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…n operator metrics ## What changes were proposed in this pull request? This patch adds explicit metadata operation timing and number of files in data source metrics. Those would be useful to include for performance profiling. Screenshot of a UI with this change (num files and metadata time are new metrics): <img width="321" alt="screen shot 2017-03-29 at 12 29 28 am" src="https://cloud.githubusercontent.com/assets/323388/24443272/d4ea58c0-1416-11e7-8940-ecb69375554a.png"> ## How was this patch tested? N/A Author: Reynold Xin <rxin@databricks.com> Closes #17465 from rxin/SPARK-20136.
… task commit messages ## What changes were proposed in this pull request? The internal FileCommitProtocol interface returns all task commit messages in bulk to the implementation when a job finishes. However, it is sometimes useful to access those messages before the job completes, so that the driver gets incremental progress updates before the job finishes. This adds an `onTaskCommit` listener to the internal api. ## How was this patch tested? Unit tests. cc rxin Author: Eric Liang <ekl@databricks.com> Closes #17475 from ericl/file-commit-api-ext.
## What changes were proposed in this pull request? There are two examples in r folder missing the run commands. In this PR, I just add the missing comment, which is consistent with other examples. ## How was this patch tested? Manual test. Author: wm624@hotmail.com <wm624@hotmail.com> Closes #17474 from wangmiao1981/stat.
…orithm.version option to configuration.md ## What changes were proposed in this pull request? Add `spark.hadoop.mapreduce.fileoutputcommitter.algorithm.version` option to `configuration.md`. Set `spark.hadoop.mapreduce.fileoutputcommitter.algorithm.version=2` can speed up [HadoopMapReduceCommitProtocol.commitJob](https://github.com/apache/spark/blob/v2.1.0/core/src/main/scala/org/apache/spark/internal/io/HadoopMapReduceCommitProtocol.scala#L121) for many output files. All cloudera's hadoop 2.6.0-cdh5.4.0 or higher versions(see: https://github.com/cloudera/hadoop-common/commit/1c1236182304d4075276c00c4592358f428bc433 and https://github.com/cloudera/hadoop-common/commit/16b2de27321db7ce2395c08baccfdec5562017f0) and apache's hadoop 2.7.0 or higher versions support this improvement. More see: 1. [MAPREDUCE-4815](https://issues.apache.org/jira/browse/MAPREDUCE-4815): Speed up FileOutputCommitter#commitJob for many output files. 2. [MAPREDUCE-6406](https://issues.apache.org/jira/browse/MAPREDUCE-6406): Update the default version for the property mapreduce.fileoutputcommitter.algorithm.version to 2. ## How was this patch tested? Manual test and exist tests. Author: Yuming Wang <wgyumg@gmail.com> Closes #17442 from wangyum/SPARK-20107.
## What changes were proposed in this pull request? Implementations of strategies for resilient block replication for different resource managers that replicate the 3-replica strategy used by HDFS, where the first replica is on an executor, the second replica within the same rack as the executor and a third replica on a different rack. The implementation involves providing two pluggable classes, one running in the driver that provides topology information for every host at cluster start and the second prioritizing a list of peer BlockManagerIds. The prioritization itself can be thought of an optimization problem to find a minimal set of peers that satisfy certain objectives and replicating to these peers first. The objectives can be used to express richer constraints over and above HDFS like 3-replica strategy. ## How was this patch tested? This patch was tested with unit tests for storage, along with new unit tests to verify prioritization behaviour. Author: Shubham Chopra <schopra31@bloomberg.net> Closes #13932 from shubhamchopra/PrioritizerStrategy.
…adoc ## What changes were proposed in this pull request? Use recommended values for row boundaries in Window's scaladoc, i.e. `Window.unboundedPreceding`, `Window.unboundedFollowing`, and `Window.currentRow` (that were introduced in 2.1.0). ## How was this patch tested? Local build Author: Jacek Laskowski <jacek@japila.pl> Closes #17417 from jaceklaskowski/window-expression-scaladoc.
