| Commit message (Collapse) | Author | Age | Files | Lines |
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Consumer API
## What changes were proposed in this pull request?
New Kafka consumer api for the released 0.10 version of Kafka
## How was this patch tested?
Unit tests, manual tests
Author: cody koeninger <cody@koeninger.org>
Closes #11863 from koeninger/kafka-0.9.
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## What changes were proposed in this pull request?
Currently, Spark Scala/Java API documents shows **org.apache.hadoop.hive.ql.io.orc** package at the top.
http://spark.apache.org/docs/2.0.0-preview/api/scala/index.html#org.apache.spark.package
http://spark.apache.org/docs/2.0.0-preview/api/java/index.html
This PR hides `SparkOrcNewRecordReader` from API docs.
## How was this patch tested?
Manual. (`build/sbt unidoc`).
The following is the screenshot after this PR.
**Scala API doc**
![Scala API doc](https://app.box.com/representation/file_version_75673952621/image_2048/1.png?shared_name=2mdqydygs8le6q9x00356898662zjwz6)
**Java API doc**
![Java API doc](https://app.box.com/representation/file_version_75673951725/image_2048/1.png?shared_name=iv23eeqy3avvkqz203v9ygfaqeyml85j)
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes #13914 from dongjoon-hyun/SPARK-16111.
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## What changes were proposed in this pull request?
In 1.4 and earlier releases, we have package grouping in the generated Java API docs. See http://spark.apache.org/docs/1.4.0/api/java/index.html. However, this disappeared in 1.5.0: http://spark.apache.org/docs/1.5.0/api/java/index.html.
Rather than fixing it, I'd suggest removing grouping. Because it might take some time to fix and it is a manual process to update the grouping in `SparkBuild.scala`. I didn't find anyone complaining about missing groups since 1.5.0 on Google.
Manually checked the generated Java API docs and confirmed that they are the same as in master.
Author: Xiangrui Meng <meng@databricks.com>
Closes #13856 from mengxr/SPARK-16155.
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Windows
## What changes were proposed in this pull request?
The way bash script `build/spark-build-info` is called from core/pom.xml prevents Spark building on Windows. Instead of calling the script directly we call bash and pass the script as an argument. This enables running it on Windows with bash installed which typically comes with Git.
This brings https://github.com/apache/spark/pull/13612 up-to-date and also addresses comments from the code review.
Closes #13612
## How was this patch tested?
I built manually (on a Mac) to verify it didn't break Mac compilation.
Author: Reynold Xin <rxin@databricks.com>
Author: avulanov <nashb@yandex.ru>
Closes #13691 from rxin/SPARK-15851.
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source code compatibility
## What changes were proposed in this pull request?
Revert partial changes in SPARK-12600, and add some deprecated method back to SQLContext for backward source code compatibility.
## How was this patch tested?
Manual test.
Author: Sean Zhong <seanzhong@databricks.com>
Closes #13637 from clockfly/SPARK-15914.
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## What changes were proposed in this pull request?
These were not updated after performance improvements. To make updating them easier, I also moved the results from inline comments out into a file, which is auto-generated when the benchmark is re-run.
Author: Eric Liang <ekl@databricks.com>
Closes #13607 from ericl/sc-3538.
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Spark's SBT build currently uses a fork of the sbt-pom-reader plugin but depends on that fork via a SBT subproject which is cloned from https://github.com/scrapcodes/sbt-pom-reader/tree/ignore_artifact_id. This unnecessarily slows down the initial build on fresh machines and is also risky because it risks a build breakage in case that GitHub repository ever changes or is deleted.
In order to address these issues, I have published a pre-built binary of our forked sbt-pom-reader plugin to Maven Central under the `org.spark-project` namespace and have updated Spark's build to use that artifact. This published artifact was built from https://github.com/JoshRosen/sbt-pom-reader/tree/v1.0.0-spark, which contains the contents of ScrapCodes's branch plus an additional patch to configure the build for artifact publication.
/cc srowen ScrapCodes for review.
Author: Josh Rosen <joshrosen@databricks.com>
Closes #13564 from JoshRosen/use-published-fork-of-pom-reader.
