## What changes were proposed in this pull request?
For randomForest classifier, if test data contains unseen labels, it will throw an error. The StringIndexer already has the handleInvalid logic. The patch add a new method to set the underlying StringIndexer handleInvalid logic.
This patch should also apply to other classifiers. This PR focuses on the main logic and randomForest classifier. I will do follow-up PR for other classifiers.
## How was this patch tested?
Add a new unit test based on the error case in the JIRA.
Author: wangmiao1981 <wm624@hotmail.com>
Closes#18496 from wangmiao1981/handle.
## What changes were proposed in this pull request?
SPARK-20979 added a new structured streaming source: Rate source. This patch adds the corresponding documentation to programming guide.
## How was this patch tested?
Tested by running jekyll locally.
Author: Prashant Sharma <prashant@apache.org>
Author: Prashant Sharma <prashsh1@in.ibm.com>
Closes#18562 from ScrapCodes/spark-21069/rate-source-docs.
This change exposes the internal code path in SparkConf that allows
configs to be read with variable substitution applied, and uses that
new method in SSLOptions so that SSL configs can reference other
variables, and more importantly, environment variables, providing
a secure way to provide passwords to Spark when using SSL.
The approach is a little bit hacky, but is the smallest change possible.
Otherwise, the concept of "namespaced configs" would have to be added
to the config system, which would create a lot of noise for not much
gain at this point.
Tested with added unit tests, and on a real cluster with SSL enabled.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#18394 from vanzin/SPARK-20379.try2.
## What changes were proposed in this pull request?
This pr modified code to use string types by default if `array` and `map` in functions have no argument. This behaviour is the same with Hive one;
```
hive> CREATE TEMPORARY TABLE t1 AS SELECT map();
hive> DESCRIBE t1;
_c0 map<string,string>
hive> CREATE TEMPORARY TABLE t2 AS SELECT array();
hive> DESCRIBE t2;
_c0 array<string>
```
## How was this patch tested?
Added tests in `DataFrameFunctionsSuite`.
Author: Takeshi Yamamuro <yamamuro@apache.org>
Closes#18516 from maropu/SPARK-21281.
## What changes were proposed in this pull request?
Adds method `summary` that allows user to specify which statistics and percentiles to calculate. By default it include the existing statistics from `describe` and quartiles (25th, 50th, and 75th percentiles) similar to Pandas. Also changes the implementation of `describe` to delegate to `summary`.
## How was this patch tested?
additional unit test
Author: Andrew Ray <ray.andrew@gmail.com>
Closes#18307 from aray/SPARK-21100.
## What changes were proposed in this pull request?
Revise rand comparison in BatchEvalPythonExecSuite
In BatchEvalPythonExecSuite, there are two cases using the case "rand() > 3"
Rand() generates a random value in [0, 1), it is wired to be compared with 3, use 0.3 instead
## How was this patch tested?
unit test
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Wang Gengliang <ltnwgl@gmail.com>
Closes#18560 from gengliangwang/revise_BatchEvalPythonExecSuite.
## What changes were proposed in this pull request?
Some dropped event will make the whole application behaves unexpectedly, e.g. some UI problem...we shall log the dropped event name to facilitate the debugging
## How was this patch tested?
Existing tests
Author: CodingCat <zhunansjtu@gmail.com>
Closes#16697 from CodingCat/SPARK-19358.
## What changes were proposed in this pull request?
un-aliased subquery is supported by Spark SQL for a long time. Its semantic was not well defined and had confusing behaviors, and it's not a standard SQL syntax, so we disallowed it in https://issues.apache.org/jira/browse/SPARK-20690 .
However, this is a breaking change, and we do have existing queries using un-aliased subquery. We should add the support back and fix its semantic.
This PR fixes the un-aliased subquery by assigning a default alias name.
After this PR, there is no syntax change from branch 2.2 to master, but we invalid a weird use case:
`SELECT v.i from (SELECT i FROM v)`. Now this query will throw analysis exception because users should not be able to use the qualifier inside a subquery.
## How was this patch tested?
new regression test
Author: Wenchen Fan <wenchen@databricks.com>
Closes#18559 from cloud-fan/sub-query.
## What changes were proposed in this pull request?
add the column name in the exception which is raised by unsupported data type.
## How was this patch tested?
+ [x] pass all tests.
Author: Yan Facai (颜发才) <facai.yan@gmail.com>
Closes#18523 from facaiy/ENH/vectorassembler_add_col.
## What changes were proposed in this pull request?
Add `toString` with options for `ConsoleSink` so it shows nicely in query progress.
