## What changes were proposed in this pull request?
`ReplSuite.newProductSeqEncoder with REPL defined class` was flaky and throws OOM exception frequently. By analyzing the heap dump, we found the reason is that, in each test case of `ReplSuite`, we create a REPL instance, which creates a classloader and loads a lot of classes related to `SparkContext`. More details please see https://github.com/apache/spark/pull/17833#issuecomment-298711435.
In this PR, we create a new test suite, `SingletonReplSuite`, which shares one REPL instances among all the test cases. Then we move most of the tests from `ReplSuite` to `SingletonReplSuite`, to avoid creating a lot of REPL instances and reduce memory footprint.
## How was this patch tested?
test only change
Author: Wenchen Fan <wenchen@databricks.com>
Closes#17844 from cloud-fan/flaky-test.
## What changes were proposed in this pull request?
Add Locale.ROOT to internal calls to String `toLowerCase`, `toUpperCase`, to avoid inadvertent locale-sensitive variation in behavior (aka the "Turkish locale problem").
The change looks large but it is just adding `Locale.ROOT` (the locale with no country or language specified) to every call to these methods.
## How was this patch tested?
Existing tests.
Author: Sean Owen <sowen@cloudera.com>
Closes#17527 from srowen/SPARK-20156.
Previously, we were using the mirror of passed in `TypeTag` when reflecting to build an encoder. This fails when the outer class is built in (i.e. `Seq`'s default mirror is based on root classloader) but inner classes (i.e. `A` in `Seq[A]`) are defined in the REPL or a library.
This patch changes us to always reflect based on a mirror created using the context classloader.
Author: Michael Armbrust <michael@databricks.com>
Closes#17201 from marmbrus/replSeqEncoder.
## What changes were proposed in this pull request?
`Signaling.cancelOnInterrupt` leaks a SparkContext per call and it makes ReplSuite unstable.
This PR adds `SparkContext.getActive` to allow `Signaling.cancelOnInterrupt` to get the active `SparkContext` to avoid the leak.
## How was this patch tested?
Jenkins
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#16825 from zsxwing/SPARK-19481.
## What changes were proposed in this pull request?
`ReplSuite`s hang due to the length limitation on Windows with the exception as below:
```
Spark context available as 'sc' (master = local-cluster[1,1,1024], app id = app-20161223114000-0000).
Spark session available as 'spark'.
Exception in thread "ExecutorRunner for app-20161223114000-0000/26995" java.lang.OutOfMemoryError: GC overhead limit exceeded
at java.util.Arrays.copyOf(Arrays.java:3332)
at java.lang.AbstractStringBuilder.expandCapacity(AbstractStringBuilder.java:137)
at java.lang.AbstractStringBuilder.ensureCapacityInternal(AbstractStringBuilder.java:121)
at java.lang.AbstractStringBuilder.append(AbstractStringBuilder.java:622)
at java.lang.StringBuilder.append(StringBuilder.java:202)
at java.lang.ProcessImpl.createCommandLine(ProcessImpl.java:194)
at java.lang.ProcessImpl.<init>(ProcessImpl.java:340)
at java.lang.ProcessImpl.start(ProcessImpl.java:137)
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1029)
at org.apache.spark.deploy.worker.ExecutorRunner.org$apache$spark$deploy$worker$ExecutorRunner$$fetchAndRunExecutor(ExecutorRunner.scala:167)
at org.apache.spark.deploy.worker.ExecutorRunner$$anon$1.run(ExecutorRunner.scala:73)
```
The reason is, it keeps failing and goes in an infinite loop. This fails because it uses the paths (via `getFile`) from URLs in the tests whereas some added afterward are normal local paths.
(`url.getFile` gives `/C:/a/b/c` and some paths are added later as the format of `C:\a\b\c`. )
So, many classpaths are duplicated because normal local paths and paths from URLs are mixed. This length is up to 40K which hits the length limitation problem (32K) on Windows.
The full command line built here is - https://gist.github.com/HyukjinKwon/46af7946c9a5fd4c6fc70a8a0aba1beb
## How was this patch tested?
Manually via AppVeyor.
**Before**
https://ci.appveyor.com/project/spark-test/spark/build/395-find-path-issues
**After**
https://ci.appveyor.com/project/spark-test/spark/build/398-find-path-issues
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#16398 from HyukjinKwon/SPARK-18842-more.
## What changes were proposed in this pull request?
Likewise [DataSet.scala](https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala#L156) KeyValueGroupedDataset should mark the queryExecution as transient.