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## What changes were proposed in this pull request?
Change the way spark picks up version information. Also embed the build information to better identify the spark version running.
More context can be found here : https://github.com/apache/spark/pull/12152
## How was this patch tested?
Ran the mvn and sbt builds to verify the version information was being displayed correctly on executing <code>spark-submit --version </code>
![image](https://cloud.githubusercontent.com/assets/7732317/15197251/f7c673a2-1795-11e6-8b2f-88f2a70cf1c1.png)
Author: Dhruve Ashar <dhruveashar@gmail.com>
Closes #13061 from dhruve/impr/SPARK-14279.
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This helps with preventing jdk8-specific calls being checked in,
because PR builders are running the compiler with the wrong settings.
If the JAVA_7_HOME env variable is set, assume it points at
a jdk7 and use its rt.jar when invoking javac. For zinc, just run
it with jdk7, and disable it when building jdk8-specific code.
A big note for sbt usage: adding the bootstrap options forces sbt
to fork the compiler, and that disables incremental compilation.
That means that it's really not convenient to use for normal
development, but should be ok for automated builds.
Tested with JAVA_HOME=jdk8 and JAVA_7_HOME=jdk7:
- mvn + zinc
- mvn sans zinc
- sbt
Verified that in all cases, jdk8-specific library calls fail to
compile.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes #13272 from vanzin/SPARK-15451.
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## What changes were proposed in this pull request?
We're using `asML` to convert the mllib vector/matrix to ml vector/matrix now. Using `as` is more correct given that this conversion actually shares the same underline data structure. As a result, in this PR, `toBreeze` will be changed to `asBreeze`. This is a private API, as a result, it will not affect any user's application.
## How was this patch tested?
unit tests
Author: DB Tsai <dbt@netflix.com>
Closes #13198 from dbtsai/minor.
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SparkSession.build.getOrCreate
## What changes were proposed in this pull request?
This PR changes SQLContext/HiveContext's public constructor to use SparkSession.build.getOrCreate and removes isRootContext from SQLContext.
## How was this patch tested?
Existing tests.
Author: Yin Huai <yhuai@databricks.com>
Closes #13310 from yhuai/SPARK-15532.
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## What changes were proposed in this pull request?
This patch renames various DefaultSources to make their names more self-describing. The choice of "DefaultSource" was from the days when we did not have a good way to specify short names.
They are now named:
- LibSVMFileFormat
- CSVFileFormat
- JdbcRelationProvider
- JsonFileFormat
- ParquetFileFormat
- TextFileFormat
Backward compatibility is maintained through aliasing.
## How was this patch tested?
Updated relevant test cases too.
Author: Reynold Xin <rxin@databricks.com>
Closes #13311 from rxin/SPARK-15543.
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## What changes were proposed in this pull request?
The ANTLR4 SBT plugin has been moved from its own repo to one on bintray. The version was also changed from `0.7.10` to `0.7.11`. The latter actually broke our build (ihji has fixed this by also adding `0.7.10` and others to the bin-tray repo).
This PR upgrades the SBT-ANTLR4 plugin and ANTLR4 to their most recent versions (`0.7.11`/`4.5.3`). I have also removed a few obsolete build configurations.
## How was this patch tested?
Manually running SBT/Maven builds.
Author: Herman van Hovell <hvanhovell@questtec.nl>
Closes #13299 from hvanhovell/SPARK-15525.
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hivecontext-compatibility module
## What changes were proposed in this pull request?
I initially asked to create a hivecontext-compatibility module to put the HiveContext there. But we are so close to Spark 2.0 release and there is only a single class in it. It seems overkill to have an entire package, which makes it more inconvenient, for a single class.
## How was this patch tested?
Tests were moved.
Author: Reynold Xin <rxin@databricks.com>
Closes #13207 from rxin/SPARK-15424.
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## What changes were proposed in this pull request?
Since we support forced spilling for Spillable, which only works in OnHeap mode, different from other SQL operators (could be OnHeap or OffHeap), we should considering the mode of consumer before calling trigger forced spilling.
## How was this patch tested?
Add new test.