**BEFORE**
```
"sink" : {
"description" : "org.apache.spark.sql.execution.streaming.ConsoleSink4b340441"
}
```
**AFTER**
```
"sink" : {
"description" : "ConsoleSink[numRows=10, truncate=false]"
}
```
/cc zsxwing tdas
## How was this patch tested?
Local build
Author: Jacek Laskowski <jacek@japila.pl>
Closes#18539 from jaceklaskowski/SPARK-21313-ConsoleSink-toString.
## What changes were proposed in this pull request?
Remove time metrics since it seems no way to measure it in non per-row tracking.
## How was this patch tested?
Existing tests.
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#18558 from viirya/SPARK-20703-followup.
## What changes were proposed in this pull request?
This PR implements bulk-copy for `ColumnVector.Array.to<type>Array()` methods (e.g. `toIntArray()`) in `ColumnVector.Array` by using `System.arrayCopy()` or `Platform.copyMemory()`.
Before this PR, when one of these method is called, the generic method in `ArrayData` is called. It is not fast since element-wise copy is performed.
This PR can improve performance of a benchmark program by 1.9x and 3.2x.
Without this PR
```
OpenJDK 64-Bit Server VM 1.8.0_131-8u131-b11-0ubuntu1.16.04.2-b11 on Linux 4.4.0-66-generic
Intel(R) Xeon(R) CPU E5-2667 v3 3.20GHz
Int Array Best/Avg Time(ms) Rate(M/s) Per Row(ns)
------------------------------------------------------------------------------------------------
ON_HEAP 586 / 628 14.3 69.9
OFF_HEAP 893 / 902 9.4 106.5
```
With this PR
```
OpenJDK 64-Bit Server VM 1.8.0_131-8u131-b11-0ubuntu1.16.04.2-b11 on Linux 4.4.0-66-generic
Intel(R) Xeon(R) CPU E5-2667 v3 3.20GHz
Int Array Best/Avg Time(ms) Rate(M/s) Per Row(ns)
------------------------------------------------------------------------------------------------
ON_HEAP 306 / 331 27.4 36.4
OFF_HEAP 282 / 287 29.8 33.6
```
Source program
```
(MemoryMode.ON_HEAP :: MemoryMode.OFF_HEAP :: Nil).foreach { memMode => {
val len = 8 * 1024 * 1024
val column = ColumnVector.allocate(len * 2, new ArrayType(IntegerType, false), memMode)
val data = column.arrayData
var i = 0
while (i < len) {
data.putInt(i, i)
i += 1
}
column.putArray(0, 0, len)
val benchmark = new Benchmark("Int Array", len, minNumIters = 20)
benchmark.addCase(s"$memMode") { iter =>
var i = 0
while (i < 50) {
column.getArray(0).toIntArray
i += 1
}
}
benchmark.run
}}
```
## How was this patch tested?
Added test suite
Author: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Closes#18425 from kiszk/SPARK-21217.
## What changes were proposed in this pull request?
Currently `ArrayConstructor` handles an array of typecode `'l'` as `int` when converting Python object in Python 2 into Java object, so if the value is larger than `Integer.MAX_VALUE` or smaller than `Integer.MIN_VALUE` then the overflow occurs.
```python
import array
data = [Row(longarray=array.array('l', [-9223372036854775808, 0, 9223372036854775807]))]
df = spark.createDataFrame(data)
df.show(truncate=False)
```
```
+----------+
|longarray |
+----------+
|[0, 0, -1]|
+----------+
```
This should be:
```
+----------------------------------------------+
|longarray |
+----------------------------------------------+
|[-9223372036854775808, 0, 9223372036854775807]|
+----------------------------------------------+
```
## How was this patch tested?
Added a test and existing tests.
Author: Takuya UESHIN <ueshin@databricks.com>
Closes#18553 from ueshin/issues/SPARK-21327.
## What changes were proposed in this pull request?
This is related with [SPARK-19918](https://issues.apache.org/jira/browse/SPARK-19918) and [SPARK-18362](https://issues.apache.org/jira/browse/SPARK-18362).
This PR proposes to use `TextFileFormat` and allow multiple input paths (but with a warning) when determining the number of features in LibSVM data source via an extra scan.
There are three points here:
- The main advantage of this change should be to remove file-listing bottlenecks in driver side.
- Another advantage is ones from using `FileScanRDD`. For example, I guess we can use `spark.sql.files.ignoreCorruptFiles` option when determining the number of features.
- We can unify the schema inference code path in text based data sources. This is also a preparation for [SPARK-21289](https://issues.apache.org/jira/browse/SPARK-21289).