As mentioned in the Jira ticket, without transient we saw serialization issues like
```
Caused by: java.io.NotSerializableException: org.apache.spark.sql.execution.QueryExecution
Serialization stack:
- object not serializable (class: org.apache.spark.sql.execution.QueryExecution, value: ==
```
## How was this patch tested?
Run the query which is specified in the Jira ticket before and after:
```
val a = spark.createDataFrame(sc.parallelize(Seq((1,2),(3,4)))).as[(Int,Int)]
val grouped = a.groupByKey(
{x:(Int,Int)=>x._1}
)
val mappedGroups = grouped.mapGroups((k,x)=>
{(k,1)}
)
val yyy = sc.broadcast(1)
val last = mappedGroups.rdd.map(xx=>
{ val simpley = yyy.value 1 }
)
```
Author: Ergin Seyfe <eseyfe@fb.com>
Closes#15706 from seyfe/keyvaluegrouped_serialization.
## What changes were proposed in this pull request?
SQLConf is session-scoped and mutable. However, we do have the requirement for a static SQL conf, which is global and immutable, e.g. the `schemaStringThreshold` in `HiveExternalCatalog`, the flag to enable/disable hive support, the global temp view database in https://github.com/apache/spark/pull/14897.
Actually we've already implemented static SQL conf implicitly via `SparkConf`, this PR just make it explicit and expose it to users, so that they can see the config value via SQL command or `SparkSession.conf`, and forbid users to set/unset static SQL conf.
## How was this patch tested?
new tests in SQLConfSuite
Author: Wenchen Fan <wenchen@databricks.com>
Closes#15295 from cloud-fan/global-conf.
## What changes were proposed in this pull request?
This pull request adds the functionality to enable accessing worker and application UI through master UI itself. Thus helps in accessing SparkUI when running spark cluster in closed networks e.g. Kubernetes. Cluster admin needs to expose only spark master UI and rest of the UIs can be in the private network, master UI will reverse proxy the connection request to corresponding resource. It adds the path for workers/application UIs as
WorkerUI: <http/https>://master-publicIP:<port>/target/workerID/
ApplicationUI: <http/https>://master-publicIP:<port>/target/appID/
This makes it easy for users to easily protect the Spark master cluster access by putting some reverse proxy e.g. https://github.com/bitly/oauth2_proxy
## How was this patch tested?
The functionality has been tested manually and there is a unit test too for testing access to worker UI with reverse proxy address.
pwendell bomeng BryanCutler can you please review it, thanks.
Author: Gurvinder Singh <gurvinder.singh@uninett.no>
Closes#13950 from gurvindersingh/rproxy.
## What changes were proposed in this pull request?
After digging into the logs, I noticed the failure is because in this test, it starts a local cluster with 2 executors. However, when SparkContext is created, executors may be still not up. When one of the executor is not up during running the job, the blocks won't be replicated.
This PR just adds a wait loop before running the job to fix the flaky test.
## How was this patch tested?
Jenkins
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#14905 from zsxwing/SPARK-17318-2.
## What changes were proposed in this pull request?
This is a straightforward clone of JoshRosen 's original patch. I have follow-up changes to fix block replication for repl-defined classes as well, but those appear to be flaking tests so I'm going to leave that for SPARK-17042
## How was this patch tested?
End-to-end test in ReplSuite (also more tests in DistributedSuite from the original patch).
Author: Eric Liang <ekl@databricks.com>
Closes#14311 from ericl/spark-16550.
## What changes were proposed in this pull request?
Currently when running spark on yarn, jars specified with --jars, --packages will be added twice, one is Spark's own file server, another is yarn's distributed cache, this can be seen from log:
for example:
```
./bin/spark-shell --master yarn-client --jars examples/target/scala-2.11/jars/scopt_2.11-3.3.0.jar
```
If specified the jar to be added is scopt jar, it will added twice:
```
...
16/07/14 15:06:48 INFO Server: Started 5603ms
16/07/14 15:06:48 INFO Utils: Successfully started service 'SparkUI' on port 4040.
