Blockingly drain all events in LiveListenerBus#stop(). #251

concretevitamin · 2014-03-27T05:53:29Z

This PR attempts to implement the proposal discussed in #221.

Some notes:

Also, move bus.stop() call to the end of sc.stop(), so that slow
listeners would not affect the cleaning of other states.
LiveListenerBus.scala: newline changes from CRLF to LF.
Add a test to track the draining behavior. I've (1) used the patch to test my application mentioned in the old PR, and it worked as expected, and (2) run the new test without this patch, and it fails as expected.

@kayousterhout @pwendell @andrewor14: do you guys mind reviewing this?

Also, move bus.stop() call to the end of sc.stop(), so that slow listeners would not affect the cleaning of other states.

AmplabJenkins · 2014-03-27T06:13:45Z

Can one of the admins verify this patch?

kayousterhout · 2014-03-27T06:24:53Z

Jenkins, test this please

On Wed, Mar 26, 2014 at 11:13 PM, UCB AMPLab [email protected]:

Can one of the admins verify this patch?

Reply to this email directly or view it on GitHubhttps://github.com//pull/251#issuecomment-38772127
.

aarondav · 2014-03-27T06:34:35Z

This commit hopefully contains all the non-CRLF changes, for easier diffing: concretevitamin@a49dc74

concretevitamin · 2014-03-27T06:52:33Z

Hey Aaron,

That's correct -- I specifically made a CRLF-only commit. I believe git diff -w will work.

On Wed, Mar 26, 2014 at 11:34 PM, Aaron Davidson
[email protected]:

This commit hopefully contains all the non-CRLF changes, for easier
diffing: concretevitamin/spark@a49dc74concretevitamin@a49dc74

Reply to this email directly or view it on GitHubhttps://github.com//pull/251#issuecomment-38772966
.

concretevitamin · 2014-03-27T23:53:12Z

Jenkins not working?

On Wednesday, March 26, 2014, Zongheng Yang [email protected] wrote:

Hey Aaron,

That's correct -- I specifically made a CRLF-only commit. I believe git diff -w will work.

On Wed, Mar 26, 2014 at 11:34 PM, Aaron Davidson <[email protected]javascript:_e(%7B%7D,'cvml','[email protected]');

wrote:

This commit hopefully contains all the non-CRLF changes, for easier
diffing: concretevitamin/spark@a49dc74concretevitamin@a49dc74

Reply to this email directly or view it on GitHubhttps://github.com//pull/251#issuecomment-38772966
.

pwendell · 2014-03-28T05:26:12Z

Jenkins, test this please?

AmplabJenkins · 2014-03-28T05:27:24Z

Merged build triggered. Some tests failed or tests have not started running yet.

AmplabJenkins · 2014-03-28T05:27:32Z

Merged build started. Some tests failed or tests have not started running yet.

pwendell · 2014-03-28T05:41:12Z

core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala

@@ -72,6 +72,20 @@ class SparkListenerSuite extends FunSuite with LocalSparkContext with ShouldMatc
    }
  }

+  test("bus.stop() waits for the event queue to completely drain") {
+    val sleepyListener = new SleepyListener(1000)


Relying on sleeps like here is a little bit brittle and it also means this test will take 5 seconds which is along time. What about instead using a synchronization mechanism and create a BlockingListener that will just block inside of onJobEnded until it's signaled to continue.

Fixed; I use a Semaphore instead and create a BlockingListener as you suggested.

Also, the test now runs in ~200ms on my laptop.

pwendell · 2014-03-28T05:52:14Z

Hey I just looked at this. Why not just have stop call waitUntilEmpty(infinity) and be done with it? I don't see a big advantage of the current approach over that.

I can only think of two differences. One is that in the current approach is slightly more efficient - but I don't think that matters for this use case. Another is that the current approach blocks the addition of new events after stop has been called. But I think it's fine to just say that the semantics of events triggered after a stop are undefined.

AmplabJenkins · 2014-03-28T06:22:17Z

Merged build finished. All automated tests passed.

AmplabJenkins · 2014-03-28T06:22:17Z

All automated tests passed.
Refer to this link for build results: https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/13539/

concretevitamin · 2014-03-28T06:28:07Z

@pwendell yeah I think I used the current approach mainly because it should be more efficient than continuously sleeping and waking. The task at hand seems very well handled by a condition variable. Additionally, the current approach is not any more complicated?

As for your second point: I thought it's safe to treat SparkListenerShutdown (and hence stop()) as the special end-of-work / poison message, so I agree with the semantics you proposed.

I will update the test shortly.

pwendell · 2014-03-28T07:12:11Z

Hey @concretevitamin even though it might not be inherently more complicated, when we look at a patch like this it's a big win if it can use an existing well tested piece of code. So in this case there is a bias towards using the existing mechanism if it's possible.

andrewor14 · 2014-03-28T21:51:31Z

core/src/main/scala/org/apache/spark/scheduler/LiveListenerBus.scala

+      post(SparkListenerShutdown)
+      while (!drained) {
+        drainedLock.wait()
+      }


Can't you just check for eventQueue.isEmpty? This can get rid of the drained variable. Also, if you synchronize on an existing variable (e.g. eventQueue) then you don't even need drainedLock.

I used drained instead of checking isEmpty because I wasn't absolutely sure if it's (currently in the codebase or in the future) possible for new events to be posted after this stop method was called. If it is possible, then having isEmpty be true is not enough to imply that the end-of-work / shutdown signal has been reached, and that although we can enforce a semantics that ignores such events we can't really prevent them from popping up?

As for 2nd point: after a bit googling it seems synchronizing on a thread-safe queue can cause issues using the queue.

