SPARK-1154: Clean up app folders in worker nodes #288

velvia · 2014-04-01T20:37:02Z

This is a fix for SPARK-1154. The issue is that worker nodes fill up with a huge number of app-* folders after some time. This change adds a periodic cleanup task which asynchronously deletes app directories older than a configurable TTL.

Two new configuration parameters have been introduced:
spark.worker.cleanup_interval
spark.worker.app_data_ttl

This change does not include moving the downloads of application jars to a location outside of the work directory. We will address that if we have time, but that potentially involves caching so it will come either as part of this PR or a separate PR.

AmplabJenkins · 2014-04-01T20:37:22Z

Merged build triggered.

AmplabJenkins · 2014-04-01T20:37:31Z

Merged build started.

AmplabJenkins · 2014-04-01T21:57:36Z

Merged build finished. All automated tests passed.

AmplabJenkins · 2014-04-01T21:57:36Z

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AmplabJenkins · 2014-04-02T08:32:23Z

Merged build triggered.

AmplabJenkins · 2014-04-02T08:32:30Z

Merged build started.

AmplabJenkins · 2014-04-02T09:32:14Z

Merged build finished. All automated tests passed.

AmplabJenkins · 2014-04-02T09:32:14Z

All automated tests passed.
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AmplabJenkins · 2014-04-02T18:02:23Z

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AmplabJenkins · 2014-04-02T18:02:33Z

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andrewor14 · 2014-04-02T19:11:45Z

core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala

+  val CLEANUP_INTERVAL_MILLIS = conf.getLong("spark.worker.cleanup_interval", 60 * 30) * 1000
+  // TTL for app folders/data;  after TTL expires it will be cleaned up
+  val APP_DATA_RETENTION_SECS = conf.getLong("spark.worker.app_data_ttl", 7 * 24 * 3600)
+


For Spark configuration we use camel case: see http://spark.apache.org/docs/0.9.0/configuration.html

Thanks, will fix.

AmplabJenkins · 2014-04-02T19:24:21Z

Merged build finished. All automated tests passed.

AmplabJenkins · 2014-04-02T19:24:21Z

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aarondav · 2014-04-02T19:24:34Z

core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala


    case SendHeartbeat =>
      masterLock.synchronized {
        if (connected) { master ! Heartbeat(workerId) }
      }

+    case Worker.AppDirCleanup =>
+      // Spin up a separate thread (in a future) to do the dir cleanup; don't tie up worker actor
+      val cleanupFuture = concurrent.future {


What ExecutionContext is this using? Is there a default one created for actors?

There is a default one for each actor, yes -- from its actorSystem.

AmplabJenkins · 2014-04-03T00:02:23Z

Build triggered.

AmplabJenkins · 2014-04-03T00:02:30Z

Build started.

velvia · 2014-04-03T00:03:08Z

Most comments addressed.

pwendell · 2014-04-03T00:03:20Z

I think something weird happened with the diff... seems to be showing a lot of changes.

velvia · 2014-04-03T00:05:12Z

@pwendell I did a git merge master and for some reason it didn't display as a merge..... :( must have gotten confused about multiple remotes.

AmplabJenkins · 2014-04-03T00:58:31Z

Build finished. All automated tests passed.

AmplabJenkins · 2014-04-03T00:58:31Z

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aarondav · 2014-04-03T01:00:15Z

Mind doing a rebase to simplify the diff? It'll be squashed anyhow when we merge it into master.

velvia · 2014-04-03T07:49:59Z

Sorry, but how do I do a rebase safely, now that I've pushed? I've never
had good luck with rebases (other than rebase -i before I push.... sorry
should have done that.)

On Wed, Apr 2, 2014 at 6:00 PM, Aaron Davidson [email protected]:

Mind doing a rebase to simplify the diff? It'll be squashed anyhow when we
merge it into master.

Reply to this email directly or view it on GitHubhttps://github.com//pull/288#issuecomment-39402284
.

The fruit of silence is prayer;
the fruit of prayer is faith;
the fruit of faith is love;
the fruit of love is service;
the fruit of service is peace. -- Mother Teresa

pwendell · 2014-04-03T17:37:39Z

@velvia what happens if you just close and re-open the pull request? Will that work?

AmplabJenkins · 2014-04-03T22:47:31Z

Merged build started.

AmplabJenkins · 2014-04-03T23:44:36Z

Merged build finished. All automated tests passed.

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All automated tests passed.
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velvia · 2014-04-05T00:20:22Z

Hey guys - think everything is addressed. Jenkins claims the build passes, but for some reason there is a Failed message at the bottom of the PR. ?

pwendell · 2014-04-05T03:49:31Z

Jenkins, test this please. (just running on jeknins again, think the travis one is a false negative).

pwendell · 2014-04-05T03:52:00Z

core/src/main/scala/org/apache/spark/util/Utils.scala

@@ -537,6 +537,21 @@ private[spark] object Utils extends Logging {
  }

  /**
+   * Finds all the files in a directory whose last modified time is older than cutoff seconds.
+   * @param dir  must be the path to a directory, or IllegalArgumentException is thrown
+   * @param cutoff measured in seconds. Files older than this are returned.


