SPARK-1330 removed extra echo from comput_classpath.sh #241
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@marmbrus do you know what should happen during the sbt assembly? |
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Merged build triggered. |
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Merged build started. |
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The full patch for the assembly issue is here: #237 It includes this change (but just outputs to stderr instead), but I think we should go ahead and merge this since the other one may be a couple more iterations until being merged. |
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Merged build finished. |
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All automated tests passed. |
| @@ -36,7 +36,6 @@ CLASSPATH="$SPARK_CLASSPATH:$FWDIR/conf" | |||
| # Hopefully we will find a way to avoid uber-jars entirely and deploy only the needed packages in | |||
| # the future. | |||
| if [ -f "$FWDIR"/sql/hive/target/scala-$SCALA_VERSION/spark-hive-assembly-*.jar ]; then | |||
| echo "Hive assembly found, including hive support. If this isn't desired run sbt hive/clean." | |||
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Would it make sense to send this to stderr?
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Yup, LGTM
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I committed this. |
jhartlaub
referenced
this pull request
in jhartlaub/spark
May 27, 2014
Fix race condition in JobLoggerSuite [0.8 branch] I found this when running the tests locally. It's similar to a race condition found when making the 0.8.0 release.
jhartlaub
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in jhartlaub/spark
May 27, 2014
Update broken links and add HDP 2.0 version string I ran a link checker on the UI and found several broken links. (cherry picked from commit 1f4a4bc) Signed-off-by: Patrick Wendell <pwendell@gmail.com>
pdeyhim
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Jun 25, 2014
remove the extra echo which prevents spark-class from working. Note that I did not update the comment above it, which is also wrong because I'm not sure what it should do. Should hive only be included if explicitly built with sbt hive/assembly or should sbt assembly build it? Author: Thomas Graves <tgraves@apache.org> Closes apache#241 from tgravescs/SPARK-1330 and squashes the following commits: b10d708 [Thomas Graves] SPARK-1330 removed extra echo from comput_classpath.sh
liancheng
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Mar 17, 2017
## What changes were proposed in this pull request? This is a backport of apache@31da755 In current Spark we could add customized SparkListener through `SparkContext#addListener` API, but there's no equivalent API to remove the registered one. In our scenario SparkListener will be added repeatedly accordingly to the changed environment. If lacks the ability to remove listeners, there might be many registered listeners finally, this is unnecessary and potentially affects the performance. So here propose to add an API to remove registered listener. ## How was this patch tested? Add an unit test to verify it. Author: jerryshao <sshao@hortonworks.com> Closes apache#241 from ala/remove-spark-listener.
erikerlandson
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May 8, 2017
erikerlandson
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Jul 28, 2017
ash211
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Jul 31, 2017
Would use 2.6.7 everywhere but upstream released a 2.6.7.1 for jackson-databind but not a corresponding 2.6.7 for the rest of jackson, so those remain on 2.6.7 This requires splitting the version variable in /pom.xml
mccheah
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Oct 12, 2017
Would use 2.6.7 everywhere but upstream released a 2.6.7.1 for jackson-databind but not a corresponding 2.6.7 for the rest of jackson, so those remain on 2.6.7 This requires splitting the version variable in /pom.xml
Igosuki
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Jul 31, 2018
…pache#241) * working on new spam/ham example * basic NB model builder * messy, but have end-to-end model server working * add jobs README, re-arrange spam classifier * add documentation to scala jobs * added secrets docs * added secure TeraSort walkthrough * wip, run ci, add keytabs to executors also * fix executorenv property string * add flag for sasl secret * finished ml pipeline walkthrough * don't test on the training data * added code explanation * addressed comments, updated test_rpc_auth test * add link to walkthroughs * addressed documentation comments * addressed comments in SpamHam.scala example * added unit test for sasl secret
bzhaoopenstack
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Sep 11, 2019
Add install-k8s role
cloud-fan
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### 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 <angers.zhu@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
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remove the extra echo which prevents spark-class from working. Note that I did not update the comment above it, which is also wrong because I'm not sure what it should do.
Should hive only be included if explicitly built with sbt hive/assembly or should sbt assembly build it?