Hm yeah these are good points. It's just a little strange to equate the "event queue being drained" with "the shutdown event is received." These are not inherently the same things, but we're treating them so.

andrewor14 · 2014-03-28T22:03:09Z

To add to the existing discussion, I think the difference between the two proposed approaches is in the mechanism, not in the semantics. My only concern with busy waiting is that if the listener code does take forever to finish, then the SparkContext will hang, and in the mean time use up a lot of resources. Since multiple applications may run on the same cluster, this may end up being costly. (In the broader context, however, this case is relevant to like <0.1% of all Spark applications, so IDK how important this difference actually is).

andrewor14 · 2014-03-29T00:16:12Z

Though arguably if the application introduces an undying listener then it's the user's fault. On second thought I'm also inclined towards using the existing code, as this becomes a very simple 1-line code change.

To make it a little more efficient maybe we can make the Thread.sleep value a parameter of waitUntilEmpty, and use a higher value in stop than in the test suites.

pwendell · 2014-03-29T00:23:54Z

@andrewor14 Yep maybe we can bump this to 100 milliseconds to make it less inefficient. Waking/sleeping 10 times per second won't impose any measurable load on the system at all, so I'm not too worried about the busywait

concretevitamin · 2014-03-29T18:18:41Z

Hey @andrewor14 @pwendell -- so what I have been thinking and what Andrew pointed out correctly is, the event "the listener bus event queue is currently empty" and the event "the shutdown message has been received by the listener bus thread" are two different events. We want stop() to do the right thing which is to wait for the second event to happen. However, as far as I can tell waitUntilEmpty() only waits for the first event. In the current uses of waitUntilEmpty() in the unit tests, due to manual control of the events posted to the listener bus the two events happen to be the same thing.

In the general case, I think it's crucial that we distinguish these two. For instance it's probably possible that during the execution of a job the event queue becomes empty (for instance, the consumption of the events is faster than the posting of the events) -- but that doesn't mean a call to stop() at such a moment should succeed; rather we want the call to succeed whenever the end-of-work SparkListenerShutdown message is processed. This is where the condition variable comes in.

Let me know what you guys think ;)

pwendell · 2014-03-29T18:29:06Z

I don't understand what you are saying SparkListenerShutDown is a thing you invented for this pull request, right? I'm not suggesting that just calling waitUntilEmpty is identical to the SparkListenerShutDown approach. There are some differences. In particular if an event is posted after stop() is called it will just be ignored in my proposal. I'm fine with those semantics.

Could you describe a concrete problem with doing waitUntilEmpty inside of stop(). And define it in terms of the current code and not the code added here?

concretevitamin · 2014-03-29T18:39:28Z

Patrick: SparkListenerShutdown exists in the current code, not introduced by this patch.

pwendell · 2014-03-29T20:13:12Z

Oh I see now - I'm not sure the SparkListenerShutDown event is super necessary because it's the bus runs inside of a daemon thread. By definition a daemon thread doesn't need to be explicitly terminated.

concretevitamin · 2014-03-29T20:37:34Z

It was introduced by this commit: 2180c87

pwendell · 2014-03-30T00:23:15Z

In the mean time - can you fix the unit test?

andrewor14 · 2014-03-30T02:55:07Z

I think the only purpose of SparkListenerShutdown was to prevent the bus from arbitrarily processing events in case other parts of sc.stop() hang. This made sense back then when the bus was still a part of DAGScheduler; stopping the scheduler itself should also stop the thread that processes its events.

Now that the bus is a thing of its own, and we move listenerBus.stop() to the end of sc.stop(), I'm not sure if SparkListenerShutdown achieves anything, as the daemon thread should be stopped automatically.

…nstead).

concretevitamin · 2014-03-30T15:35:57Z

I have updated the test. Since bus.stop() would block until the listener is signaled to proceed, I used a new thread to call the stop method.

concretevitamin · 2014-04-01T05:30:35Z

Is this good to go? I can see the argument that SparkListenerShutdown is probably not doing anything now, but removing it should be in another PR. To stick with the current semantics it's more correct to treat the two events as different events?

…TimeMillis ## What changes were proposed in this pull request? Currently some test suites use "VACUUM ... RETAIN 0.0 HOURS". This tells vacuum to run with a horizon equal to the present time (0.0 hours = the current time). However, in the case of a NTP adjustment this will cause some tests to flake if the current time runs backwards: https://jenkins2.test.databricks.com/job/BazelUnitPRBuilder/107593/consoleFull One possible fix is to wrap the filesystem used in tests to use a truly monotonic clock (perhaps just System.currentTimeMillis wrapped to increase monotonically). There is already a helper function in DatabricksAtomicCommitProtocolSuite that can do this: private def makeFakeTimedFs(clock: Clock): FileSystem ## How was this patch tested? Ran unit tests. Author: Eric Liang <[email protected]> Closes apache#251 from ericl/sc-6047.

…a init-container (apache#251) * Download remotely-located resources on driver startup. Use init-container in executors. * FIx owner reference slightly * Clean up config * Don't rely too heavily on conventions that can change * Fix flaky test * Tidy up file resolver * Whitespace arrangement * Indentation change * Fix more indentation * Consolidate init container component providers * Minor method signature and comment changes * Rename class for consistency * Resolve conflicts * Fix flaky test * Add some tests and some refactoring. * Make naming consistent for Staged -> Submitted * Add unit test for the submission client. * Refine expectations * Rename variables and fix typos * Address more comments. Remove redundant SingleKeyConfigMap. * Minor test adjustments. * add another test * Fix conflicts.

