You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Kazuaki Ishizaki (JIRA)" <ji...@apache.org> on 2017/11/09 17:02:00 UTC
[jira] [Commented] (SPARK-22481) CatalogImpl.refreshTable is slow
[ https://issues.apache.org/jira/browse/SPARK-22481?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16246041#comment-16246041 ]
Kazuaki Ishizaki commented on SPARK-22481:
------------------------------------------
This change was introduce by [this PR|https://github.com/apache/spark/pull/17097/files#diff-463cb1b0f60d87ada075a820f18e1104R443]. It seems to be related to the first refactoring in the description.
[~cloud_fan] Is there any reason to always call {{sparkSession.table()}}?
> CatalogImpl.refreshTable is slow
> --------------------------------
>
> Key: SPARK-22481
> URL: https://issues.apache.org/jira/browse/SPARK-22481
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.1.1, 2.1.2, 2.2.0
> Reporter: Ran Haim
> Priority: Critical
>
> CatalogImpl.refreshTable was updated in 2.1.1 and since than it has become really slow.
> The cause of the issue is that it is now *always* creates a dataset, and this is redundant most of the time, we only need the dataset if the table is cached.
> before 2.1.1:
> override def refreshTable(tableName: String): Unit = {
> val tableIdent = sparkSession.sessionState.sqlParser.parseTableIdentifier(tableName)
> // Temp tables: refresh (or invalidate) any metadata/data cached in the plan recursively.
> // Non-temp tables: refresh the metadata cache.
> sessionCatalog.refreshTable(tableIdent)
> // If this table is cached as an InMemoryRelation, drop the original
> // cached version and make the new version cached lazily.
> val logicalPlan = sparkSession.sessionState.catalog.lookupRelation(tableIdent)
> // Use lookupCachedData directly since RefreshTable also takes databaseName.
> val isCached = sparkSession.sharedState.cacheManager.lookupCachedData(logicalPlan).nonEmpty
> if (isCached) {
> // Create a data frame to represent the table.
> // TODO: Use uncacheTable once it supports database name.
> {color:red} val df = Dataset.ofRows(sparkSession, logicalPlan){color}
> // Uncache the logicalPlan.
> sparkSession.sharedState.cacheManager.uncacheQuery(df, blocking = true)
> // Cache it again.
> sparkSession.sharedState.cacheManager.cacheQuery(df, Some(tableIdent.table))
> }
> }
> after 2.1.1:
> override def refreshTable(tableName: String): Unit = {
> val tableIdent = sparkSession.sessionState.sqlParser.parseTableIdentifier(tableName)
> // Temp tables: refresh (or invalidate) any metadata/data cached in the plan recursively.
> // Non-temp tables: refresh the metadata cache.
> sessionCatalog.refreshTable(tableIdent)
> // If this table is cached as an InMemoryRelation, drop the original
> // cached version and make the new version cached lazily.
> {color:red} val table = sparkSession.table(tableIdent){color}
> if (isCached(table)) {
> // Uncache the logicalPlan.
> sparkSession.sharedState.cacheManager.uncacheQuery(table, blocking = true)
> // Cache it again.
> sparkSession.sharedState.cacheManager.cacheQuery(table, Some(tableIdent.table))
> }
> }
--
This message was sent by Atlassian JIRA
(v6.4.14#64029)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org