Don't need to rev this again just for this - but is there supposed to be one space or two spaces after the parameter name? It's inconsistent here.

AmplabJenkins · 2014-04-05T03:52:23Z

Build triggered.

AmplabJenkins · 2014-04-05T03:52:31Z

Build started.

AmplabJenkins · 2014-04-05T04:47:53Z

Build finished. All automated tests passed.

AmplabJenkins · 2014-04-05T04:47:54Z

All automated tests passed.
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pwendell · 2014-04-05T05:50:17Z

@aarondav look good to you?

aarondav · 2014-04-06T01:01:51Z

LGTM, would you mind bringing this up to date with master (looks like a pretty trivial conflict).

pwendell · 2014-04-07T02:22:46Z

I just went ahead and fixed the conflict and merged this.

velvia · 2014-04-07T02:28:02Z

Thanks Patrick!

-Evan
To be free is not merely to cast off one's chains, but to live in a way that respects & enhances the freedom of others. (#NelsonMandela)

On Apr 6, 2014, at 7:22 PM, Patrick Wendell [email protected] wrote:

I just went ahead and fixed the conflict and merged this.

—
Reply to this email directly or view it on GitHub.

standard Naive Bayes classifier Has implemented the standard Naive Bayes classifier. This is an updated version of apache#288, which is closed because of misoperations.

@aarondav

This is a fix for [SPARK-1154](https://issues.apache.org/jira/browse/SPARK-1154). The issue is that worker nodes fill up with a huge number of app-* folders after some time. This change adds a periodic cleanup task which asynchronously deletes app directories older than a configurable TTL. Two new configuration parameters have been introduced: spark.worker.cleanup_interval spark.worker.app_data_ttl This change does not include moving the downloads of application jars to a location outside of the work directory. We will address that if we have time, but that potentially involves caching so it will come either as part of this PR or a separate PR. Author: Evan Chan <[email protected]> Author: Kelvin Chu <[email protected]> Closes apache#288 from velvia/SPARK-1154-cleanup-app-folders and squashes the following commits: 0689995 [Evan Chan] CR from @aarondav - move config, clarify for standalone mode 9f10d96 [Evan Chan] CR from @pwendell - rename configs and add cleanup.enabled f2f6027 [Evan Chan] CR from @andrewor14 553d8c2 [Kelvin Chu] change the variable name to currentTimeMillis since it actually tracks in seconds 8dc9cb5 [Kelvin Chu] Fixed a bug in Utils.findOldFiles() after merge. cb52f2b [Kelvin Chu] Change the name of findOldestFiles() to findOldFiles() 72f7d2d [Kelvin Chu] Fix a bug of Utils.findOldestFiles(). file.lastModified is returned in milliseconds. ad99955 [Kelvin Chu] Add unit test for Utils.findOldestFiles() dc1a311 [Evan Chan] Don't recompute current time with every new file e3c408e [Evan Chan] Document the two new settings b92752b [Evan Chan] SPARK-1154: Add a periodic task to clean up app directories

* Bump to Hadoop 2.9.0-palantir.3 * Update deps list

This reverts commit bb010b8.

* Revert "Bump Hadoop to 2.9.0-palantir.3 (apache#288)" This reverts commit bb010b8. * Revert "Hadoop 2.9.0-palantir.2 (apache#283)" This reverts commit 65956b7.