Author: Davies Liu <davies@databricks.com>
Closes #13151 from davies/fix_mode.
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algorithms
## What changes were proposed in this pull request?
Once SPARK-14487 and SPARK-14549 are merged, we will migrate to use the new vector and matrix type in the new ml pipeline based apis.
## How was this patch tested?
Unit tests
Author: DB Tsai <dbt@netflix.com>
Author: Liang-Chi Hsieh <simonh@tw.ibm.com>
Author: Xiangrui Meng <meng@databricks.com>
Closes #12627 from dbtsai/SPARK-14615-NewML.
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spark-tags
## What changes were proposed in this pull request?
(See https://github.com/apache/spark/pull/12416 where most of this was already reviewed and committed; this is just the module structure and move part. This change does not move the annotations into test scope, which was the apparently problem last time.)
Rename `spark-test-tags` -> `spark-tags`; move common annotations like `Since` to `spark-tags`
## How was this patch tested?
Jenkins tests.
Author: Sean Owen <sowen@cloudera.com>
Closes #13074 from srowen/SPARK-15290.
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## What changes were proposed in this pull request?
Renaming the streaming-kafka artifact to include kafka version, in anticipation of needing a different artifact for later kafka versions
## How was this patch tested?
Unit tests
Author: cody koeninger <cody@koeninger.org>
Closes #12946 from koeninger/SPARK-15085.
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## What changes were proposed in this pull request?
This PR removes the old `json(path: String)` API which is covered by the new `json(paths: String*)`.
## How was this patch tested?
Jenkins tests (existing tests should cover this)
Author: hyukjinkwon <gurwls223@gmail.com>
Author: Hyukjin Kwon <gurwls223@gmail.com>
Closes #13040 from HyukjinKwon/SPARK-15250.
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## What changes were proposed in this pull request?
Currently PipedRDD internally uses PrintWriter to write data to the stdin of the piped process, which by default uses a BufferedWriter of buffer size 8k. In our experiment, we have seen that 8k buffer size is too small and the job spends significant amount of CPU time in system calls to copy the data. We should have a way to configure the buffer size for the writer.
## How was this patch tested?
Ran PipedRDDSuite tests.
Author: Sital Kedia <skedia@fb.com>
Closes #12309 from sitalkedia/bufferedPipedRDD.
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## What changes were proposed in this pull request?
Removed blockTransferService and sparkFilesDir from SparkEnv since they're rarely used and don't need to be in stored in the env. Edited their few usages to accommodate the change.
## How was this patch tested?
ran dev/run-tests locally
Author: Alex Bozarth <ajbozart@us.ibm.com>
Closes #12970 from ajbozarth/spark10653.
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## What changes were proposed in this pull request?
Create a maven profile for executing the docker integration tests using maven
Remove docker integration tests from main sbt build
Update documentation on how to run docker integration tests from sbt
## How was this patch tested?
Manual test of the docker integration tests as in :
mvn -Pdocker-integration-tests -pl :spark-docker-integration-tests_2.11 compile test
## Other comments
Note that the the DB2 Docker Tests are still disabled as there is a kernel version issue on the AMPLab Jenkins slaves and we would need to get them on the right level before enabling those tests. They do run ok locally with the updates from PR #12348
Author: Luciano Resende <lresende@apache.org>
Closes #12508 from lresende/docker.
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## What changes were proposed in this pull request?
Enhance the DB2 JDBC Dialect docker tests as they seemed to have had some issues on previous merge causing some tests to fail.
## How was this patch tested?
By running the integration tests locally.
Author: Luciano Resende <lresende@apache.org>
Closes #12348 from lresende/SPARK-14589.
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#### What changes were proposed in this pull request?
This PR removes three methods the were deprecated in 1.6.0:
- `PortableDataStream.close()`
- `LinearRegression.weights`
- `LogisticRegression.weights`
The rationale for doing this is that the impact is small and that Spark 2.0 is a major release.
#### How was this patch tested?
Compilation succeded.
Author: Herman van Hovell <hvanhovell@questtec.nl>
Closes #12732 from hvanhovell/SPARK-14952.
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## What changes were proposed in this pull request?