16/07/14 15:06:48 INFO SparkUI: Bound SparkUI to 0.0.0.0, and started at http://192.168.0.102:4040
16/07/14 15:06:48 INFO SparkContext: Added JAR file:/Users/sshao/projects/apache-spark/examples/target/scala-2.11/jars/scopt_2.11-3.3.0.jar at spark://192.168.0.102:63996/jars/scopt_2.11-3.3.0.jar with timestamp 1468480008637
16/07/14 15:06:49 INFO RMProxy: Connecting to ResourceManager at /0.0.0.0:8032
16/07/14 15:06:49 INFO Client: Requesting a new application from cluster with 1 NodeManagers
16/07/14 15:06:49 INFO Client: Verifying our application has not requested more than the maximum memory capability of the cluster (8192 MB per container)
16/07/14 15:06:49 INFO Client: Will allocate AM container, with 896 MB memory including 384 MB overhead
16/07/14 15:06:49 INFO Client: Setting up container launch context for our AM
16/07/14 15:06:49 INFO Client: Setting up the launch environment for our AM container
16/07/14 15:06:49 INFO Client: Preparing resources for our AM container
16/07/14 15:06:49 WARN Client: Neither spark.yarn.jars nor spark.yarn.archive is set, falling back to uploading libraries under SPARK_HOME.
16/07/14 15:06:50 INFO Client: Uploading resource file:/private/var/folders/tb/8pw1511s2q78mj7plnq8p9g40000gn/T/spark-a446300b-84bf-43ff-bfb1-3adfb0571a42/__spark_libs__6486179704064718817.zip -> hdfs://localhost:8020/user/sshao/.sparkStaging/application_1468468348998_0009/__spark_libs__6486179704064718817.zip
16/07/14 15:06:51 INFO Client: Uploading resource file:/Users/sshao/projects/apache-spark/examples/target/scala-2.11/jars/scopt_2.11-3.3.0.jar -> hdfs://localhost:8020/user/sshao/.sparkStaging/application_1468468348998_0009/scopt_2.11-3.3.0.jar
16/07/14 15:06:51 INFO Client: Uploading resource file:/private/var/folders/tb/8pw1511s2q78mj7plnq8p9g40000gn/T/spark-a446300b-84bf-43ff-bfb1-3adfb0571a42/__spark_conf__326416236462420861.zip -> hdfs://localhost:8020/user/sshao/.sparkStaging/application_1468468348998_0009/__spark_conf__.zip
...
```
So here try to avoid adding jars to Spark's fileserver unnecessarily.
## How was this patch tested?
Manually verified both in yarn client and cluster mode, also in standalone mode.
Author: jerryshao <sshao@hortonworks.com>
Closes#14196 from jerryshao/SPARK-16540.
## What changes were proposed in this pull
(Paste from JIRA issue.)
As a follow up for SPARK-15697, I have following semantics for `:reset` command.
On `:reset` we forget all that user has done but not the initialization of spark. To avoid confusion or make it more clear, we show the message `spark` and `sc` are not erased, infact they are in same state as they were left by previous operations done by the user.
While doing above, somewhere I felt that this is not usually what reset means. But an accidental shutdown of a cluster can be very costly, so may be in that sense this is less surprising and still useful.
## How was this patch tested?
Manually, by calling `:reset` command, by both altering the state of SparkContext and creating some local variables.
Author: Prashant Sharma <prashant@apache.org>
Author: Prashant Sharma <prashsh1@in.ibm.com>
Closes#13661 from ScrapCodes/repl-reset-command.
When `--packages` is specified with spark-shell the classes from those packages cannot be found, which I think is due to some of the changes in SPARK-12343.
Tested manually with both scala 2.10 and 2.11 repls.
vanzin davies can you guys please review?
Author: Marcelo Vanzin <vanzin@cloudera.com>
Author: Nezih Yigitbasi <nyigitbasi@netflix.com>
Closes#13709 from nezihyigitbasi/SPARK-15782.
## What changes were proposed in this pull request?
When `--packages` is specified with `spark-shell` the classes from those packages cannot be found, which I think is due to some of the changes in `SPARK-12343`. In particular `SPARK-12343` removes a line that sets the `spark.jars` system property in client mode, which is used by the repl main class to set the classpath.
## How was this patch tested?
Tested manually.
This system property is used by the repl to populate its classpath. If
this is not set properly the classes for external packages cannot be
found.
tgravescs vanzin as you may be familiar with this part of the code.
Author: Nezih Yigitbasi <nyigitbasi@netflix.com>
Closes#13527 from nezihyigitbasi/repl-fix.
## What changes were proposed in this pull request?
Unblock some of the useful repl commands. like, "implicits", "javap", "power", "type", "kind". As they are useful and fully functional and part of scala/scala project, I see no harm in having them either.
