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https://issues.apache.org/jira/browse/SPARK-21198?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16063431#comment-16063431
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Saif Addin commented on SPARK-21198:
------------------------------------
Regarding listtables, here is the code used inside the program:
{code:java}
println(s"processing all tables for every db. db length is:
${databases.tail.length}")
for (d <- databases.tail) {
val d1 = new Date().getTime
val dbs = spark.sqlContext.tables(d).filter("isTemporary =
false").select("tableName").collect.map(_.getString(0))
println("Processed tables in DB using sqlContext. Time: " + ((new
Date().getTime - d1) / 1000.0) + s" seconds. ${dbs.length} tables")
val d2 = new Date().getTime
val dbs2 =
spark.catalog.listTables(d).filter(!_.isTemporary).map(_.name).collect
println("Processed tables in DB using catalog. Time: " + ((new
Date().getTime - d2) / 1000.0) + s" seconds. ${dbs.length} tables")
....other stuff
{code}
and timings are as follows
{code:java}
processing all tables for every db. db length is: 30
Processed tables in DB using sqlContext. Time: 0.863 seconds. 19 tables
Processed tables in DB using catalog. Time: 6.978 seconds. 19 tables
Processed tables in DB using sqlContext. Time: 0.276 seconds. 607 tables
Processed tables in DB using catalog. Time: 194.501 seconds. 607 tables
Processed tables in DB using sqlContext. Time: 0.243 seconds. 55 tables
Processed tables in DB using catalog. Time: 17.907 seconds. 55 tables
Processed tables in DB using sqlContext. Time: 0.238 seconds. 13 tables
Processed tables in DB using catalog. Time: 4.642 seconds. 13 tables
Processed tables in DB using sqlContext. Time: 0.238 seconds. 392 tables
... goes on...
{code}
> 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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