### What changes were proposed in this pull request? It is very common for a SQL query to query a table more than once. For example: ``` == Physical Plan == *(12) HashAggregate(keys=[cmn_mtrc_summ_dt#21, rev_rollup#1279, CASE WHEN (rev_rollup#1319 = rev_rollup#1279) THEN 0 ELSE 1 END#1366, CASE WHEN cast(sap_category_id#24 as decimal(10,0)) IN (5,7,23,41) THEN 0 ELSE 1 END#1367], functions=[sum(coalesce(bid_count#34, 0)), sum(coalesce(ck_trans_count#35, 0)), sum(coalesce(ended_bid_count#36, 0)), sum(coalesce(ended_lstg_count#37, 0)), sum(coalesce(ended_success_lstg_count#38, 0)), sum(coalesce(item_sold_count#39, 0)), sum(coalesce(new_lstg_count#40, 0)), sum(coalesce(gmv_us_amt#41, 0.00)), sum(coalesce(gmv_slr_lc_amt#42, 0.00)), sum(CheckOverflow((promote_precision(cast(coalesce(rvnu_insrtn_fee_us_amt#46, 0.000000) as decimal(19,6))) + promote_precision(cast(coalesce(rvnu_insrtn_crd_us_amt#50, 0.000000) as decimal(19,6)))), DecimalType(19,6), true)), sum(CheckOverflow((promote_precision(cast(coalesce(rvnu_fetr_fee_us_amt#54, 0.000000) as decimal(19,6))) + promote_precision(cast(coalesce(rvnu_fetr_crd_us_amt#58, 0.000000) as decimal(19,6)))), DecimalType(19,6), true)), sum(CheckOverflow((promote_precision(cast(coalesce(rvnu_fv_fee_us_amt#62, 0.000000) as decimal(19,6))) + promote_precision(cast(coalesce(rvnu_fv_crd_us_amt#67, 0.000000) as decimal(19,6)))), DecimalType(19,6), true)), sum(CheckOverflow((promote_precision(cast(coalesce(rvnu_othr_l_fee_us_amt#72, 0.000000) as decimal(19,6))) + promote_precision(cast(coalesce(rvnu_othr_l_crd_us_amt#76, 0.000000) as decimal(19,6)))), DecimalType(19,6), true)), sum(CheckOverflow((promote_precision(cast(coalesce(rvnu_othr_nl_fee_us_amt#80, 0.000000) as decimal(19,6))) + promote_precision(cast(coalesce(rvnu_othr_nl_crd_us_amt#84, 0.000000) as decimal(19,6)))), DecimalType(19,6), true)), sum(CheckOverflow((promote_precision(cast(coalesce(rvnu_slr_tools_fee_us_amt#88, 0.000000) as decimal(19,6))) + promote_precision(cast(coalesce(rvnu_slr_tools_crd_us_amt#92, 0.000000) as decimal(19,6)))), DecimalType(19,6), true)), sum(coalesce(rvnu_unasgnd_us_amt#96, 0.000000)), sum((coalesce(rvnu_transaction_us_amt#112, 0.0) + coalesce(rvnu_transaction_crd_us_amt#115, 0.0))), sum((coalesce(rvnu_total_us_amt#118, 0.0) + coalesce(rvnu_total_crd_us_amt#121, 0.0)))]) +- Exchange hashpartitioning(cmn_mtrc_summ_dt#21, rev_rollup#1279, CASE WHEN (rev_rollup#1319 = rev_rollup#1279) THEN 0 ELSE 1 END#1366, CASE WHEN cast(sap_category_id#24 as decimal(10,0)) IN (5,7,23,41) THEN 0 ELSE 1 END#1367, 200), true, [id=#403] +- *(11) HashAggregate(keys=[cmn_mtrc_summ_dt#21, rev_rollup#1279, CASE WHEN (rev_rollup#1319 = rev_rollup#1279) THEN 0 ELSE 1 END AS CASE WHEN (rev_rollup#1319 = rev_rollup#1279) THEN 0 ELSE 1 END#1366, CASE WHEN cast(sap_category_id#24 as decimal(10,0)) IN (5,7,23,41) THEN 0 ELSE 1 END AS CASE WHEN cast(sap_category_id#24 as decimal(10,0)) IN (5,7,23,41) THEN 0 ELSE 1 END#1367], functions=[partial_sum(coalesce(bid_count#34, 0)), partial_sum(coalesce(ck_trans_count#35, 0)), partial_sum(coalesce(ended_bid_count#36, 0)), partial_sum(coalesce(ended_lstg_count#37, 0)), partial_sum(coalesce(ended_success_lstg_count#38, 0)), partial_sum(coalesce(item_sold_count#39, 0)), partial_sum(coalesce(new_lstg_count#40, 0)), partial_sum(coalesce(gmv_us_amt#41, 0.00)), partial_sum(coalesce(gmv_slr_lc_amt#42, 0.00)), partial_sum(CheckOverflow((promote_precision(cast(coalesce(rvnu_insrtn_fee_us_amt#46, 0.000000) as decimal(19,6))) + promote_precision(cast(coalesce(rvnu_insrtn_crd_us_amt#50, 0.000000) as decimal(19,6)))), DecimalType(19,6), true)), partial_sum(CheckOverflow((promote_precision(cast(coalesce(rvnu_fetr_fee_us_amt#54, 0.000000) as decimal(19,6))) + promote_precision(cast(coalesce(rvnu_fetr_crd_us_amt#58, 0.000000) as decimal(19,6)))), DecimalType(19,6), true)), partial_sum(CheckOverflow((promote_precision(cast(coalesce(rvnu_fv_fee_us_amt#62, 0.000000) as decimal(19,6))) + promote_precision(cast(coalesce(rvnu_fv_crd_us_amt#67, 