of files.
But spark load all 19K of files into SharedInMemoryCache which takes about 60
secs and only after that throws unused partitions.
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