In the past, genjavadoc had issues with package private members which led the spark project to use a forked version. This issue has been fixed upstream (typesafehub/genjavadoc#70) and a release is available for scala versions 2.10, 2.11 **and 2.12**, hence a forked version for spark is no longer necessary.
This pull request updates the build configuration to use the newest upstream genjavadoc.
## How was this patch tested?
The build was run `sbt unidoc`. During the process javadoc emits some errors on the generated java stubs, however these errors were also present before the upgrade. Furthermore, the produced html is fine.
Author: Jakob Odersky <jakob@odersky.com>
Closes #12707 from jodersky/SPARK-14511-genjavadoc.
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spark-mllib-local"
This reverts commit dae538a4d7c36191c1feb02ba87ffc624ab960dc.
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spark-mllib-local
## What changes were proposed in this pull request?
This PR adds `since` tag into the matrix and vector classes in spark-mllib-local.
## How was this patch tested?
Scala-style checks passed.
Author: Pravin Gadakh <prgadakh@in.ibm.com>
Closes #12416 from pravingadakh/SPARK-14613.
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## What changes were proposed in this pull request?
This PR introduces a new accumulator API which is much simpler than before:
1. the type hierarchy is simplified, now we only have an `Accumulator` class
2. Combine `initialValue` and `zeroValue` concepts into just one concept: `zeroValue`
3. there in only one `register` method, the accumulator registration and cleanup registration are combined.
4. the `id`,`name` and `countFailedValues` are combined into an `AccumulatorMetadata`, and is provided during registration.
`SQLMetric` is a good example to show the simplicity of this new API.
What we break:
1. no `setValue` anymore. In the new API, the intermedia type can be different from the result type, it's very hard to implement a general `setValue`
2. accumulator can't be serialized before registered.
Problems need to be addressed in follow-ups:
1. with this new API, `AccumulatorInfo` doesn't make a lot of sense, the partial output is not partial updates, we need to expose the intermediate value.
2. `ExceptionFailure` should not carry the accumulator updates. Why do users care about accumulator updates for failed cases? It looks like we only use this feature to update the internal metrics, how about we sending a heartbeat to update internal metrics after the failure event?
3. the public event `SparkListenerTaskEnd` carries a `TaskMetrics`. Ideally this `TaskMetrics` don't need to carry external accumulators, as the only method of `TaskMetrics` that can access external accumulators is `private[spark]`. However, `SQLListener` use it to retrieve sql metrics.
## How was this patch tested?
existing tests
Author: Wenchen Fan <wenchen@databricks.com>
Closes #12612 from cloud-fan/acc.
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This reverts commit 3f49afee937a66d458e0c194e46d6a9e380e054e.
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## What changes were proposed in this pull request?
In Spark 2.0, `SparkSession` is the new thing. Internally we should stop using `SQLContext` everywhere since that's supposed to be not the main user-facing API anymore.
In this patch I took care to not break any public APIs. The one place that's suspect is `o.a.s.ml.source.libsvm.DefaultSource`, but according to mengxr it's not supposed to be public so it's OK to change the underlying `FileFormat` trait.
**Reviewers**: This is a big patch that may be difficult to review but the changes are actually really straightforward. If you prefer I can break it up into a few smaller patches, but it will delay the progress of this issue a little.
## How was this patch tested?
No change in functionality intended.
Author: Andrew Or <andrew@databricks.com>
Closes #12625 from andrewor14/spark-session-refactor.
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## What changes were proposed in this pull request?
Sbt compile and test should also run scalastyle. This makes it less likely you forget to run scalastyle and fail in jenkins. Scalastyle results are cached for efficiency.
This patch was originally written by ahirreddy; I just fixed it up to work with scalastyle 0.8.0.
## How was this patch tested?
Tested manually with `build/sbt package`.
Author: Eric Liang <ekl@databricks.com>
Closes #12555 from ericl/scalastyle.
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## What changes were proposed in this pull request?
This PR creates a compatibility module in sql (called `hive-1-x-compatibility`), which will host HiveContext in Spark 2.0 (moving HiveContext to here will be done separately). This module is not included in assembly because only users who still want to access HiveContext need it.