0.000000) as decimal(19,6)))), DecimalType(19,6), true)), partial_sum(CheckOverflow((promote_precision(cast(coalesce(rvnu_othr_l_fee_us_amt#72, 0.000000) as decimal(19,6))) + promote_precision(cast(coalesce(rvnu_othr_l_crd_us_amt#76, 0.000000) as decimal(19,6)))), DecimalType(19,6), true)), partial_sum(CheckOverflow((promote_precision(cast(coalesce(rvnu_othr_nl_fee_us_amt#80, 0.000000) as decimal(19,6))) + promote_precision(cast(coalesce(rvnu_othr_nl_crd_us_amt#84, 0.000000) as decimal(19,6)))), DecimalType(19,6), true)), partial_sum(CheckOverflow((promote_precision(cast(coalesce(rvnu_slr_tools_fee_us_amt#88, 0.000000) as decimal(19,6))) + promote_precision(cast(coalesce(rvnu_slr_tools_crd_us_amt#92, 0.000000) as decimal(19,6)))), DecimalType(19,6), true)), partial_sum(coalesce(rvnu_unasgnd_us_amt#96, 0.000000)), partial_sum((coalesce(rvnu_transaction_us_amt#112, 0.0) + coalesce(rvnu_transaction_crd_us_amt#115, 0.0))), partial_sum((coalesce(rvnu_total_us_amt#118, 0.0) + coalesce(rvnu_total_crd_us_amt#121, 0.0)))]) +- *(11) Project [cmn_mtrc_summ_dt#21, sap_category_id#24, bid_count#34, ck_trans_count#35, ended_bid_count#36, ended_lstg_count#37, ended_success_lstg_count#38, item_sold_count#39, new_lstg_count#40, gmv_us_amt#41, gmv_slr_lc_amt#42, rvnu_insrtn_fee_us_amt#46, rvnu_insrtn_crd_us_amt#50, rvnu_fetr_fee_us_amt#54, rvnu_fetr_crd_us_amt#58, rvnu_fv_fee_us_amt#62, rvnu_fv_crd_us_amt#67, rvnu_othr_l_fee_us_amt#72, rvnu_othr_l_crd_us_amt#76, rvnu_othr_nl_fee_us_amt#80, rvnu_othr_nl_crd_us_amt#84, rvnu_slr_tools_fee_us_amt#88, rvnu_slr_tools_crd_us_amt#92, rvnu_unasgnd_us_amt#96, ... 6 more fields] +- *(11) BroadcastHashJoin [byr_cntry_id#23], [cntry_id#1309], LeftOuter, BuildRight :- *(11) Project [cmn_mtrc_summ_dt#21, byr_cntry_id#23, sap_category_id#24, bid_count#34, ck_trans_count#35, ended_bid_count#36, ended_lstg_count#37, ended_success_lstg_count#38, item_sold_count#39, new_lstg_count#40, gmv_us_amt#41, gmv_slr_lc_amt#42, rvnu_insrtn_fee_us_amt#46, rvnu_insrtn_crd_us_amt#50, rvnu_fetr_fee_us_amt#54, rvnu_fetr_crd_us_amt#58, rvnu_fv_fee_us_amt#62, rvnu_fv_crd_us_amt#67, rvnu_othr_l_fee_us_amt#72, rvnu_othr_l_crd_us_amt#76, rvnu_othr_nl_fee_us_amt#80, rvnu_othr_nl_crd_us_amt#84, rvnu_slr_tools_fee_us_amt#88, rvnu_slr_tools_crd_us_amt#92, ... 6 more fields] : +- *(11) BroadcastHashJoin [slr_cntry_id#28], [cntry_id#1269], LeftOuter, BuildRight : :- *(11) Project [gen_attr_1#360 AS cmn_mtrc_summ_dt#21, gen_attr_5#267 AS byr_cntry_id#23, gen_attr_7#268 AS sap_category_id#24, gen_attr_15#272 AS slr_cntry_id#28, gen_attr_27#278 AS bid_count#34, gen_attr_29#279 AS ck_trans_count#35, gen_attr_31#280 AS ended_bid_count#36, gen_attr_33#282 AS ended_lstg_count#37, gen_attr_35#283 AS ended_success_lstg_count#38, gen_attr_37#284 AS item_sold_count#39, gen_attr_39#281 AS new_lstg_count#40, gen_attr_41#285 AS gmv_us_amt#41, gen_attr_43#287 AS gmv_slr_lc_amt#42, gen_attr_51#290 AS rvnu_insrtn_fee_us_amt#46, gen_attr_59#294 AS rvnu_insrtn_crd_us_amt#50, gen_attr_67#298 AS rvnu_fetr_fee_us_amt#54, gen_attr_75#302 AS rvnu_fetr_crd_us_amt#58, gen_attr_83#306 AS rvnu_fv_fee_us_amt#62, gen_attr_93#311 AS rvnu_fv_crd_us_amt#67, gen_attr_103#316 AS rvnu_othr_l_fee_us_amt#72, gen_attr_111#320 AS rvnu_othr_l_crd_us_amt#76, gen_attr_119#324 AS rvnu_othr_nl_fee_us_amt#80, gen_attr_127#328 AS rvnu_othr_nl_crd_us_amt#84, gen_attr_135#332 AS rvnu_slr_tools_fee_us_amt#88, ... 6 more fields] : : +- *(11) BroadcastHashJoin [cast(gen_attr_308#777 as decimal(20,0))], [cast(gen_attr_309#803 as decimal(20,0))], LeftOuter, BuildRight : : :- *(11) Project [gen_attr_5#267, gen_attr_7#268, gen_attr_15#272, gen_attr_27#278, gen_attr_29#279, gen_attr_31#280, gen_attr_39#281, gen_attr_33#282, gen_attr_35#283, gen_attr_37#284, gen_attr_41#285, gen_attr_43#287, gen_attr_51#290, gen_attr_59#294, gen_attr_67#298, gen_attr_75#302, gen_attr_83#306, gen_attr_93#311, gen_attr_103#316, gen_attr_111#320, gen_attr_119#324, gen_attr_127#328, gen_attr_135#332, gen_attr_143#336, ... 