## How was this patch tested?
Unit tests in `LibSVMRelationSuite`.
Closes#18288
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#18556 from HyukjinKwon/libsvm-schema.
## What changes were proposed in this pull request?
Making EventTimeWatermarkExec explicitly UnaryExecNode
/cc tdas zsxwing
## How was this patch tested?
Local build.
Author: Jacek Laskowski <jacek@japila.pl>
Closes#18509 from jaceklaskowski/EventTimeWatermarkExec-UnaryExecNode.
## What changes were proposed in this pull request?
SparkContext is shared by all sessions, we should not update its conf for only one session.
## How was this patch tested?
existing tests
Author: Wenchen Fan <wenchen@databricks.com>
Closes#18536 from cloud-fan/config.
## What changes were proposed in this pull request?
Few changes to the Structured Streaming documentation
- Clarify that the entire stream input table is not materialized
- Add information for Ganglia
- Add Kafka Sink to the main docs
- Removed a couple of leftover experimental tags
- Added more associated reading material and talk videos.
In addition, https://github.com/apache/spark/pull/16856 broke the link to the RDD programming guide in several places while renaming the page. This PR fixes those sameeragarwal cloud-fan.
- Added a redirection to avoid breaking internal and possible external links.
- Removed unnecessary redirection pages that were there since the separate scala, java, and python programming guides were merged together in 2013 or 2014.
## How was this patch tested?
(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#18485 from tdas/SPARK-21267.
## What changes were proposed in this pull request?
Rename org.apache.spark.sql.catalyst.plans.logical.statsEstimation.Range to ValueInterval.
The current naming is identical to logical operator "range".
Refactoring it to ValueInterval is more accurate.
## How was this patch tested?
unit test
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Wang Gengliang <ltnwgl@gmail.com>
Closes#18549 from gengliangwang/ValueInterval.
## What changes were proposed in this pull request?
Currently we can't produce a `Dataset` containing `Set` in SparkSQL. This PR tries to support serialization/deserialization of `Set`.
Because there's no corresponding internal data type in SparkSQL for a `Set`, the most proper choice for serializing a set should be an array.
## How was this patch tested?
Added unit tests.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#18416 from viirya/SPARK-21204.
## What changes were proposed in this pull request?
When data type is struct, InSet now uses TypeUtils.getInterpretedOrdering (similar to EqualTo) to build a TreeSet. In other cases it will use a HashSet as before (which should be faster). Similarly, In.eval uses Ordering.equiv instead of equals.
## How was this patch tested?
New test in SQLQuerySuite.
Author: Bogdan Raducanu <bogdan@databricks.com>
Closes#18455 from bogdanrdc/SPARK-21228.
## What changes were proposed in this pull request?
This PR Improvement in two:
1.With spark.shuffle.spill.diskWriteBufferSize configure diskWriteBufferSize of ShuffleExternalSorter.
when change the size of the diskWriteBufferSize to test `forceSorterToSpill`
The average performance of running 10 times is as follows:(their unit is MS).
```
diskWriteBufferSize: 1M 512K 256K 128K 64K 32K 16K 8K 4K
---------------------------------------------------------------------------------------
RecordSize = 2.5M 742 722 694 686 667 668 671 669 683
RecordSize = 1M 294 293 292 287 283 285 281 279 285
```
2.Remove outputBufferSizeInBytes and inputBufferSizeInBytes to initialize in mergeSpillsWithFileStream function.
## How was this patch tested?
The unit test.
Author: caoxuewen <cao.xuewen@zte.com.cn>
Closes#18174 from heary-cao/buffersize.
## What changes were proposed in this pull request?
Add missing test cases back and revise code style
Follow up the previous PR: https://github.com/apache/spark/pull/18479
## How was this patch tested?
Unit test
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Wang Gengliang <ltnwgl@gmail.com>
Closes#18548 from gengliangwang/stat_propagation_revise.
## What changes were proposed in this pull request?
1. move `StatisticsCollectionTestBase` to a separate file.
2. move some test cases to `StatisticsCollectionSuite` so that `hive/StatisticsSuite` only keeps tests that need hive support.
3. clear up some test cases.
## How was this patch tested?
Existing tests.
Author: wangzhenhua <wangzhenhua@huawei.com>
Author: Zhenhua Wang <wzh_zju@163.com>
Closes#18545 from wzhfy/cleanStatSuites.
## What changes were proposed in this pull request?
Right now in the UI, after SPARK-20213, we can show the operations to write data out. However, there is no way to associate metrics with data writes. We should show relative metrics on the operations.