## How was this patch tested?
I manually tested `sbt/sbt -Phive package` and `mvn -Phive package -DskipTests`.
Author: Yin Huai <yhuai@databricks.com>
Closes #12580 from yhuai/compatibility.
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## What changes were proposed in this pull request?
Implement some `hashCode` and `equals` together in order to enable the scalastyle.
This is a first batch, I will continue to implement them but I wanted to know your thoughts.
Author: Joan <joan@goyeau.com>
Closes #12157 from joan38/SPARK-6429-HashCode-Equals.
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Vector, Matrix types
## What changes were proposed in this pull request?
For maintaining wrappers around spark.mllib algorithms in spark.ml, it will be useful to have ```private[spark]``` methods for converting from one linear algebra representation to another.
This PR adds toNew, fromNew methods for all spark.mllib Vector and Matrix types.
## How was this patch tested?
Unit tests for all conversions
Author: Joseph K. Bradley <joseph@databricks.com>
Closes #12504 from jkbradley/linalg-conversions.
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## What changes were proposed in this pull request?
After removing most of `HiveContext` in 8fc267ab3322e46db81e725a5cb1adb5a71b2b4d we can now move existing functionality in `SQLContext` to `SparkSession`. As of this PR `SQLContext` becomes a simple wrapper that has a `SparkSession` and delegates all functionality to it.
## How was this patch tested?
Jenkins.
Author: Andrew Or <andrew@databricks.com>
Closes #12553 from andrewor14/implement-spark-session.
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thread for memory
## What changes were proposed in this pull request?
In #9241 It implemented a mechanism to call spill() on those SQL operators that support spilling if there is not enough memory for execution.
But ExternalSorter and AppendOnlyMap in Spark core are not worked. So this PR make them benefit from #9241. Now when there is not enough memory for execution, it can get memory by spilling ExternalSorter and AppendOnlyMap in Spark core.
## How was this patch tested?
add two unit tests for it.
Author: Lianhui Wang <lianhuiwang09@gmail.com>
Closes #10024 from lianhuiwang/SPARK-4452-2.
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## What changes were proposed in this pull request?
Before this PR, we create accumulators at driver side(and register them) and send them to executor side, then we create `TaskMetrics` with these accumulators at executor side.
After this PR, we will create `TaskMetrics` at driver side and send it to executor side, so that we can create accumulators inside `TaskMetrics` directly, which is cleaner.
## How was this patch tested?
existing tests.
Author: Wenchen Fan <wenchen@databricks.com>
Closes #12472 from cloud-fan/acc.
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execution/datasources package #12178
## What changes were proposed in this pull request?
This PR moves `HadoopFsRelation` related data source API into `execution/datasources` package.
Note that to avoid conflicts, this PR is based on #12153. Effective changes for this PR only consist of the last three commits. Will rebase after merging #12153.
## How was this patch tested?
Existing tests.
Author: Yin Huai <yhuai@databricks.com>
Author: Cheng Lian <lian@databricks.com>
Closes #12361 from liancheng/spark-14407-hide-hadoop-fs-relation.
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## What changes were proposed in this pull request?
This PR adds support for specifying an optional custom coalescer to the `coalesce()` method. Currently I have only added this feature to the `RDD` interface, and once we sort out the details we can proceed with adding this feature to the other APIs (`Dataset` etc.)
## How was this patch tested?
Added a unit test for this functionality.
/cc rxin (per our discussion on the mailing list)
Author: Nezih Yigitbasi <nyigitbasi@netflix.com>
Closes #11865 from nezihyigitbasi/custom_coalesce_policy.
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## What changes were proposed in this pull request?
This PR is a follow up for https://github.com/apache/spark/pull/12417, now we always track input/output/shuffle metrics in spark JSON protocol and status API.
Most of the line changes are because of re-generating the gold answer for `HistoryServerSuite`, and we add a lot of 0 values for read/write metrics.
## How was this patch tested?
existing tests.
Author: Wenchen Fan <wenchen@databricks.com>
Closes #12462 from cloud-fan/follow.