6 more fields] : : : +- *(11) BroadcastHashJoin [cast(gen_attr_310#674 as int)], [cast(gen_attr_311#774 as int)], LeftOuter, BuildRight : : : :- *(11) Project [gen_attr_5#267, gen_attr_7#268, gen_attr_15#272, gen_attr_27#278, gen_attr_29#279, gen_attr_31#280, gen_attr_39#281, gen_attr_33#282, gen_attr_35#283, gen_attr_37#284, gen_attr_41#285, gen_attr_43#287, gen_attr_51#290, gen_attr_59#294, gen_attr_67#298, gen_attr_75#302, gen_attr_83#306, gen_attr_93#311, gen_attr_103#316, gen_attr_111#320, gen_attr_119#324, gen_attr_127#328, gen_attr_135#332, gen_attr_143#336, ... 6 more fields] : : : : +- *(11) BroadcastHashJoin [cast(gen_attr_5#267 as decimal(20,0))], [cast(gen_attr_312#665 as decimal(20,0))], LeftOuter, BuildRight : : : : :- *(11) Project [gen_attr_5#267, gen_attr_7#268, gen_attr_15#272, gen_attr_27#278, gen_attr_29#279, gen_attr_31#280, gen_attr_39#281, gen_attr_33#282, gen_attr_35#283, gen_attr_37#284, gen_attr_41#285, gen_attr_43#287, gen_attr_51#290, gen_attr_59#294, gen_attr_67#298, gen_attr_75#302, gen_attr_83#306, gen_attr_93#311, gen_attr_103#316, gen_attr_111#320, gen_attr_119#324, gen_attr_127#328, gen_attr_135#332, gen_attr_143#336, ... 5 more fields] : : : : : +- *(11) BroadcastHashJoin [cast(gen_attr_313#565 as decimal(20,0))], [cast(gen_attr_314#591 as decimal(20,0))], LeftOuter, BuildRight : : : : : :- *(11) Project [gen_attr_5#267, gen_attr_7#268, gen_attr_15#272, gen_attr_27#278, gen_attr_29#279, gen_attr_31#280, gen_attr_39#281, gen_attr_33#282, gen_attr_35#283, gen_attr_37#284, gen_attr_41#285, gen_attr_43#287, gen_attr_51#290, gen_attr_59#294, gen_attr_67#298, gen_attr_75#302, gen_attr_83#306, gen_attr_93#311, gen_attr_103#316, gen_attr_111#320, gen_attr_119#324, gen_attr_127#328, gen_attr_135#332, gen_attr_143#336, ... 6 more fields] : : : : : : +- *(11) BroadcastHashJoin [cast(gen_attr_315#462 as int)], [cast(gen_attr_316#562 as int)], LeftOuter, BuildRight : : : : : : :- *(11) Project [gen_attr_5#267, gen_attr_7#268, gen_attr_15#272, gen_attr_27#278, gen_attr_29#279, gen_attr_31#280, gen_attr_39#281, gen_attr_33#282, gen_attr_35#283, gen_attr_37#284, gen_attr_41#285, gen_attr_43#287, gen_attr_51#290, gen_attr_59#294, gen_attr_67#298, gen_attr_75#302, gen_attr_83#306, gen_attr_93#311, gen_attr_103#316, gen_attr_111#320, gen_attr_119#324, gen_attr_127#328, gen_attr_135#332, gen_attr_143#336, ... 6 more fields] : : : : : : : +- *(11) BroadcastHashJoin [cast(gen_attr_15#272 as decimal(20,0))], [cast(gen_attr_317#453 as decimal(20,0))], LeftOuter, BuildRight : : : : : : : :- *(11) Project [gen_attr_5#267, gen_attr_7#268, gen_attr_15#272, gen_attr_27#278, gen_attr_29#279, gen_attr_31#280, gen_attr_39#281, gen_attr_33#282, gen_attr_35#283, gen_attr_37#284, gen_attr_41#285, gen_attr_43#287, gen_attr_51#290, gen_attr_59#294, gen_attr_67#298, gen_attr_75#302, gen_attr_83#306, gen_attr_93#311, gen_attr_103#316, gen_attr_111#320, gen_attr_119#324, gen_attr_127#328, gen_attr_135#332, gen_attr_143#336, ... 5 more fields] : : : : : : : : +- *(11) BroadcastHashJoin [cast(gen_attr_25#277 as decimal(20,0))], [cast(gen_attr_318#379 as decimal(20,0))], LeftOuter, BuildRight : : : : : : : : :- *(11) Project [gen_attr_5#267, gen_attr_7#268, gen_attr_15#272, gen_attr_25#277, gen_attr_27#278, gen_attr_29#279, gen_attr_31#280, gen_attr_39#281, gen_attr_33#282, gen_attr_35#283, gen_attr_37#284, gen_attr_41#285, gen_attr_43#287, gen_attr_51#290, gen_attr_59#294, gen_attr_67#298, gen_attr_75#302, gen_attr_83#306, gen_attr_93#311, gen_attr_103#316, gen_attr_111#320, gen_attr_119#324, gen_attr_127#328, gen_attr_135#332, ... 