…as supporting unaligned access java.nio.Bits.unaligned() does not return true for the ppc64le arch. see https://bugs.openjdk.java.net/browse/JDK-8165231 ## What changes were proposed in this pull request? check architecture ## How was this patch tested? unit test Author: samelamin <hussam.elamin@gmail.com> Author: samelamin <sam_elamin@discovery.com> Closes #17472 from samelamin/SPARK-19999.
…ll if set by --conf or configure file ## What changes were proposed in this pull request? while submit apps with -v or --verbose， we can print the right queue name, but if we set a queue name with `spark.yarn.queue` by --conf or in the spark-default.conf, we just got `null` for the queue in Parsed arguments. ``` bin/spark-shell -v --conf spark.yarn.queue=thequeue Using properties file: /home/hadoop/spark-2.1.0-bin-apache-hdp2.7.3/conf/spark-defaults.conf .... Adding default property: spark.yarn.queue=default Parsed arguments: master yarn deployMode client ... queue null .... verbose true Spark properties used, including those specified through --conf and those from the properties file /home/hadoop/spark-2.1.0-bin-apache-hdp2.7.3/conf/spark-defaults.conf: spark.yarn.queue -> thequeue .... ``` ## How was this patch tested? ut and local verify Author: Kent Yao <yaooqinn@hotmail.com> Closes #17430 from yaooqinn/SPARK-20096.
…tion
Fixed a few typos.
There is one more I'm not sure of:
```
Append mode uses watermark to drop old aggregation state. But the output of a
windowed aggregation is delayed the late threshold specified in `withWatermark()` as by
the modes semantics, rows can be added to the Result Table only once after they are
```
Not sure how to change `is delayed the late threshold`.
Author: Seigneurin, Alexis (CONT) <Alexis.Seigneurin@capitalone.com>
Closes #17443 from aseigneurin/typos.
…eported Intellij IDEA ## What changes were proposed in this pull request? Few changes related to Intellij IDEA inspection. ## How was this patch tested? Changes were tested by existing unit tests Author: Denis Bolshakov <denis.bolshakov@onefactor.com> Closes #17458 from dbolshak/SPARK-20127.
## What changes were proposed in this pull request? Instead of iterating all expressions that can return null for null inputs, we can just check `NullIntolerant`. ## How was this patch tested? existing tests Author: Wenchen Fan <wenchen@databricks.com> Closes #17450 from cloud-fan/null.
GulajavaMinistudio
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Oct 27, 2019
### What changes were proposed in this pull request? `org.apache.spark.sql.kafka010.KafkaDelegationTokenSuite` failed lately. After had a look at the logs it just shows the following fact without any details: ``` Caused by: sbt.ForkMain$ForkError: sun.security.krb5.KrbException: Server not found in Kerberos database (7) - Server not found in Kerberos database ``` Since the issue is intermittent and not able to reproduce it we should add more debug information and wait for reproduction with the extended logs. ### Why are the changes needed? Failing test doesn't give enough debug information. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? I've started the test manually and checked that such additional debug messages show up: ``` >>> KrbApReq: APOptions are 00000000 00000000 00000000 00000000 >>> EType: sun.security.krb5.internal.crypto.Aes128CtsHmacSha1EType Looking for keys for: kafka/localhostEXAMPLE.COM Added key: 17version: 0 Added key: 23version: 0 Added key: 16version: 0 Found unsupported keytype (3) for kafka/localhostEXAMPLE.COM >>> EType: sun.security.krb5.internal.crypto.Aes128CtsHmacSha1EType Using builtin default etypes for permitted_enctypes default etypes for permitted_enctypes: 17 16 23. >>> EType: sun.security.krb5.internal.crypto.Aes128CtsHmacSha1EType MemoryCache: add 1571936500/174770/16C565221B70AAB2BEFE31A83D13A2F4/client/localhostEXAMPLE.COM to client/localhostEXAMPLE.COM|kafka/localhostEXAMPLE.COM MemoryCache: Existing AuthList: #3: 1571936493/200803/8CD70D280B0862C5DA1FF901ECAD39FE/client/localhostEXAMPLE.COM #2: 1571936499/985009/BAD33290D079DD4E3579A8686EC326B7/client/localhostEXAMPLE.COM #1: 1571936499/995208/B76B9D78A9BE283AC78340157107FD40/client/localhostEXAMPLE.COM ``` Closes apache#26252 from gaborgsomogyi/SPARK-29580. Authored-by: Gabor Somogyi <gabor.g.somogyi@gmail.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