#### Supported commands
This change supports updating metrics for file-based data writing operations, including `InsertIntoHadoopFsRelationCommand`, `InsertIntoHiveTable`.
Supported metrics:
* number of written files
* number of dynamic partitions
* total bytes of written data
* total number of output rows
* average writing data out time (ms)
* (TODO) min/med/max number of output rows per file/partition
* (TODO) min/med/max bytes of written data per file/partition
#### Commands not supported
`InsertIntoDataSourceCommand`, `SaveIntoDataSourceCommand`:
The two commands uses DataSource APIs to write data out, i.e., the logic of writing data out is delegated to the DataSource implementations, such as `InsertableRelation.insert` and `CreatableRelationProvider.createRelation`. So we can't obtain metrics from delegated methods for now.
`CreateHiveTableAsSelectCommand`, `CreateDataSourceTableAsSelectCommand` :
The two commands invokes other commands to write data out. The invoked commands can even write to non file-based data source. We leave them as future TODO.
#### How to update metrics of writing files out
A `RunnableCommand` which wants to update metrics, needs to override its `metrics` and provide the metrics data structure to `ExecutedCommandExec`.
The metrics are prepared during the execution of `FileFormatWriter`. The callback function passed to `FileFormatWriter` will accept the metrics and update accordingly.
There is a metrics updating function in `RunnableCommand`. In runtime, the function will be bound to the spark context and `metrics` of `ExecutedCommandExec` and pass to `FileFormatWriter`.
## How was this patch tested?
Updated unit tests.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#18159 from viirya/SPARK-20703-2.
Current "--jars (spark.jars)", "--files (spark.files)", "--py-files (spark.submit.pyFiles)" and "--archives (spark.yarn.dist.archives)" only support non-glob path. This is OK for most of the cases, but when user requires to add more jars, files into Spark, it is too verbose to list one by one. So here propose to add glob path support for resources.
Also improving the code of downloading resources.
## How was this patch tested?
UT added, also verified manually in local cluster.
Author: jerryshao <sshao@hortonworks.com>
Closes#18235 from jerryshao/SPARK-21012.
## What changes were proposed in this pull request?
Stopping query while it is being initialized can throw interrupt exception, in which case temporary checkpoint directories will not be deleted, and the test will fail.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#18442 from tdas/DatastreamReaderWriterSuite-fix.
## What changes were proposed in this pull request?
Corrects offsetInBytes calculation in UnsafeRow.writeToStream. Known failures include writes to some DataSources that have own SparkPlan implementations and cause EXCHANGE in writes.
## How was this patch tested?
Extended UnsafeRowSuite.writeToStream to include an UnsafeRow over byte array having non-zero offset.
Author: Sumedh Wale <swale@snappydata.io>
Closes#18535 from sumwale/SPARK-21312.
### What changes were proposed in this pull request?
This PR removes SQLConf parameters from the optimizer rules
### How was this patch tested?
The existing test cases
Author: gatorsmile <gatorsmile@gmail.com>
Closes#18533 from gatorsmile/rmSQLConfOptimizer.
## What changes were proposed in this pull request?
This PR uses `runUninterruptibly` to avoid that the clean up codes in StreamExecution is interrupted. It also removes an optimization in `runUninterruptibly` to make sure this method never throw `InterruptedException`.
## How was this patch tested?
Jenkins
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#18461 from zsxwing/SPARK-21248.
## What changes were proposed in this pull request?
This PR aims to bump Py4J in order to fix the following float/double bug.
Py4J 0.10.5 fixes this (https://github.com/bartdag/py4j/issues/272) and the latest Py4J is 0.10.6.
**BEFORE**
```
>>> df = spark.range(1)
>>> df.select(df['id'] + 17.133574204226083).show()
+--------------------+
|(id + 17.1335742042)|
+--------------------+
| 17.1335742042|
+--------------------+
```
**AFTER**
```
>>> df = spark.range(1)
>>> df.select(df['id'] + 17.133574204226083).show()
+-------------------------+
|(id + 17.133574204226083)|
+-------------------------+
| 17.133574204226083|
+-------------------------+
```
## How was this patch tested?
Manual.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#18546 from dongjoon-hyun/SPARK-21278.
### What changes were proposed in this pull request?
This PR is to remove SQLConf parameters from the parser-related classes.
### How was this patch tested?
The existing test cases.
Author: gatorsmile <gatorsmile@gmail.com>
Closes#18531 from gatorsmile/rmSQLConfParser.
