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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2018/07/27 00:31:00 UTC
[jira] [Commented] (SPARK-4502) Spark SQL reads unneccesary nested
fields from Parquet
[ https://issues.apache.org/jira/browse/SPARK-4502?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16559083#comment-16559083 ]
Apache Spark commented on SPARK-4502:
-------------------------------------
User 'ajacques' has created a pull request for this issue:
https://github.com/apache/spark/pull/21889
> Spark SQL reads unneccesary nested fields from Parquet
> ------------------------------------------------------
>
> Key: SPARK-4502
> URL: https://issues.apache.org/jira/browse/SPARK-4502
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 1.1.0
> Reporter: Liwen Sun
> Priority: Critical
>
> When reading a field of a nested column from Parquet, SparkSQL reads and assemble all the fields of that nested column. This is unnecessary, as Parquet supports fine-grained field reads out of a nested column. This may degrades the performance significantly when a nested column has many fields.
> For example, I loaded json tweets data into SparkSQL and ran the following query:
> {{SELECT User.contributors_enabled from Tweets;}}
> User is a nested structure that has 38 primitive fields (for Tweets schema, see: https://dev.twitter.com/overview/api/tweets), here is the log message:
> {{14/11/19 16:36:49 INFO InternalParquetRecordReader: Assembled and processed 385779 records from 38 columns in 3976 ms: 97.02691 rec/ms, 3687.0227 cell/ms}}
> For comparison, I also ran:
> {{SELECT User FROM Tweets;}}
> And here is the log message:
> {{14/11/19 16:45:40 INFO InternalParquetRecordReader: Assembled and processed 385779 records from 38 columns in 9461 ms: 40.77571 rec/ms, 1549.477 cell/ms}}
> So both queries load 38 columns from Parquet, while the first query only needs 1 column. I also measured the bytes read within Parquet. In these two cases, the same number of bytes (99365194 bytes) were read.
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