The recent org.apache.orc:orc-mapreduce:1.4.0 addition introduced a conflict that we must resolve in the BOM

* removed base64 decoding logic * add cli unittests for jsonpayload

### What changes were proposed in this pull request? Push down filter through expand. For case below: ``` create table t1(pid int, uid int, sid int, dt date, suid int) using parquet; create table t2(pid int, vs int, uid int, csid int) using parquet; SELECT years, appversion, SUM(uusers) AS users FROM (SELECT Date_trunc('year', dt) AS years, CASE WHEN h.pid = 3 THEN 'iOS' WHEN h.pid = 4 THEN 'Android' ELSE 'Other' END AS viewport, h.vs AS appversion, Count(DISTINCT u.uid) AS uusers ,Count(DISTINCT u.suid) AS srcusers FROM t1 u join t2 h ON h.uid = u.uid GROUP BY 1, 2, 3) AS a WHERE viewport = 'iOS' GROUP BY 1, 2 ``` Plan. before this pr: ``` == Physical Plan == *(5) HashAggregate(keys=[years#30, appversion#32], functions=[sum(uusers#33L)]) +- Exchange hashpartitioning(years#30, appversion#32, 200), true, [id=#251] +- *(4) HashAggregate(keys=[years#30, appversion#32], functions=[partial_sum(uusers#33L)]) +- *(4) HashAggregate(keys=[date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12], functions=[count(if ((gid#44 = 1)) u.`uid`#47 else null)]) +- Exchange hashpartitioning(date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12, 200), true, [id=#246] +- *(3) HashAggregate(keys=[date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12], functions=[partial_count(if ((gid#44 = 1)) u.`uid`#47 else null)]) +- *(3) HashAggregate(keys=[date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12, u.`uid`#47, u.`suid`#48, gid#44], functions=[]) +- Exchange hashpartitioning(date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12, u.`uid`#47, u.`suid`#48, gid#44, 200), true, [id=#241] +- *(2) HashAggregate(keys=[date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12, u.`uid`#47, u.`suid`#48, gid#44], functions=[]) +- *(2) Filter (CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46 = iOS) +- *(2) Expand [ArrayBuffer(date_trunc(year, cast(dt#9 as timestamp), Some(Etc/GMT+7)), CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END, vs#12, uid#7, null, 1), ArrayBuffer(date_trunc(year, cast(dt#9 as timestamp), Some(Etc/GMT+7)), CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END, vs#12, null, suid#10, 2)], [date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12, u.`uid`#47, u.`suid`#48, gid#44] +- *(2) Project [uid#7, dt#9, suid#10, pid#11, vs#12] +- *(2) BroadcastHashJoin [uid#7], [uid#13], Inner, BuildRight :- *(2) Project [uid#7, dt#9, suid#10] : +- *(2) Filter isnotnull(uid#7) : +- *(2) ColumnarToRow : +- FileScan parquet default.t1[uid#7,dt#9,suid#10] Batched: true, DataFilters: [isnotnull(uid#7)], Format: Parquet, Location: InMemoryFileIndex[file:/root/spark-3.0.0-bin-hadoop3.2/spark-warehouse/t1], PartitionFilters: [], PushedFilters: [IsNotNull(uid)], ReadSchema: struct<uid:int,dt:date,suid:int> +- BroadcastExchange HashedRelationBroadcastMode(List(cast(input[2, int, true] as bigint))), [id=#233] +- *(1) Project [pid#11, vs#12, uid#13] +- *(1) Filter isnotnull(uid#13) +- *(1) ColumnarToRow +- FileScan parquet default.t2[pid#11,vs#12,uid#13] Batched: true, DataFilters: [isnotnull(uid#13)], Format: Parquet, Location: InMemoryFileIndex[file:/root/spark-3.0.0-bin-hadoop3.2/spark-warehouse/t2], PartitionFilters: [], PushedFilters: [IsNotNull(uid)], ReadSchema: struct<pid:int,vs:int,uid:int> ``` Plan. after. this pr. : ``` == Physical Plan == AdaptiveSparkPlan isFinalPlan=false +- HashAggregate(keys=[years#0, appversion#2], functions=[sum(uusers#3L)], output=[years#0, appversion#2, users#5L]) +- Exchange hashpartitioning(years#0, appversion#2, 5), true, [id=#71] +- HashAggregate(keys=[years#0, appversion#2], functions=[partial_sum(uusers#3L)], output=[years#0, appversion#2, sum#22L]) +- HashAggregate(keys=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12], functions=[count(distinct uid#7)], output=[years#0, appversion#2, uusers#3L]) +- Exchange hashpartitioning(date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, 5), true, [id=#67] +- HashAggregate(keys=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12], functions=[partial_count(distinct uid#7)], output=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, count#27L]) +- HashAggregate(keys=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, uid#7], functions=[], output=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, uid#7]) +- Exchange hashpartitioning(date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, uid#7, 5), true, [id=#63] +- HashAggregate(keys=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles)) AS date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END AS CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, uid#7], functions=[], output=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, uid#7]) +- Project [uid#7, dt#9, pid#11, vs#12] +- BroadcastHashJoin [uid#7], [uid#13], Inner, BuildRight, false :- Filter isnotnull(uid#7) : +- FileScan parquet default.t1[uid#7,dt#9] Batched: true, DataFilters: [isnotnull(uid#7)], Format: Parquet, Location: InMemoryFileIndex[file:/private/var/folders/4l/7_c5c97s1_gb0d9_d6shygx00000gn/T/warehouse-c069d87..., PartitionFilters: [], PushedFilters: [IsNotNull(uid)], ReadSchema: struct<uid:int,dt:date> +- BroadcastExchange HashedRelationBroadcastMode(List(cast(input[2, int, false] as bigint)),false), [id=#58] +- Filter ((CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END = iOS) AND isnotnull(uid#13)) +- FileScan parquet default.t2[pid#11,vs#12,uid#13] Batched: true, DataFilters: [(CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END = iOS), isnotnull..., Format: Parquet, Location: InMemoryFileIndex[file:/private/var/folders/4l/7_c5c97s1_gb0d9_d6shygx00000gn/T/warehouse-c069d87..., PartitionFilters: [], PushedFilters: [IsNotNull(uid)], ReadSchema: struct<pid:int,vs:int,uid:int> ``` ### Why are the changes needed? Improve performance, filter more data. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? Added UT Closes #30278 from AngersZhuuuu/SPARK-33302. Authored-by: angerszhu <[email protected]> Signed-off-by: Wenchen Fan <[email protected]>

…conf.tem…" (apache#252) * Revert "[MAPR-SPARK-176] Fix Spark Project Catalyst unit tests (apache#251)" This reverts commit 5de05075cd14abf8ac65046a57a5d76617818fbe. * Revert "[MAPR-SPARK-210] Rename sprk-defaults.conf to spark-defaults.conf.template (apache#249)" This reverts commit 1baa677d727e89db7c605ffbae9a9eba00337ad0.