6 more fields] : : : : : : : : : +- *(11) BroadcastHashJoin [cast(gen_attr_23#276 as decimal(20,0))], [cast(gen_attr_319#367 as decimal(20,0))], LeftOuter, BuildRight : : : : : : : : : :- *(11) Project [byr_cntry_id#1169 AS gen_attr_5#267, sap_category_id#1170 AS gen_attr_7#268, slr_cntry_id#1174 AS gen_attr_15#272, lstg_curncy_id#1178 AS gen_attr_23#276, blng_curncy_id#1179 AS gen_attr_25#277, bid_count#1180 AS gen_attr_27#278, ck_trans_count#1181 AS gen_attr_29#279, ended_bid_count#1182 AS gen_attr_31#280, new_lstg_count#1183 AS gen_attr_39#281, ended_lstg_count#1184 AS gen_attr_33#282, ended_success_lstg_count#1185 AS gen_attr_35#283, item_sold_count#1186 AS gen_attr_37#284, gmv_us_amt#1187 AS gen_attr_41#285, gmv_slr_lc_amt#1189 AS gen_attr_43#287, rvnu_insrtn_fee_us_amt#1192 AS gen_attr_51#290, rvnu_insrtn_crd_us_amt#1196 AS gen_attr_59#294, rvnu_fetr_fee_us_amt#1200 AS gen_attr_67#298, rvnu_fetr_crd_us_amt#1204 AS gen_attr_75#302, rvnu_fv_fee_us_amt#1208 AS gen_attr_83#306, rvnu_fv_crd_us_amt#1213 AS gen_attr_93#311, rvnu_othr_l_fee_us_amt#1218 AS gen_attr_103#316, rvnu_othr_l_crd_us_amt#1222 AS gen_attr_111#320, rvnu_othr_nl_fee_us_amt#1226 AS gen_attr_119#324, rvnu_othr_nl_crd_us_amt#1230 AS gen_attr_127#328, ... 7 more fields] : : : : : : : : : : +- *(11) ColumnarToRow : : : : : : : : : : +- FileScan parquet default.big_table1[byr_cntry_id#1169,sap_category_id#1170,slr_cntry_id#1174,lstg_curncy_id#1178,blng_curncy_id#1179,bid_count#1180,ck_trans_count#1181,ended_bid_count#1182,new_lstg_count#1183,ended_lstg_count#1184,ended_success_lstg_count#1185,item_sold_count#1186,gmv_us_amt#1187,gmv_slr_lc_amt#1189,rvnu_insrtn_fee_us_amt#1192,rvnu_insrtn_crd_us_amt#1196,rvnu_fetr_fee_us_amt#1200,rvnu_fetr_crd_us_amt#1204,rvnu_fv_fee_us_amt#1208,rvnu_fv_crd_us_amt#1213,rvnu_othr_l_fee_us_amt#1218,rvnu_othr_l_crd_us_amt#1222,rvnu_othr_nl_fee_us_amt#1226,rvnu_othr_nl_crd_us_amt#1230,... 7 more fields] Batched: true, DataFilters: [], Format: Parquet, Location: PrunedInMemoryFileIndex[], PartitionFilters: [isnotnull(cmn_mtrc_summ_dt#1262), (cmn_mtrc_summ_dt#1262 >= 18078), (cmn_mtrc_summ_dt#1262 <= 18..., PushedFilters: [], ReadSchema: struct<byr_cntry_id:decimal(4,0),sap_category_id:decimal(9,0),slr_cntry_id:decimal(4,0),lstg_curn... : : : : : : : : : +- BroadcastExchange HashedRelationBroadcastMode(List(cast(input[0, decimal(9,0), true] as decimal(20,0)))), [id=#288] : : : : : : : : : +- *(1) Project [CURNCY_ID#1263 AS gen_attr_319#367] : : : : : : : : : +- *(1) Filter isnotnull(CURNCY_ID#1263) : : : : : : : : : +- *(1) ColumnarToRow : : : : : : : : : +- FileScan parquet default.small_table1[CURNCY_ID#1263] Batched: true, DataFilters: [isnotnull(CURNCY_ID#1263)], Format: Parquet, Location: InMemoryFileIndex[file:/user/hive/warehouse/small_table1], PartitionFilters: [], PushedFilters: [IsNotNull(CURNCY_ID)], ReadSchema: struct<CURNCY_ID:decimal(9,0)>, SelectedBucketsCount: 1 out of 1 : : : : : : : : +- BroadcastExchange HashedRelationBroadcastMode(List(cast(input[0, decimal(9,0), true] as decimal(20,0)))), [id=#297] : : : : : : : : +- *(2) Project [CURNCY_ID#1263 AS gen_attr_318#379] : : : : : : : : +- *(2) Filter isnotnull(CURNCY_ID#1263) : : : : : : : : +- *(2) ColumnarToRow : : : : : : : : +- FileScan parquet default.small_table1[CURNCY_ID#1263] Batched: true, DataFilters: [isnotnull(CURNCY_ID#1263)], Format: Parquet, Location: InMemoryFileIndex[file:/user/hive/warehouse/small_table1], PartitionFilters: [], PushedFilters: [IsNotNull(CURNCY_ID)], ReadSchema: struct<CURNCY_ID:decimal(9,0)>, SelectedBucketsCount: 1 out of 1 : : : : : : : +- BroadcastExchange HashedRelationBroadcastMode(List(cast(input[0, decimal(4,0), true] as decimal(20,0)))), [id=#306] : : : : : : : +- *(3) Project [cntry_id#1269 AS gen_attr_317#453, rev_rollup_id#1278 AS gen_attr_315#462] : : : : : : : +- *(3) Filter isnotnull(cntry_id#1269) : : : : : : : +- *(3) ColumnarToRow : : : : : : : +- FileScan parquet default.small_table2[cntry_id#1269,rev_rollup_id#1278] Batched: true, DataFilters: [isnotnull(cntry_id#1269)], Format: Parquet, Location: InMemoryFileIndex[file:/user/hive/warehouse/small_table2], PartitionFilters: [], PushedFilters: [IsNotNull(cntry_id)], ReadSchema: struct<cntry_id:decimal(4,0),rev_rollup_id:smallint> : : : : : : +- BroadcastExchange HashedRelationBroadcastMode(List(cast(cast(input[0, smallint, true] as