Verbatim paste form JIRA description.
"implicits", "javap", "power", "type", "kind" commands in repl are blocked. However, they work fine in all cases I have tried. It is clear we don't support them as they are part of the scala/scala repl project. What is the harm in unblocking them, given they are useful ?
In previous versions of spark we disabled these commands because it was difficult to support them without customization and the associated maintenance. Since the code base of scala repl was actually ported and maintained under spark source. Now that is not the situation and one can benefit from these commands in Spark REPL as much as in scala repl.
## How was this patch tested?
Existing tests and manual, by trying out all of the above commands.
P.S. Symantics of reset are to be discussed in a separate issue.
Author: Prashant Sharma <prashsh1@in.ibm.com>
Closes#13437 from ScrapCodes/SPARK-15697/repl-unblock-commands.
Description from JIRA.
In ReplSuite, for a test that can be tested well on just local should not really have to start a local-cluster. And similarly a test is in-sufficiently run if it's actually fixing a problem related to a distributed run in environment with local run.
Existing tests.
Author: Prashant Sharma <prashsh1@in.ibm.com>
Closes#13574 from ScrapCodes/SPARK-15841/repl-suite-fix.
## What changes were proposed in this pull request?
This PR corrects the remaining cases for using old accumulators.
This does not change some old accumulator usages below:
- `ImplicitSuite.scala` - Tests dedicated to old accumulator, for implicits with `AccumulatorParam`
- `AccumulatorSuite.scala` - Tests dedicated to old accumulator
- `JavaSparkContext.scala` - For supporting old accumulators for Java API.
- `debug.package.scala` - Usage with `HashSet[String]`. Currently, it seems no implementation for this. I might be able to write an anonymous class for this but I didn't because I think it is not worth writing a lot of codes only for this.
- `SQLMetricsSuite.scala` - This uses the old accumulator for checking type boxing. It seems new accumulator does not require type boxing for this case whereas the old one requires (due to the use of generic).
## How was this patch tested?
Existing tests cover this.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#13434 from HyukjinKwon/accum.
## What changes were proposed in this pull request?
This PR change REPL/Main to check this property `spark.sql.catalogImplementation` to decide if `enableHiveSupport `should be called.
If `spark.sql.catalogImplementation` is set to `hive`, and hive classes are built, Spark will use Hive support.
Other wise, Spark will create a SparkSession with in-memory catalog support.
## How was this patch tested?
Run the REPL component test.
Author: xin Wu <xinwu@us.ibm.com>
Author: Xin Wu <xinwu@us.ibm.com>
Closes#13088 from xwu0226/SPARK-15236.
## What changes were proposed in this pull request?
see https://github.com/apache/spark/pull/12873#discussion_r61993910. The problem is, if we create `SparkContext` first and then call `SparkSession.builder.enableHiveSupport().getOrCreate()`, we will reuse the existing `SparkContext` and the hive flag won't be set.
## How was this patch tested?
verified it locally.
Author: Wenchen Fan <wenchen@databricks.com>
Closes#12890 from cloud-fan/repl.
## What changes were proposed in this pull request?
Users should use the builder pattern instead.
## How was this patch tested?
Jenks.
Author: Andrew Or <andrew@databricks.com>
Closes#12873 from andrewor14/spark-session-constructor.
## What changes were proposed in this pull request?
This is a proposal to print the Spark Driver UI link when spark-shell is launched.
## How was this patch tested?
Launched spark-shell in local mode and cluster mode. Spark-shell console output included following line:
"Spark context Web UI available at <Spark web url>"
Author: Ergin Seyfe <eseyfe@fb.com>
Closes#12341 from seyfe/spark_console_display_webui_link.
## What changes were proposed in this pull request?
```
Spark context available as 'sc' (master = local[*], app id = local-1461283768192).
Spark session available as 'spark'.
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 2.0.0-SNAPSHOT
/_/
Using Scala version 2.11.8 (Java HotSpot(TM) 64-Bit Server VM, Java 1.7.0_51)
Type in expressions to have them evaluated.
Type :help for more information.
scala> sql("SHOW TABLES").collect()
16/04/21 17:09:39 WARN ObjectStore: Version information not found in metastore. hive.metastore.schema.verification is not enabled so recording the schema version 1.2.0
16/04/21 17:09:39 WARN ObjectStore: Failed to get database default, returning NoSuchObjectException
res0: Array[org.apache.spark.sql.Row] = Array([src,false])
scala> sql("SHOW TABLES").collect()
res1: Array[org.apache.spark.sql.Row] = Array([src,false])
scala> spark.createDataFrame(Seq((1, 1), (2, 2), (3, 3)))
res2: org.apache.spark.sql.DataFrame = [_1: int, _2: int]
```
Hive things are loaded lazily.