GulajavaMinistudio
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Jun 12, 2020
### What changes were proposed in this pull request?
This PR proposes to make `PythonFunction` holds `Seq[Byte]` instead of `Array[Byte]` to be able to compare if the byte array has the same values for the cache manager.
### Why are the changes needed?
Currently the cache manager doesn't use the cache for `udf` if the `udf` is created again even if the functions is the same.
```py
>>> func = lambda x: x
>>> df = spark.range(1)
>>> df.select(udf(func)("id")).cache()
```
```py
>>> df.select(udf(func)("id")).explain()
== Physical Plan ==
*(2) Project [pythonUDF0#14 AS <lambda>(id)#12]
+- BatchEvalPython [<lambda>(id#0L)], [pythonUDF0#14]
+- *(1) Range (0, 1, step=1, splits=12)
```
This is because `PythonFunction` holds `Array[Byte]`, and `equals` method of array equals only when the both array is the same instance.
### Does this PR introduce _any_ user-facing change?
Yes, if the user reuse the Python function for the UDF, the cache manager will detect the same function and use the cache for it.
### How was this patch tested?
I added a test case and manually.
```py
>>> df.select(udf(func)("id")).explain()
== Physical Plan ==
InMemoryTableScan [<lambda>(id)#12]
+- InMemoryRelation [<lambda>(id)#12], StorageLevel(disk, memory, deserialized, 1 replicas)
+- *(2) Project [pythonUDF0#5 AS <lambda>(id)#3]
+- BatchEvalPython [<lambda>(id#0L)], [pythonUDF0#5]
+- *(1) Range (0, 1, step=1, splits=12)
```
Closes apache#28774 from ueshin/issues/SPARK-31945/udf_cache.
Authored-by: Takuya UESHIN <ueshin@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
GulajavaMinistudio
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Jul 8, 2020
… without WindowExpression
### What changes were proposed in this pull request?
Add WindowFunction check at `CheckAnalysis`.
### Why are the changes needed?
Provide friendly error msg.
**BEFORE**
```scala
scala> sql("select rank() from values(1)").show
java.lang.UnsupportedOperationException: Cannot generate code for expression: rank()
```
**AFTER**
```scala
scala> sql("select rank() from values(1)").show
org.apache.spark.sql.AnalysisException: Window function rank() requires an OVER clause.;;
Project [rank() AS RANK()#3]
+- LocalRelation [col1#2]
```
### Does this PR introduce _any_ user-facing change?
Yes, user wiill be given a better error msg.
### How was this patch tested?
Pass the newly added UT.
Closes apache#28808 from ulysses-you/SPARK-31975.