…cript K8S-1077 (apache#598) * K8S-1077 - use single k8s secret with user info MapR [SPARK-651] Replacing joda-time-*.jar with joda-time-2.10.3.jar. MapR [SPARK-638] Wrong permissions when creating files under directory with GID bit set. MapR [SPARK-627] SparkHistoryServer-2.4 is getting 403 Unauthorized home page for users(spark.ui.view.acls) via spark-submit MapR [SPARK-639] Default headers are adding two times MapR [SPARK-629] Spark UI for job lose CSS styles MapR [MS-925] After upgrade to MEP 6.2 (Spark 2.4.0) can no longer consume Kafka / MapR Streams. MapR [SPARK-626] Update kafka dependencies for Spark 2.4.4.0 in release MEP-6.3.0 MapR [SPARK-340] Jetty web server version at Spark should be updated tp v9.4.X MapR [SPARK-617] an't use ssl via spark beeline MapR [SPARK-617] Can't use ssl via spark beeline MapR [SPARK-620] Replace core dependency in Spark-2.4.4 MapR [SPARK-621] Fix multiple XML configuration initialization for (apache#575) custom headers. Use X-XSS-Protection, X-Content-Type-Options Content-Security-Policy and Strict-Transport-Security configuration only in case: cluster security is enabled OR spark.ui.security.headers.enabled set to true. MapR [SPARK-595] Spark cannot access hs2 through zookeeper Revert "MapR [SPARK-595] Spark cannot access hs2 through zookeeper (apache#577)" MapR [SPARK-595] Spark cannot access hs2 through zookeeper MapR [SPARK-620] Replace core dependency in Spark-2.4. MapR [SPARK-619] Move absent commits from 2.4.3 branch to 2.4.4 (apache#574) * Adding SQL API to write to kafka from Spark (apache#567) * Branch 2.4.3 extended kafka and examples (apache#569) * The v2 API is in its own package - the v2 api is in a different package - the old functionality is available in a separated package * v2 API examples - All the examples are using the newest API. - I have removed the old examples since they are not relevant any more and the same functionality is shown in the new examples usin the new API. * MapR [SPARK-619] Move absent commits from 2.4.3 branch to 2.4.4 CORE-321. Add custom http header support for jetty. MapR [SPARK-609] Port Apache Spark-2.4.4 changes to the MapR Spark-2.4.4 branch Adding multi table loader (apache#560) * Adding multi table loader - This allows us to load multiple matching tables into one Union DataFrame. If we have the fallowing MFS structure: ``` /clients/client_1/data.table /clients/client_2/data.table ``` we can load a union dataframe by doing `loadFromMapRDB("/clients/*/*.table")` * Fixing the path to the reader MapR [SPARK-588] Spark thriftserver fails when work with hive-maprdb json table MapR [SPARK-598] Spark can't add needed properties to hive-site.xml MAPR-SPARK-596: Change HBase compatible version for Spark 2.4.3 MapR [SPARK-592] Add possibility to use start-thriftserver.sh script with 2304 port MapR [SPARK-584] MaprDB connector's setHintUsingIndex method doesn't work as expected MapR [SPARK-583] MaprDB connector's loadFromMaprDB function for Java API doesn't work as expected SPARK-579 info about ssl_trustore is added for metrics MapR [SPARK-552] Failed to get broadcast_11_piece0 of broadcast_11 SPARK-569 Generation of SSL ceritificates for spark UI MapR [SPARK-575] Warning messages in spark workspace after the second attempt to login to job's UI Update zookeeper version Adding `joinWithMapRDBTable` function (apache#529) The related documentation of this function is here https://github.com/anicolaspp/MapRDBConnector#joinwithmaprdbtable. The main idea is that having a dataframe (no matter how was it constructed) we can join it with a MapR-DB table. This functions looks at the join query and load only those records from MapR-DB that will join instead of loading the full table and then join in memory. In other words, we only load what we know will be joint. Adding DataSource Reader Support (apache#525) * Adding DataSource Reader Support * Update SparkSessionExt.scala * creating a package object * Update MapRDBSpark.scala * fully path to avoid name collition * refactorings MapR [SPARK-451] Spark hadoop/core dependency updates MapR [SPARK-566] Move absent commits from 2.4.0 branch MapR [SPARK-561] Spark 2.4.3 porting to MapR MapR [SPARK-561] Spark 2.4.3 porting to MapR MapR [SPARK-558] Render application UI init page if driver is not up MapR [SPARK-541] Avoid duplication of the first unexpired record MapR [COLD-150][K8S] Fix metrics copy MapR [K8S-893] Hide plain text password from logs MapR [SPARK-540] Include 'avro' artifacts MapR [SPARK-536] PySpark streaming package for kafka-0-10 added K8S-853: Enable spark metrics for external tenant MapR [SPARK-531] Remove duplicating entries from classpath in ClasspathFilter MapR [SPARK-516] Spark jobs failure using yarn mode on kerberos fixed MapR [SPARK-462] Spark and SparkHistoryServer allow week ciphers, which can allow man in the middle attack [SPARK-508] MapR-DB OJAI Connector for Spark isNull condition returns incorrect result MapR [SPARK-510] nonmapr "admin" users not able to view other user logs in SHS SPARK-460: Spark Metrics for CollectD Configuration for collecting Spark metrics SPARK-463 MAPR_MAVEN_REPO variable for specifying mapR repository MapR [SPARK-492] Spark 2.4.0.0 configure.sh has error messages MapR [SPARK-515][K8S] Remove configure.sh call for k8s MapR [SPARK-515] Move configuring spark-env.sh back to the private-pkg MapR [SPARK-515] Move configuring spark-env.sh back to the private-pkg MapR [SPARK-514] Recovery from checkpoint is broken MapR [SPARK-445] Messages loss fixed by reverting [MAPR-32290] changes from kafka09 package (apache#460) * MapR [SPARK-445] Revert "[MAPR-32290] Spark processing offsets when messages are already TTL in the first batch (apache#376)" This reverts commit e8d59b9. * MapR [SPARK-445] Revert "[MAPR-32290] Spark processing offsets when messages are already ttl in first batch (apache#368)" This reverts commit b282a8b. MapR [SPARK-445] Messages loss fixed by reverting [MAPR-32290] changes from kafka10 package MapR [SPARK-469] Fix NPE in generated classes by reverting "[SPARK-23466][SQL] Remove redundant null checks in generated Java code by GenerateUnsafeProjection" (apache#455) This reverts commit c5583fd. MapR [SPARK-482] Spark streaming app