## How was this patch tested?
Manual.
Author: Andrew Or <andrew@databricks.com>
Closes#12589 from andrewor14/spark-session-repl.
## What changes were proposed in this pull request?
Improve signal handling to allow interrupting running tasks from the REPL (with Ctrl+C).
If no tasks are running or Ctrl+C is pressed twice, the signal is forwarded to the default handler resulting in the usual termination of the application.
This PR is a rewrite of -- and therefore closes#8216 -- as per piaozhexiu's request
## How was this patch tested?
Signal handling is not easily testable therefore no unit tests were added. Nevertheless, the new functionality is implemented in a best-effort approach, soft-failing in case signals aren't available on a specific OS.
Author: Jakob Odersky <jakob@odersky.com>
Closes#12557 from jodersky/SPARK-10001-sigint.
## What changes were proposed in this pull request?
When we clean a closure, if its outermost parent is not a closure, we won't clone and clean it as cloning user's objects is dangerous. However, if it's a REPL line object, which may carry a lot of unnecessary references(like hadoop conf, spark conf, etc.), we should clean it as it's not a user object.
This PR improves the check for user's objects to exclude REPL line object.
## How was this patch tested?
existing tests.
Author: Wenchen Fan <wenchen@databricks.com>
Closes#12327 from cloud-fan/closure.
## What changes were proposed in this pull request?
When we first introduced Aggregators, we required the user of Aggregators to (implicitly) specify the encoders. It would actually make more sense to have the encoders be specified by the implementation of Aggregators, since each implementation should have the most state about how to encode its own data type.
Note that this simplifies the Java API because Java users no longer need to explicitly specify encoders for aggregators.
## How was this patch tested?
Updated unit tests.
Author: Reynold Xin <rxin@databricks.com>
Closes#12231 from rxin/SPARK-14451.
## What changes were proposed in this pull request?
Spark Shell provides an easy way to use Spark in Scala environment. This PR adds `reset` command to a blocked list, also cleaned up according to the Scala coding style.
```scala
scala> sc
res0: org.apache.spark.SparkContext = org.apache.spark.SparkContext718fad24
scala> :reset
scala> sc
<console>:11: error: not found: value sc
sc
^
```
If we blocks `reset`, Spark Shell works like the followings.
```scala
scala> :reset
reset: no such command. Type :help for help.
scala> :re
re is ambiguous: did you mean :replay or :require?
```
## How was this patch tested?
Manual. Run `bin/spark-shell` and type `:reset`.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#11920 from dongjoon-hyun/SPARK-14102.
## What changes were proposed in this pull request?
In https://github.com/apache/spark/pull/11410, we missed a corner case: define the inner class and use it in `Dataset` at the same time by using paste mode. For this case, the inner class and the `Dataset` are inside same line object, when we build the `Dataset`, we try to get outer pointer from line object, and it will fail because the line object is not initialized yet.
https://issues.apache.org/jira/browse/SPARK-13456?focusedCommentId=15209174&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-15209174 is an example for this corner case.
This PR make the process of getting outer pointer from line object lazy, so that we can successfully build the `Dataset` and finish initializing the line object.
## How was this patch tested?
new test in repl suite.
Author: Wenchen Fan <wenchen@databricks.com>
Closes#11931 from cloud-fan/repl.
## What changes were proposed in this pull request?
case classes defined in REPL are wrapped by line classes, and we have a trick for scala 2.10 REPL to automatically register the wrapper classes to `OuterScope` so that we can use when create encoders.
However, this trick doesn't work right after we upgrade to scala 2.11, and unfortunately the tests are only in scala 2.10, which makes this bug hidden until now.
This PR moves the encoder tests to scala 2.11 `ReplSuite`, and fixes this bug by another approach(the previous trick can't port to scala 2.11 REPL): make `OuterScope` smarter that can detect classes defined in REPL and load the singleton of line wrapper classes automatically.
## How was this patch tested?
the migrated encoder tests in `ReplSuite`
Author: Wenchen Fan <wenchen@databricks.com>
Closes#11410 from cloud-fan/repl.
## What changes were proposed in this pull request?
Logging was made private in Spark 2.0. If we move it, then users would be able to create a Logging trait themselves to avoid changing their own code.