Authored-by: ulysses <youxiduo@weidian.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
GulajavaMinistudio
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Oct 14, 2022
…ly equivalent children in `RewriteDistinctAggregates` ### What changes were proposed in this pull request? In `RewriteDistinctAggregates`, when grouping aggregate expressions by function children, treat children that are semantically equivalent as the same. ### Why are the changes needed? This PR will reduce the number of projections in the Expand operator when there are multiple distinct aggregations with superficially different children. In some cases, it will eliminate the need for an Expand operator. Example: In the following query, the Expand operator creates 3\*n rows (where n is the number of incoming rows) because it has a projection for each of function children `b + 1`, `1 + b` and `c`. ``` create or replace temp view v1 as select * from values (1, 2, 3.0), (1, 3, 4.0), (2, 4, 2.5), (2, 3, 1.0) v1(a, b, c); select a, count(distinct b + 1), avg(distinct 1 + b) filter (where c > 0), sum(c) from v1 group by a; ``` The Expand operator has three projections (each producing a row for each incoming row): ``` [a#87, null, null, 0, null, UnscaledValue(c#89)], <== projection #1 (for regular aggregation) [a#87, (b#88 + 1), null, 1, null, null], <== projection #2 (for distinct aggregation of b + 1) [a#87, null, (1 + b#88), 2, (c#89 > 0.0), null]], <== projection #3 (for distinct aggregation of 1 + b) ``` In reality, the Expand only needs one projection for `1 + b` and `b + 1`, because they are semantically equivalent. With the proposed change, the Expand operator's projections look like this: ``` [a#67, null, 0, null, UnscaledValue(c#69)], <== projection #1 (for regular aggregations) [a#67, (b#68 + 1), 1, (c#69 > 0.0), null]], <== projection #2 (for distinct aggregation on b + 1 and 1 + b) ``` With one less projection, Expand produces 2\*n rows instead of 3\*n rows, but still produces the correct result. In the case where all distinct aggregates have semantically equivalent children, the Expand operator is not needed at all. Benchmark code in the JIRA (SPARK-40382). Before the PR: ``` distinct aggregates: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative ------------------------------------------------------------------------------------------------------------------------ all semantically equivalent 14721 14859 195 5.7 175.5 1.0X some semantically equivalent 14569 14572 5 5.8 173.7 1.0X none semantically equivalent 14408 14488 113 5.8 171.8 1.0X ``` After the PR: ``` distinct aggregates: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative ------------------------------------------------------------------------------------------------------------------------ all semantically equivalent 3658 3692 49 22.9 43.6 1.0X some semantically equivalent 9124 9214 127 9.2 108.8 0.4X none semantically equivalent 14601 14777 250 5.7 174.1 0.3X ``` ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? New unit tests. Closes apache#37825 from bersprockets/rewritedistinct_issue. Authored-by: Bruce Robbins <bersprockets@gmail.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
GulajavaMinistudio
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Mar 23, 2023
…edExpression() ### What changes were proposed in this pull request? In `EquivalentExpressions.addExpr()`, add a guard `supportedExpression()` to make it consistent with `addExprTree()` and `getExprState()`. ### Why are the changes needed? This fixes a regression caused by apache#39010 which added the `supportedExpression()` to `addExprTree()` and `getExprState()` but not `addExpr()`. One example of a use case affected by the inconsistency is the `PhysicalAggregation` pattern in physical planning. There, it calls `addExpr()` to deduplicate the aggregate expressions, and then calls `getExprState()` to deduplicate the result expressions. Guarding inconsistently will cause the aggregate and result expressions go out of sync, eventually resulting in query execution error (or whole-stage codegen error). ### Does this PR introduce _any_ user-facing change? This fixes a regression affecting Spark 3.3.2+, where it may manifest as an error running aggregate operators with higher-order functions. Example running the SQL command: ```sql select max(transform(array(id), x -> x)), max(transform(array(id), x -> x)) from range(2) ``` example error message before the fix: ``` java.lang.IllegalStateException: Couldn't find max(transform(array(id#0L), lambdafunction(lambda x#2L, lambda x#2L, false)))#4 in [max(transform(array(id#0L), lambdafunction(lambda x#1L, lambda x#1L, false)))#3] ``` after the fix this error is gone. ### How was this patch tested? Added new test cases to `SubexpressionEliminationSuite` for the immediate issue, and to `DataFrameAggregateSuite` for an example of user-visible symptom. Closes apache#40473 from rednaxelafx/spark-42851. Authored-by: Kris Mok <kris.mok@databricks.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>
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