fails to start by UnknownTopicOrPartitionException with checkpoint MapR [SPARK-496] Spark HS UI doesn't work MapR [SPARK-416] CVE-2018-1320 vulnerability in Apache Thrift MapR [SPARK-486][K8S] Fix sasl encryption error on Kubernetes MapR [SPARK-481] Cannot run spark configure.sh on Client node MapR [K8S-637][K8S] Add configure.sh configuration in spark-defaults.conf for job runtime MapR [SPARK-465] Error messages after update of spark 2.4 MapR [SPARK-465] Error messages after update of spark 2.4 MapR [SPARK-464] Can't submit spark 2.4 jobs from mapr-client [SPARK-466] SparkR errors fixed MapR [SPARK-456] Spark shell can't be started SPARK-417 impersonation fixes for spark executor. Impersonation is mo… (apache#433) * SPARK-417 impersonation fixes for spark executor. Impersonation is moved from HadoopRDD.compute() method to org.apache.spark.executor.Executor.run() method * SPARK-363 Hive version changed to '1.2.0-mapr-spark-MEP-6.0.0' [SPARK-449] Kafka offset commit issue fixed MapR [SPARK-287] Move logic of creating /apps/spark folder from installer's scripts to the configure.sh MapR [SPARK-221] Investigate possibility to move creating of the spark-env.sh from private-pkg to configure.sh MapR [SPARK-430] PID files should be under /opt/mapr/pid MapR [SPARK-446] Spark configure.sh doesn't start/stop Spark services MapR [SPARK-434] Move absent commits from 2.3.2 branch (apache#425) * MapR [SPARK-352] Spark shell fails with "NoClassDefFoundError: org/apache/hadoop/fs/FSDataInputStream" if java is not available in PATH * MapR [SPARK-350] Deprecate Spark Kafka-09 package * MapR [SPARK-326] Investigate possibility of writing Java example for the MapRDB OJAI connector * [SPARK-356] Merge mapr changes from kafka-09 package into the kafka-10 * SPARK-319 Fix for sparkR version check * MapR [SPARK-349] Update OJAI client to v3 for Spark MapR-DB JSON connector * MapR [SPARK-367] Move absent commits from 2.3.1 branch * MapR [SPARK-137] Analyze the warning during compilation of OJAI connector * MapR [SPARK-369] Spark 2.3.2 fails with error related to zookeeper * [MAPR-26258] hbasecontext.HBaseDistributedScanExample fails * [SPARK-24355] Spark external shuffle server improvement to better handle block fetch requests * MapR [SPARK-374] Spark Hive example fails when we submit job from another(simple) cluster user * MapR [SPARK-434] Move absent commits from 2.3.2 branch * MapR [SPARK-434] Move absent commits from 2.3.2 branch * MapR [SPARK-373] Unexpected behavior during job running in standalone cluster mode * MapR [SPARK-419] Update hive-maprdb-json-handler jar for spark 2.3.2.0 and spark 2.2.1 * MapR [SPARK-396] Interface change of sendToKafka * MapR [SPARK-357] consumer groups are prepeneded with a "service_" prefix * MapR [SPARK-429] Changes in maprdb connector are the cause of broken backward compatibility * MapR [SPARK-427] Update kafka in Spark-2.4.0 to the 1.1.1-mapr * MapR [SPARK-434] Move absent commits from 2.3.2 branch * Move absent commits from 2.3.2 branch * MapR [SPARK-434] Move absent commits from 2.3.2 branch * Move absent commits from 2.3.2 branch * Move absent commits from 2.3.2 branch MapR [SPARK-427] Update kafka in Spark-2.4.0 to the 1.1.1-mapr MapR [SPARK-379] Spark 2.4 4-gidit version MapR [PIC-48][K8S] Port k8s changes to 2.4.0 [PIC-48] Create user for k8s driver and executor if required [PIC-48] Create user for k8s driver and executor if required Revert "Remove spark.ui.filters property" This reverts commit d8941ba36c3451cdce15d18d6c1a52991de3b971. [SPARK-351] Copy kubernetes start scripts anyway PIC-34: Rename default configmap name to be consistent with mapr-kubernetes [SPARK-23668][K8S] Add config option for passing through k8s Pod.spec.imagePullSecrets (apache#355) Pass through the `imagePullSecrets` option to the k8s pod in order to allow user to access private image registries. See https://kubernetes.io/docs/tasks/configure-pod-container/pull-image-private-registry/ Unit tests + manual testing. Manual testing procedure: 1. Have private image registry. 2. Spark-submit application with no `spark.kubernetes.imagePullSecret` set. Do `kubectl describe pod ...`. See the error message: ``` Error syncing pod, skipping: failed to "StartContainer" for "spark-kubernetes-driver" with ErrImagePull: "rpc error: code = 2 desc = Error: Status 400 trying to pull repository ...: \"{\\n \\\"errors\\\" : [ {\\n \\\"status\\\" : 400,\\n \\\"message\\\" : \\\"Unsupported docker v1 repository request for '...'\\\"\\n } ]\\n}\"" ``` 3. Create secret `kubectl create secret docker-registry ...` 4. Spark-submit with `spark.kubernetes.imagePullSecret` set to the new secret. See that deployment was successful. Author: Andrew Korzhuev <[email protected]> Author: Andrew Korzhuev <[email protected]> Closes apache#20811 from andrusha/spark-23668-image-pull-secrets. [SPARK-321] Change default value of spark.mapr.ssl.secret.prefix property [PIC-32] Spark on k8s with MapR secure cluster Update entrypoint.sh with correct spark version (apache#340) This PR has minor fix to correct the spark version string [SPARK-274] Create home directory for user who submitted job [MAPR-SPARK-230] Implement security for Spark on Kubernetes Run Spark job with specify the username for driver and executor Read cluster configs from configMap Run configure.sh script form entrypoint.sh Remove spark.kubernetes.driver.pod.commands property Add Spark properties for executor and driver environment variable MapR [SPARK-296] Structured Streaming memory leak Revert "[MAPR-SPARK-210] Rename sprk-defaults.conf to spark-defaults.conf.tem…" (apache#252) * Revert "[MAPR-SPARK-176] Fix Spark Project Catalyst unit tests (apache#251)" This reverts commit 5de05075cd14abf8ac65046a57a5d76617818fbe. * Revert "[MAPR-SPARK-210] Rename sprk-defaults.conf to spark-defaults.conf.template (apache#249)" This reverts commit 1baa677d727e89db7c605ffbae9a9eba00337ad0. [MAPR-SPARK-210] Rename sprk-defaults.conf to spark-defaults.conf.template MapR [SPARK-379] Port Spark to 2.4.0 MapR [SPARK-341] Spark 2.3.2 porting [MAPR-32290] Spark processing offsets when messages are already TTL in the first batch * Bug 32263 - Seek called on unsubscribed partitions [MSPARK-331] Remove snapshot