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https://issues.apache.org/jira/browse/SPARK-21198?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16061899#comment-16061899
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Liang-Chi Hsieh commented on SPARK-21198:
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{{CatalogImpl.listTables}} actually returns the metadata for all tables in the
specified database. So for each table, it goes to get the metadata back. For a
large database with many tables, it might take long time to get the results
back.
{{SQLContext.tableNames}} goes around this interface and accesses
{{SessionCatalog.listTables}} which just retrieves table names.
In Spark 2.1, {{SessionCatalog}} is internal and you can't access it through
{{SparkSession}}. However, it is open up since 2.2, but it's still not an
user-facing API. It is open up just to ease debugging.
Personally I'd think that there should be an API in user-facing {{CatalogImpl}}
to return just table names. If users like to get more metadata, they can use
{{CatalogImpl.getTable}} with the table name.
> SparkSession catalog is terribly slow
> -------------------------------------
>
> Key: SPARK-21198
> URL: https://issues.apache.org/jira/browse/SPARK-21198
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.1.0
> Reporter: Saif Addin
>
> We have a considerably large Hive metastore and a Spark program that goes
> through Hive data availability.
> In spark 1.x, we were using sqlConext.tableNames, sqlContext.sql() and
> sqlContext.isCached() to go throgh Hive metastore information.
> Once migrated to spark 2.x we switched over SparkSession.catalog instead, but
> it turns out that both listDatabases() and listTables() take between 5 to 20
> minutes depending on the database to return results, using operations such as
> the following one:
> spark.catalog.listTables(db).filter(__.isTemporary).map(__.name).collect
> and made the program unbearably slow to return a list of tables.
> I know we still have spark.sqlContext.tableNames as workaround but I am
> assuming this is going to be deprecated anytime soon?
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