int) as bigint))), [id=#315] : : : : : : +- *(4) Project [rev_rollup_id#1286 AS gen_attr_316#562, curncy_id#1289 AS gen_attr_313#565] : : : : : : +- *(4) Filter isnotnull(rev_rollup_id#1286) : : : : : : +- *(4) ColumnarToRow : : : : : : +- FileScan parquet default.small_table3[rev_rollup_id#1286,curncy_id#1289] Batched: true, DataFilters: [isnotnull(rev_rollup_id#1286)], Format: Parquet, Location: InMemoryFileIndex[file:/user/hive/warehouse/small_table3], PartitionFilters: [], PushedFilters: [IsNotNull(rev_rollup_id)], ReadSchema: struct<rev_rollup_id:smallint,curncy_id:decimal(4,0)> : : : : : +- BroadcastExchange HashedRelationBroadcastMode(List(cast(input[0, decimal(9,0), true] as decimal(20,0)))), [id=#324] : : : : : +- *(5) Project [CURNCY_ID#1263 AS gen_attr_314#591] : : : : : +- *(5) Filter isnotnull(CURNCY_ID#1263) : : : : : +- *(5) ColumnarToRow : : : : : +- FileScan parquet default.small_table1[CURNCY_ID#1263] Batched: true, DataFilters: [isnotnull(CURNCY_ID#1263)], Format: Parquet, Location: InMemoryFileIndex[file:/user/hive/warehouse/small_table1], PartitionFilters: [], PushedFilters: [IsNotNull(CURNCY_ID)], ReadSchema: struct<CURNCY_ID:decimal(9,0)>, SelectedBucketsCount: 1 out of 1 : : : : +- BroadcastExchange HashedRelationBroadcastMode(List(cast(input[0, decimal(4,0), true] as decimal(20,0)))), [id=#333] : : : : +- *(6) Project [cntry_id#1269 AS gen_attr_312#665, rev_rollup_id#1278 AS gen_attr_310#674] : : : : +- *(6) Filter isnotnull(cntry_id#1269) : : : : +- *(6) ColumnarToRow : : : : +- FileScan parquet default.small_table2[cntry_id#1269,rev_rollup_id#1278] Batched: true, DataFilters: [isnotnull(cntry_id#1269)], Format: Parquet, Location: InMemoryFileIndex[file:/user/hive/warehouse/small_table2], PartitionFilters: [], PushedFilters: [IsNotNull(cntry_id)], ReadSchema: struct<cntry_id:decimal(4,0),rev_rollup_id:smallint> : : : +- BroadcastExchange HashedRelationBroadcastMode(List(cast(cast(input[0, smallint, true] as int) as bigint))), [id=#342] : : : +- *(7) Project [rev_rollup_id#1286 AS gen_attr_311#774, curncy_id#1289 AS gen_attr_308#777] : : : +- *(7) Filter isnotnull(rev_rollup_id#1286) : : : +- *(7) ColumnarToRow : : : +- FileScan parquet default.small_table3[rev_rollup_id#1286,curncy_id#1289] Batched: true, DataFilters: [isnotnull(rev_rollup_id#1286)], Format: Parquet, Location: InMemoryFileIndex[file:/user/hive/warehouse/small_table3], PartitionFilters: [], PushedFilters: [IsNotNull(rev_rollup_id)], ReadSchema: struct<rev_rollup_id:smallint,curncy_id:decimal(4,0)> : : +- BroadcastExchange HashedRelationBroadcastMode(List(cast(input[0, decimal(9,0), true] as decimal(20,0)))), [id=#351] : : +- *(8) Project [CURNCY_ID#1263 AS gen_attr_309#803] : : +- *(8) Filter isnotnull(CURNCY_ID#1263) : : +- *(8) ColumnarToRow : : +- FileScan parquet default.small_table1[CURNCY_ID#1263] Batched: true, DataFilters: [isnotnull(CURNCY_ID#1263)], Format: Parquet, Location: InMemoryFileIndex[file:/user/hive/warehouse/small_table1], PartitionFilters: [], PushedFilters: [IsNotNull(CURNCY_ID)], ReadSchema: struct<CURNCY_ID:decimal(9,0)>, SelectedBucketsCount: 1 out of 1 : +- BroadcastExchange HashedRelationBroadcastMode(List(input[0, decimal(4,0), true])), [id=#360] : +- *(9) Project [cntry_id#1269, rev_rollup#1279] : +- *(9) Filter isnotnull(cntry_id#1269) : +- *(9) ColumnarToRow : +- FileScan parquet default.small_table2[cntry_id#1269,rev_rollup#1279] Batched: true, DataFilters: [isnotnull(cntry_id#1269)], Format: Parquet, Location: InMemoryFileIndex[file:/user/hive/warehouse/small_table2], PartitionFilters: [], PushedFilters: [IsNotNull(cntry_id)], ReadSchema: struct<cntry_id:decimal(4,0),rev_rollup:string> +- ReusedExchange [cntry_id#1309, rev_rollup#1319], BroadcastExchange HashedRelationBroadcastMode(List(input[0, decimal(4,0), true])), [id=#360] ``` This PR try to improve `ResolveTables` and `ResolveRelations` performance by reducing the connection times to Hive Metastore Server in such case. ### Why are the changes needed? 