versions of mapr dependencies from Spark-2.3.1 [MAPR-32290] Spark processing offsets when messages are already ttl in first batch MapR [SPARK-325] Add examples for work with the MapRDB JSON connector into the Spark project [ATS-449] Unit test for EBF 32013 created. MAPR-SPARK-311: Spark beeline uses default ssl truststore instead of mapr ssl truststore Bug 32355 - Executor tab empty on Spark UI [SPARK-318] Submitting Spark jobs from Oozie fails due to ClassNotFoundException Bug 32014 - Spark Consumer fails with java.lang.AssertionError Revert "[SPARK-306] Kafka clients 1.0.1 present in jars directory for Spark 2.3.1" (apache#341) * Revert "[SPARK-306] Kafka clients 1.0.1 present in jars directory for Spark 2.3.1 (apache#335)" This reverts commit 832411e. Bug 32014 - Spark Consumer fails with java.lang.AssertionError (apache#326) (apache#336) * MapR [32014] Spark Consumer fails with java.lang.AssertionError [SPARK-306] Kafka clients 1.0.1 present in jars directory for Spark 2.3.1 DEVOPS-2768 temporarily removed curl for file downloading [SPARK-302] Local privilege escalation MapR [SPARK-297] Added unit test for empty value conversion MapR [SPARK-297] Empty values are loaded as non-null MapR [SPARK-296] Structured Streaming memory leak 2.3.1 spark 289 (apache#318) * MapR [SPARK-289] Fix unit test for Spark-2.3.1 [SPARK-130] MapRDB connector - NPE while saving Pair RDD with 'null' values MapR [SPARK-283] Unit tests fail during initialization SSL properties. [SPARK-212] SparkHiveExample fails when we run it twice MapR [SPARK-282] Remove maprfs and hadoop jars from mapr spark package MapR [SPARK-278] Spark submit fails for jobs with python MapR [SPARK-279] Can't connect to spark thrift server with new spark and hive packages MapR [SPARK-276] Update zookeeper dependency to v.3.4.11 for spark 2.3.1 MapR [SPARK-272] Use only client passwords from ssl-client.xml MapR [SPARK-266] Spark jobs can't finish correctly, when there is an error during job running MapR [SPARK-263] Add possibility to use keyPassword which is different from keyStorePassword [MSPARK-31632] RM UI showing broken page for Spark jobs MapR [SPARK-261] Use mapr-security-web for getting passwords. MapR [SPARK-259] Spark application doesn't finish correctly MapR [SPARK-268] Update Spark version for Warden change project version to 2.3.1-mapr-SNAPSHOT MapR [SPARK-256] Spark doesn't work on yarn mode MapR [SPARK-255] Installer fresh install 610/600 secure fails to start "mapr-spark-thriftserver", "mapr-spark-historyserver" Mapr [SPARK-248] MapRDBTableScanRDD fails to convert to Scala Dataframe when using where clause MapR [SPARK-225] Hadoop credentials provider usage for hiding passwords at spark-defaults MapR [SPARK-214] Hive-2.1 poperties can't be read from a hive-site.xml as Spark uses Hive-1.2 MapR [SPARK-216] Spark thriftserver fails when work with hive-maprdb json table SPARK-244 (apache#278) Provide ability to use MapR-Negotiation authentication for Spark HistoryServer MapR [SPARK-226] Spark - pySpark Security Vulnerability MapR [SPARK-220] SparkR fails with UDF functions bug fixed MapR [SPARK-227] KafkaUtils.createDirectStream fails with kafka-09 MapR [SPARK-183] Spark Integration for Kafka 0.10 unit tests disabled MapR [SPARK-182] Spark Project External Kafka Producer v09 unit tests fixed MapR [SPARK-179] Spark Integration for Kafka 0.9 unit tests fixed MapR [SPARK-181] Kafka 0.10 Structured Streaming unit tests fixed [MSPARK-31305] Spark History server NOT loading applications submitted by users other than 'mapr' MapR [SPARK-175] Fix Spark Project Streaming unit tests [MAPR-SPARK-176] Fix Spark Project Catalyst unit tests [MAPR-SPARK-178] Fix Spark Project Hive unit tests MapR [SPARK-174] Spark Core unit tests fixed Changed version for spark-kafka connector. MapR [SPARK-202] Update MapR Spark to 2.3.0 Fixed compile time errors in tests Change project version [SPARK-198] Update hadoop dependency version to 2.7.0-mapr-1803 for Spark 2.2.1 MapR [SPARK-188] Couldn't connect to thrift server via spark beeline on kerberos cluster MapR [SPARK-143] Spark History Server does not require login for secured-by-default clusters MapR [SPARK-186] Update OJAI versions to the latest for Spark-2.2.1 OJAI Connector MapR [SPARK-191] Incorrect work of MapR-DB Sink 'complete' and 'update' modes fixed MapR [SPARK-170] StackOverflowException in equals method in DBMapValue 2.2.1 build fixed (apache#231) * MapR [SPARK-164] Update Kafka version to 1.0.1-mapr in Spark Kafka Producer module MapR [SPARK-161] Include Kafka Structured streaming jar to Spark package. MapR [SPARK-155] Change Spark Master port from 8080 MapR [SPARK-153] Exception in spark job with configured labels on yarn-client mode MapR [SPARK-152] Incorrect date string parsing fixed MapR [SPARK-21] Structured Streaming MapR-DB Sink created MapR [SPARK-135] Spark 2.2 with MapR Streams ( Kafka 1.0) (apache#218) * MapR [SPARK-135] Spark 2.2 with MapR Streams (Kafka 1.0) Added functionality of MapR-Streams specific EOF handling. MapR [SPARK-143] Spark History Server does not require login for secured-by-default clusters Disable build failing if scalastyle checking is fall. MapR [SPARK-16] Change Spark version in Warden files and configure.sh MapR [SPARK-144] Add insertToMapRDB method for rdd for Java API [MAPR-30536] Spark SQL queries on Map column fails after upgrade MapR [SPARK-139] Remove "update" related APIs from connector MapR [SPARK-140] Change the option name "tableName" to "tablePath" in the Spark/MapR-DB connectors. MapR [SPARK-121] Spark OJAI JAVA: update functionality removed MapR [SPARK-118] Spark OJAI Python: missed DataFrame import while moving imports in order to fix MapR [ZEP-101] interpreter issue MapR [SPARK-118] Spark OJAI Python: move MapR DB Connector class importing in order to fix MapR [ZEP-101] interpreter issue MapR [SPARK-117] Spark OJAI Python: Save functionality implementation MapR [SPARK-131] Exception when try to save JSON table with Binary _id field Spark OJAI JAVA: load to RDD, save from RDD implementation (apache#195) * MapR [SPARK-124] Loading to JavaRDD implemented * MapR [SPARK-124] MapRDBJavaSparkContext constructor changed * MapR [SPARK-124] implemented RDD[Row] saving MapR [SPARK-118] Spark OJAI Python: Read implementation MapR [SPARK-128] MapRDB connector - wrong handle of null fields when nullable is false * MapR [SPARK-121] Spark OJAI JAVA: Read to Dataset functionality implementation * Minor refactoring MapR [SPARK-125] Default value of idFieldPath parameter is not handle MapR [SPARK-113] Hit java.lang.UnsupportedOperationException: empty.reduceLeft during loadFromMapRDB Spark Mapr-DB connector was refactored according to Scala style Removed code duplication [MSPARK-107]idField information is lost in MapRDBDataFrameWriterFunctions.saveToMapRDB configure.sh takes options to change ports Kafka client excluded from package because correct version is located in "mapr classpath" Changed Kafka version in Kafka producer module. Branch spark 69 (apache#170) * Fixing the wrong type casting of TimeStamp to OTimeStamp when read from spark dataFrame. * SPARK-69: Problem with license when we try to read from json and write to maprdb remove creatin /usr/local/spark link from configure.sh. This link will be creates by private-pkg remove include-maprdb from default profiles added profiles in maprdb pom file instead of two pom files Fixed maprdb connector dependencies. Fixing the wrong type casting of TimeStamp to OTimeStamp when read from spark dataFrame. changed port for spark-thriftserver as it conflicts with hive server changed port for spark-thriftserver as it conflicts with hive server remove .not_configured_yet file after success Ojai connector fixed required java version [MSPARK-45] Move Spark-OJAI connector code to Spark github repo (apache#132) * SPARK-45 Move Spark-OJAI connector code to Spark github repo * Fixing pom versions for maprdb spark connector. * Changes made to the connector code to be compatible with 5.2.* and 6.0 clients. Spark 2.1.0 mapr 29106 (apache#150) * [SPARK-20922][CORE] Add whitelist of classes that can be deserialized by the launcher. Blindly deserializing classes using Java serialization opens the code up to issues in other libraries, since just deserializing data from a stream may end up execution code (think readObject()). Since the launcher protocol is pretty self-contained, there's just a handful of classes it legitimately needs to deserialize, and they're in just two packages, so add a filter that throws errors if classes from any other package show up in the stream. This also maintains backwards compatibility (the updated launcher code can still communicate with the backend code in older Spark releases). Tested with new and existing unit tests. Author: Marcelo Vanzin <[email protected]> Closes apache#18166 from vanzin/SPARK-20922. (cherry picked from commit 8efc6e9) Signed-off-by: Marcelo Vanzin <[email protected]> (cherry picked from commit 772a9b9) * [SPARK-20922][CORE][HOTFIX] Don't use Java 8 lambdas in older branches. Author: Marcelo Vanzin <[email protected]> Closes apache#18178 from vanzin/SPARK-20922-hotfix. Added security by default for historyserver use waitForConsumerAssignment() instead of consumer.poll(0) for spark-29052 change MAPR_HADOOP_CLASSPATH in configure.sh for creating it by mapr-classpath.sh change MAPR_HADOOP_CLASSPATH in configure.sh for creating it by mapr-classpath.sh changes for mapr-classpath.sh changes for mapr-classpath.sh configure.sh changes [SPARK-39] Classpath filter was added Fixed impersonation when data read from MapR-DB via Spark-Hive. added configure.sh and warden.spark-thriftserver.conf hive-hbase-handler added to Spark jars Fixed "Single message comes late" 28339 bug fixed Spark streaming skipped message with zero offset from Kafka 0.9 [MSPARK-9] Initial fix for Spark unit tests Bump dependencies after ECO-1703 release [SPARK-33] Streaming example fixed [MAPR-26060] Fixed case when mapr-streams make gaps in offsets ported features from kafka 10 to kafka 9 [MAPR-26289][SPARK-2.1] Streaming general improvements (apache#93) * Added include-kafka-09 profile to Assembly * Set default poll timeout to 120s Set default HBase verison to 1.1.8 Changes from Kafka10 package were ported to Kafka09 package. [MAPR-26053] Include MapR Classes to the default value of spark.sql.hive.metastore.sharedPrefixes [MAPR-25807] Spark-Warehouse path computes incorrectly Add MapR-SASL support for Thrift Server Adding scala library. [MAPR-25713] Spark might try to load MapR Class Loader multiple times and fail [MAPR-25311] Bump Spark dependencies after ECO-1611 release [MINOR] Fix spark-jars.sh script [MAPR-24603] Could not launch beeline shell after starting spark thrift server fixed syntax error in V09DirectKafkaWordCount example Spark 2.0.1 MAPR-streams Python API [MAPR-24415] SPARK_JAVA_OPTS is deprecated Kafka streaming producer added. Minor fix for previous commit Added script for MAPR-24374 Some minor changes to spark-defaults.conf Changed default HBase version to 1.1.1 in compatibility.version Streaming example was refactored [MAPR-24470] HiveFromSpark test fails in yarn-cluster mode Added MapR Repo [MAPR-22940] Failed to connect spark beeline (after spark thrift server is started) on Kerberos cluster [MAPR-18865] Unable to submit spark apps from Windows client Skip maven clean task on the parent module New: Issue with running Hive commands in Spark This is fixed in SPARK-7819 Isolated Hive Client Loader appears to cause Native Library libMapRClient.4.0.2-mapr.so already loaded in another classloader error Spark warden.services.conf should have dependency on cldb Remove DFS shuffle settings. These settings are not used right now. Copy every file in the conf directory into the distribution package. Create spark-defaults.conf for MapR Settings to enable DFS shuffle on MapR. Support hbase classpath computation in util script. Adding external conf and scripts. Enable SPARK_HIVE mode while building. This is needed to bundle datanucleus jars needed for hive table creation. Build Spark on MapR. - make-distribution.sh takes an environment variable to enable profiles - MVN_PROFILE_ARG - Added warden conf files under ext-conf. - Updated pom.xml to use right set of jars and version. Spark Master failed to start in HA mode Updated Apache Curator version Added spark streaming integration with kafka 0.9 and mapr-streams Added MapR Repo