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## What changes were proposed in this pull request?
Enable Oracle docker tests
## How was this patch tested?
Existing tests
Author: Luciano Resende <lresende@apache.org>
Closes #12270 from lresende/oracle.
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Right now Spark's Scaladoc does not link to Scala standard library and other dependencies. This would bother Spark starters because they may be not experienced Scala programmers.
This patch fixes these links in ScalaDoc.
Author: 杨博 (Yang Bo) <pop.atry@gmail.com>
Closes #12444 from Atry/patch-1.
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## What changes were proposed in this pull request?
Part of the reason why TaskMetrics and its callers are complicated are due to the optional metrics we collect, including input, output, shuffle read, and shuffle write. I think we can always track them and just assign 0 as the initial values. It is usually very obvious whether a task is supposed to read any data or not. By always tracking them, we can remove a lot of map, foreach, flatMap, getOrElse(0L) calls throughout Spark.
This patch also changes a few behaviors.
1. Removed the distinction of data read/write methods (e.g. Hadoop, Memory, Network, etc).
2. Accumulate all data reads and writes, rather than only the first method. (Fixes SPARK-5225)
## How was this patch tested?
existing tests.
This is bases on https://github.com/apache/spark/pull/12388, with more test fixes.
Author: Reynold Xin <rxin@databricks.com>
Author: Wenchen Fan <wenchen@databricks.com>
Closes #12417 from cloud-fan/metrics-refactor.
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## What changes were proposed in this pull request?
This patch removes some of the deprecated APIs in TaskMetrics. This is part of my bigger effort to simplify accumulators and task metrics.
## How was this patch tested?
N/A - only removals
Author: Reynold Xin <rxin@databricks.com>
Closes #12375 from rxin/SPARK-14617.
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## What changes were proposed in this pull request?
Old `HadoopFsRelation` API includes `buildInternalScan()` which uses `SqlNewHadoopRDD` in `ParquetRelation`.
Because now the old API is removed, `SqlNewHadoopRDD` is not used anymore.
So, this PR removes `SqlNewHadoopRDD` and several unused imports.
This was discussed in https://github.com/apache/spark/pull/12326.
## How was this patch tested?
Several related existing unit tests and `sbt scalastyle`.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes #12354 from HyukjinKwon/SPARK-14596.
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## What changes were proposed in this pull request?
This adds a new API call `TaskContext.getLocalProperty` for getting properties set in the driver from executors. These local properties are automatically propagated from the driver to executors. For streaming, the context for streaming tasks will be the initial driver context when ssc.start() is called.
## How was this patch tested?
Unit tests.
cc JoshRosen
Author: Eric Liang <ekl@databricks.com>
Closes #12248 from ericl/sc-2813.
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Add integration tests based on docker to test DB2 JDBC dialect support
Author: Luciano Resende <lresende@apache.org>
Closes #9893 from lresende/SPARK-10521.
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## What changes were proposed in this pull request?
In order to separate the linear algebra, and vector matrix classes into a standalone jar, we need to setup the build first. This PR will create a new jar called mllib-local with minimal dependencies.
The previous PR was failing the build because of `spark-core:test` dependency, and that was reverted. In this PR, `FunSuite` with `// scalastyle:ignore funsuite` in mllib-local test was used, similar to sketch.
Thanks.
## How was this patch tested?
Unit tests
mengxr tedyu holdenk
Author: DB Tsai <dbt@netflix.com>
Closes #12298 from dbtsai/dbtsai-mllib-local-build-fix.
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This reverts commit 1598d11bb0248384872cf88bc2b16f3b238046ad.
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## What changes were proposed in this pull request?
In order to separate the linear algebra, and vector matrix classes into a standalone jar, we need to setup the build first. This PR will create a new jar called mllib-local with minimal dependencies. The test scope will still depend on spark-core and spark-core-test in order to use the common utilities, but the runtime will avoid any platform dependency. Couple platform independent classes will be moved to this package to demonstrate how this work.
## How was this patch tested?
Unit tests
Author: DB Tsai <dbt@netflix.com>
Closes #12241 from dbtsai/dbtsai-mllib-local-build.
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