1. Reduce the connection times to Hive Metastore Server. 2. Improve `ResolveTables` and `ResolveRelations` performance. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? manual test. After [SPARK-29606](https://issues.apache.org/jira/browse/SPARK-29606) and before this PR: ``` === Metrics of Analyzer/Optimizer Rules === Total number of runs: 9323 Total time: 2.687441263 seconds Rule Effective Time / Total Time Effective Runs / Total Runs org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations 929173767 / 930133504 2 / 18 org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveTables 0 / 383363402 0 / 18 org.apache.spark.sql.catalyst.optimizer.EliminateOuterJoin 0 / 99433540 0 / 4 org.apache.spark.sql.catalyst.analysis.DecimalPrecision 41809394 / 83727901 2 / 18 org.apache.spark.sql.execution.datasources.PruneFileSourcePartitions 71372977 / 71372977 1 / 1 org.apache.spark.sql.catalyst.analysis.TypeCoercion$ImplicitTypeCasts 0 / 59071933 0 / 18 org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences 37858325 / 58471776 5 / 18 org.apache.spark.sql.catalyst.analysis.TypeCoercion$PromoteStrings 20889892 / 53229016 1 / 18 org.apache.spark.sql.catalyst.analysis.TypeCoercion$FunctionArgumentConversion 23428968 / 50890815 1 / 18 org.apache.spark.sql.catalyst.analysis.TypeCoercion$InConversion 23230666 / 49182607 1 / 18 org.apache.spark.sql.catalyst.analysis.Analyzer$ExtractGenerator 0 / 43638350 0 / 18 org.apache.spark.sql.catalyst.optimizer.ColumnPruning 17194844 / 42530885 1 / 6 ``` After [SPARK-29606](https://issues.apache.org/jira/browse/SPARK-29606) and after this PR: ``` === Metrics of Analyzer/Optimizer Rules === Total number of runs: 9323 Total time: 2.163765869 seconds Rule Effective Time / Total Time Effective Runs / Total Runs org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations 658905353 / 659829383 2 / 18 org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveTables 0 / 220708715 0 / 18 org.apache.spark.sql.catalyst.optimizer.EliminateOuterJoin 0 / 9960681 0 / 4 org.apache.spark.sql.catalyst.analysis.DecimalPrecision 39616060 / 78215752 2 / 18 org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences 36706549 / 54917789 5 / 18 org.apache.spark.sql.execution.datasources.PruneFileSourcePartitions 53561921 / 53561921 1 / 1 org.apache.spark.sql.catalyst.analysis.TypeCoercion$ImplicitTypeCasts 0 / 52329678 0 / 18 org.apache.spark.sql.catalyst.analysis.TypeCoercion$PromoteStrings 20945755 / 49695998 1 / 18 org.apache.spark.sql.catalyst.analysis.TypeCoercion$FunctionArgumentConversion 20872241 / 46740145 1 / 18 org.apache.spark.sql.catalyst.analysis.TypeCoercion$InConversion 19780298 / 44327227 1 / 18 org.apache.spark.sql.catalyst.analysis.Analyzer$ExtractGenerator 0 / 42312023 0 / 18 org.apache.spark.sql.catalyst.optimizer.ColumnPruning 17197393 / 39501424 1 / 6 ``` Closes #26589 from wangyum/SPARK-29947. Authored-by: Yuming Wang <[email protected]> Signed-off-by: Wenchen Fan <[email protected]>

andrewor14 reviewed Apr 2, 2014
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aarondav reviewed Apr 2, 2014
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pwendell reviewed Apr 5, 2014
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asfgit closed this in 1440154 Apr 7, 2014

rahij pushed a commit to rahij/spark that referenced this pull request Dec 5, 2017

Bump Hadoop to 2.9.0-palantir.3 (apache#288)

bb010b8

* Bump to Hadoop 2.9.0-palantir.3 * Update deps list

rahij added a commit to rahij/spark that referenced this pull request Dec 5, 2017

Revert "Bump Hadoop to 2.9.0-palantir.3 (apache#288)"

4b76670

This reverts commit bb010b8.

bzhaoopenstack pushed a commit to bzhaoopenstack/spark that referenced this pull request Sep 11, 2019

Fix multiple default security group conflicts issue (apache#288)

5cd49e5

SPARK-1154: Clean up app folders in worker nodes #288

SPARK-1154: Clean up app folders in worker nodes #288

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