## How was this patch tested?
existing tests.
Author: Wenchen Fan <wenchen@databricks.com>
Closes#11764 from cloud-fan/logger.
Three different things were needed to get rid of spurious warnings:
- silence deprecation warnings when cloning configuration
- change the way SparkHadoopUtil instantiates SparkConf to silence
warnings
- avoid creating new SparkConf instances where it's not needed.
On top of that, I changed the way that Logging.scala detects the repl;
now it uses a method that is overridden in the repl's Main class, and
the hack in Utils.scala is not needed anymore. This makes the 2.11 repl
behave like the 2.10 one and set the default log level to WARN, which
is a lot better. Previously, this wasn't working because the 2.11 repl
triggers log initialization earlier than the 2.10 one.
I also removed and simplified some other code in the 2.11 repl's Main
to avoid replicating logic that already exists elsewhere in Spark.
Tested the 2.11 repl in local and yarn modes.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#11510 from vanzin/SPARK-13626.
## What changes were proposed in this pull request?
After SPARK-6990, `dev/lint-java` keeps Java code healthy and helps PR review by saving much time.
This issue aims remove unused imports from Java/Scala code and add `UnusedImports` checkstyle rule to help developers.
## How was this patch tested?
```
./dev/lint-java
./build/sbt compile
```
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#11438 from dongjoon-hyun/SPARK-13583.
Now:
```
$ bin/spark-shell -i test.scala
NOTE: SPARK_PREPEND_CLASSES is set, placing locally compiled Spark classes ahead of assembly.
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel).
16/01/29 17:37:38 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
16/01/29 17:37:39 INFO Main: Created spark context..
Spark context available as sc (master = local[*], app id = local-1454085459000).
16/01/29 17:37:39 INFO Main: Created sql context..
SQL context available as sqlContext.
Loading test.scala...
hello
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 2.0.0-SNAPSHOT
/_/
Using Scala version 2.11.7 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_45)
Type in expressions to have them evaluated.
Type :help for more information.
```
Author: Iulian Dragos <jaguarul@gmail.com>
Closes#10984 from dragos/issue/repl-eval-file.
This patch changes Spark's build to make Scala 2.11 the default Scala version. To be clear, this does not mean that Spark will stop supporting Scala 2.10: users will still be able to compile Spark for Scala 2.10 by following the instructions on the "Building Spark" page; however, it does mean that Scala 2.11 will be the default Scala version used by our CI builds (including pull request builds).
The Scala 2.11 compiler is faster than 2.10, so I think we'll be able to look forward to a slight speedup in our CI builds (it looks like it's about 2X faster for the Maven compile-only builds, for instance).
After this patch is merged, I'll update Jenkins to add new compile-only jobs to ensure that Scala 2.10 compilation doesn't break.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#10608 from JoshRosen/SPARK-6363.
Removes some duplicated code that was reintroduced during a merge.
Author: Jakob Odersky <jodersky@gmail.com>
Closes#10711 from jodersky/repl-2.11-duplicate.
This avoids bringing up yet another HTTP server on the driver, and
instead reuses the file server already managed by the driver's
RpcEnv. As a bonus, the repl now inherits the security features of
the network library.
There's also a small change to create the directory for storing classes
under the root temp dir for the application (instead of directly
under java.io.tmpdir).
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#9923 from vanzin/SPARK-11563.
Process arguments passed to the spark-shell. Fixes running the spark-shell from within a build environment.
Author: Jakob Odersky <jodersky@gmail.com>
Closes#9824 from jodersky/shell-2.11.
In the default Spark distribution, there are currently two separate
log4j config files, with different default values for the root logger,
so that when running the shell you have a different default log level.
This makes the shell more usable, since the logs don't overwhelm the
output.
But if you install a custom log4j.properties, you lose that, because
then it's going to be used no matter whether you're running a regular
app or the shell.
With this change, the overriding of the log level is done differently;
the log level repl's main class (org.apache.spark.repl.Main) is used
to define the root logger's level when running the shell, defaulting
to WARN if it's not set explicitly.
On a somewhat related change, the shell output about the "sc" variable
was changed a bit to contain a little more useful information about
the application, since when the root logger's log level is WARN, that
information is never shown to the user.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#9816 from vanzin/shell-logging.
Make this lazy so that it can set the yarn mode before creating the securityManager.
