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https://issues.apache.org/jira/browse/SPARK-21198?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16062194#comment-16062194
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Liang-Chi Hsieh commented on SPARK-21198:
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Have you profile the time spent in your application?
Although I think {{CatalogImpl.listTables}} which retrieves table metadata will
cost more time, I'm not sure if it will take 5 to 20 minutes (based on your
description above) for a database with 200 tables. If it takes 0.1s to retrieve
one table metadata, it should not cost more than 1 min.
> SparkSession catalog is terribly slow
> -------------------------------------
>
> Key: SPARK-21198
> URL: https://issues.apache.org/jira/browse/SPARK-21198
> Project: Spark
> Issue Type: Bug
> Components: SQL
> 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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