concretevitamin added 2 commits March 26, 2014 22:46

Blockingly drain all events in LiveListenerBus#stop().

a49dc74

Also, move bus.stop() call to the end of sc.stop(), so that slow listeners would not affect the cleaning of other states.

LiveListenerBus.scala: newline changes from CRLF to LF.

36bcc4b

pwendell reviewed Mar 28, 2014
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andrewor14 reviewed Mar 28, 2014
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Add isDrained() and fix listener bus stop() test (rely on semaphore i…

0dc8e51

…nstead).

Minor comment fix.

8f65949

andrewor14 mentioned this pull request Apr 1, 2014

Add support to both explicitly and automatically clean-up broadcast tdas/spark#1

Merged

andrewor14 mentioned this pull request Apr 9, 2014

SPARK-1407 drain event queue before stopping event logger #366

Closed

concretevitamin closed this Jun 7, 2014

concretevitamin deleted the listenerbus branch June 7, 2014 06:50

mccheah pushed a commit to mccheah/spark that referenced this pull request Oct 12, 2017

Add version for hadoop-mapreduce-client-core to the BOM (apache#251)

0d4903d

The recent org.apache.orc:orc-mapreduce:1.4.0 addition introduced a conflict that we must resolve in the BOM

Igosuki pushed a commit to Adikteev/spark that referenced this pull request Jul 31, 2018

[SPARK-573] removed base64 decoding logic (apache#251)

0bb1705

* removed base64 decoding logic * add cli unittests for jsonpayload

arjunshroff pushed a commit to arjunshroff/spark that referenced this pull request Nov 24, 2020

[MAPR-SPARK-176] Fix Spark Project Catalyst unit tests (apache#251)

1678c60

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Blockingly drain all events in LiveListenerBus#stop(). #251

Blockingly drain all events in LiveListenerBus#stop(). #251

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Blockingly drain all events in LiveListenerBus#stop(). #251

Blockingly drain all events in LiveListenerBus#stop(). #251

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