Author: Tom Graves <tgraves@yahoo-inc.com>
Author: Thomas Graves <tgraves@staydecay.corp.gq1.yahoo.com>
Closes#8719 from tgravescs/SPARK-10549.
The bulk of the changes are on `transient` annotation on class parameter. Often the compiler doesn't generate a field for this parameters, so the the transient annotation would be unnecessary.
But if the class parameter are used in methods, then fields are created. So it is safer to keep the annotations.
The remainder are some potential bugs, and deprecated syntax.
Author: Luc Bourlier <luc.bourlier@typesafe.com>
Closes#8433 from skyluc/issue/sbt-2.11.
This patch fixes [[SPARK-9180]](https://issues.apache.org/jira/browse/SPARK-9180).
Users can now set the app name of spark-shell using `spark-shell --name "whatever"`.
Author: Kenichi Maehashi <webmaster@kenichimaehashi.com>
Closes#7512 from kmaehashi/fix-spark-shell-app-name and squashes the following commits:
e24991a [Kenichi Maehashi] use setIfMissing instead of setAppName
18aa4ad [Kenichi Maehashi] fix spark-shell to accept --name option
There are a few memory limits that people hit often and that we could
make higher, especially now that memory sizes have grown.
- spark.akka.frameSize: This defaults at 10 but is often hit for map
output statuses in large shuffles. This memory is not fully allocated
up-front, so we can just make this larger and still not affect jobs
that never sent a status that large. We increase it to 128.
- spark.executor.memory: Defaults at 512m, which is really small. We
increase it to 1g.
Author: Matei Zaharia <matei@databricks.com>
Closes#7586 from mateiz/configs and squashes the following commits:
ce0038a [Matei Zaharia] [SPARK-9244] Increase some memory defaults
This PR removes most of the code in the Spark REPL for Scala 2.11 and leaves just a couple of overridden methods in `SparkILoop` in order to:
- change welcome message
- restrict available commands (like `:power`)
- initialize Spark context
The two codebases have diverged and it's extremely hard to backport fixes from the upstream REPL. This somewhat radical step is absolutely necessary in order to fix other REPL tickets (like SPARK-8013 - Hive Thrift server for 2.11). BTW, the Scala REPL has fixed the serialization-unfriendly wrappers thanks to ScrapCodes's work in [#4522](https://github.com/scala/scala/pull/4522)
All tests pass and I tried the `spark-shell` on our Mesos cluster with some simple jobs (including with additional jars), everything looked good.
As soon as Scala 2.11.7 is out we need to upgrade and get a shaded `jline` dependency, clearing the way for SPARK-8013.
/cc pwendell
Author: Iulian Dragos <jaguarul@gmail.com>
Closes#6903 from dragos/issue/no-spark-repl-fork and squashes the following commits:
c596c6f [Iulian Dragos] Merge branch 'master' into issue/no-spark-repl-fork
2b1a305 [Iulian Dragos] Removed spaces around multiple imports.
0ce67a6 [Iulian Dragos] Remove -verbose flag for java compiler (added by mistake in an earlier commit).
10edaf9 [Iulian Dragos] Keep the jline dependency only in the 2.10 build.
529293b [Iulian Dragos] Add back Spark REPL files to rat-excludes, since they are part of the 2.10 real.
d85370d [Iulian Dragos] Remove jline dependency from the Spark REPL.
b541930 [Iulian Dragos] Merge branch 'master' into issue/no-spark-repl-fork
2b15962 [Iulian Dragos] Change jline dependency and bump Scala version.
b300183 [Iulian Dragos] Rename package and add license on top of the file, remove files from rat-excludes and removed `-Yrepl-sync` per reviewer’s request.
9d46d85 [Iulian Dragos] Fix SPARK-7944.
abcc7cb [Iulian Dragos] Remove the REPL forked code.
Author: Jonathan Alter <jonalter@users.noreply.github.com>
Closes#7093 from jonalter/SPARK-7977 and squashes the following commits:
ccd44cc [Jonathan Alter] Changed println to log in ThreadingSuite
7fcac3e [Jonathan Alter] Reverting to println in ThreadingSuite
10724b6 [Jonathan Alter] Changing some printlns to logs in tests
eeec1e7 [Jonathan Alter] Merge branch 'master' of github.com:apache/spark into SPARK-7977
0b1dcb4 [Jonathan Alter] More println cleanup
aedaf80 [Jonathan Alter] Merge branch 'master' of github.com:apache/spark into SPARK-7977
925fd98 [Jonathan Alter] Merge branch 'master' of github.com:apache/spark into SPARK-7977
0c16fa3 [Jonathan Alter] Replacing some printlns with logs
45c7e05 [Jonathan Alter] Merge branch 'master' of github.com:apache/spark into SPARK-7977
5c8e283 [Jonathan Alter] Allowing println in audit-release examples
5b50da1 [Jonathan Alter] Allowing printlns in example files
ca4b477 [Jonathan Alter] Merge branch 'master' of github.com:apache/spark into SPARK-7977
83ab635 [Jonathan Alter] Fixing new printlns
54b131f [Jonathan Alter] Merge branch 'master' of github.com:apache/spark into SPARK-7977
1cd8a81 [Jonathan Alter] Removing some unnecessary comments and printlns
b837c3a [Jonathan Alter] Disallowing println
Right now `unit-tests.log` are not of much value because we can't tell where the test boundaries are easily. This patch adds log statements before and after each test to outline the test boundaries, e.g.:
```
===== TEST OUTPUT FOR o.a.s.serializer.KryoSerializerSuite: 'kryo with parallelize for primitive arrays' =====
15/05/27 12:36:39.596 pool-1-thread-1-ScalaTest-running-KryoSerializerSuite INFO SparkContext: Starting job: count at KryoSerializerSuite.scala:230
15/05/27 12:36:39.596 dag-scheduler-event-loop INFO DAGScheduler: Got job 3 (count at KryoSerializerSuite.scala:230) with 4 output partitions (allowLocal=false)
15/05/27 12:36:39.596 dag-scheduler-event-loop INFO DAGScheduler: Final stage: ResultStage 3(count at KryoSerializerSuite.scala:230)
15/05/27 12:36:39.596 dag-scheduler-event-loop INFO DAGScheduler: Parents of final stage: List()
15/05/27 12:36:39.597 dag-scheduler-event-loop INFO DAGScheduler: Missing parents: List()
15/05/27 12:36:39.597 dag-scheduler-event-loop INFO DAGScheduler: Submitting ResultStage 3 (ParallelCollectionRDD[5] at parallelize at KryoSerializerSuite.scala:230), which has no missing parents
...
15/05/27 12:36:39.624 pool-1-thread-1-ScalaTest-running-KryoSerializerSuite INFO DAGScheduler: Job 3 finished: count at KryoSerializerSuite.scala:230, took 0.028563 s
15/05/27 12:36:39.625 pool-1-thread-1-ScalaTest-running-KryoSerializerSuite INFO KryoSerializerSuite:
***** FINISHED o.a.s.serializer.KryoSerializerSuite: 'kryo with parallelize for primitive arrays' *****
...
```
Author: Andrew Or <andrew@databricks.com>
Closes#6441 from andrewor14/demarcate-tests and squashes the following commits:
879b060 [Andrew Or] Fix compile after rebase
d622af7 [Andrew Or] Merge branch 'master' of github.com:apache/spark into demarcate-tests
017c8ba [Andrew Or] Merge branch 'master' of github.com:apache/spark into demarcate-tests
7790b6c [Andrew Or] Fix tests after logical merge conflict
c7460c0 [Andrew Or] Merge branch 'master' of github.com:apache/spark into demarcate-tests
c43ffc4 [Andrew Or] Fix tests?
8882581 [Andrew Or] Fix tests
ee22cda [Andrew Or] Fix log message
fa9450e [Andrew Or] Merge branch 'master' of github.com:apache/spark into demarcate-tests
12d1e1b [Andrew Or] Various whitespace changes (minor)
69cbb24 [Andrew Or] Make all test suites extend SparkFunSuite instead of FunSuite
bbce12e [Andrew Or] Fix manual things that cannot be covered through automation
da0b12f [Andrew Or] Add core tests as dependencies in all modules
f7d29ce [Andrew Or] Introduce base abstract class for all test suites
Visibility rules for static members are different in Scala and Java, and this case requires an explicit static import. Even though these are Java files, they are run through scaladoc, which enforces Scala rules.
Also reverted the commit that reverts the upgrade to 2.11.6
Author: Iulian Dragos <jaguarul@gmail.com>
Closes#6260 from dragos/issue/scaladoc-false-error and squashes the following commits:
f2e998e [Iulian Dragos] Revert "[HOTFIX] Revert "[SPARK-7092] Update spark scala version to 2.11.6""
0bad052 [Iulian Dragos] Fix scaladoc faux-error.