## What changes were proposed in this pull request?
Support register Java UDAFs in PySpark so that user can use Java UDAF in PySpark. Besides that I also add api in `UDFRegistration`
## How was this patch tested?
Unit test is added
Author: Jeff Zhang <zjffdu@apache.org>
Closes#17222 from zjffdu/SPARK-19439.
## What changes were proposed in this pull request?
This change adds a new configuration option `spark.scheduler.listenerbus.eventqueue.size` to the configuration docs to specify the capacity of the spark listener bus event queue. Default value is 10000.
This is doc PR for [SPARK-15703](https://issues.apache.org/jira/browse/SPARK-15703).
I added option to the `Scheduling` section, however it might be more related to `Spark UI` section.
## How was this patch tested?
Manually verified correct rendering of configuration option.
Author: sadikovi <ivan.sadikov@lincolnuni.ac.nz>
Author: Ivan Sadikov <ivan.sadikov@team.telstra.com>
Closes#18476 from sadikovi/SPARK-20858.
## What changes were proposed in this pull request?
The old unit test not effect
## How was this patch tested?
unit test
Author: he.qiao <he.qiao17@zte.com.cn>
Closes#18511 from Geek-He/dev_0703.
## What changes were proposed in this pull request?
support to create [temporary] function with the keyword 'OR REPLACE' and 'IF NOT EXISTS'
## How was this patch tested?
manual test and added test cases
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: ouyangxiaochen <ou.yangxiaochen@zte.com.cn>
Closes#17681 from ouyangxiaochen/spark-419.
## What changes were proposed in this pull request?
Currently `RowEncoder` doesn't preserve nullability of `ArrayType` or `MapType`.
It returns always `containsNull = true` for `ArrayType`, `valueContainsNull = true` for `MapType` and also the nullability of itself is always `true`.
This pr fixes the nullability of them.
## How was this patch tested?
Add tests to check if `RowEncoder` preserves array/map nullability.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Author: Takuya UESHIN <ueshin@databricks.com>
Closes#13873 from ueshin/issues/SPARK-16167.
## What changes were proposed in this pull request?
Add offset to PySpark in GLM as in #16699.
## How was this patch tested?
Python test
Author: actuaryzhang <actuaryzhang10@gmail.com>
Closes#18534 from actuaryzhang/pythonOffset.
## What changes were proposed in this pull request?
Add `returnNullable` to `StaticInvoke` the same as #15780 is trying to add to `Invoke` and modify to handle properly.
## How was this patch tested?
Existing tests.
Author: Takuya UESHIN <ueshin@happy-camper.st>
Author: Takuya UESHIN <ueshin@databricks.com>
Closes#16056 from ueshin/issues/SPARK-18623.
## What changes were proposed in this pull request?
For these collection-related encoder expressions, we don't need to create `isNull` variable if the loop element is not nullable.
## How was this patch tested?
existing tests.
Author: Wenchen Fan <wenchen@databricks.com>
Closes#18529 from cloud-fan/minor.
## What changes were proposed in this pull request?
Add doc for methods that were left out, and fix various style and consistency issues.
Author: actuaryzhang <actuaryzhang10@gmail.com>
Closes#18493 from actuaryzhang/sparkRDocCleanup.
## What changes were proposed in this pull request?
`ExternalMapToCatalyst` should null-check map key prior to converting to internal value to throw an appropriate Exception instead of something like NPE.
## How was this patch tested?
Added a test and existing tests.
Author: Takuya UESHIN <ueshin@databricks.com>
Closes#18524 from ueshin/issues/SPARK-21300.
### What changes were proposed in this pull request?
It is strange to see the following error message. Actually, the column is from another table.
```
cannot resolve '`right.a`' given input columns: [a, c, d];
```
After the PR, the error message looks like
```
cannot resolve '`right.a`' given input columns: [left.a, right.c, right.d];
```
### How was this patch tested?
Added a test case
Author: gatorsmile <gatorsmile@gmail.com>
Closes#18520 from gatorsmile/removeSQLConf.
## What changes were proposed in this pull request?
After running R tests in local build, it outputs Rplots.pdf. This one should be ignored in the git repository.
Author: wangmiao1981 <wm624@hotmail.com>
Closes#18518 from wangmiao1981/ignore.
## What changes were proposed in this pull request?
Grouped documentation for column window methods.
Author: actuaryzhang <actuaryzhang10@gmail.com>
Closes#18481 from actuaryzhang/sparkRDocWindow.
## What changes were proposed in this pull request?
The scal() and creation of newCenter vector is done in the driver, after a collectAsMap operation while it could be done in the distributed RDD.
This PR moves this code before the collectAsMap for more efficiency
## How was this patch tested?
This was tested manually by running the KMeansExample and verifying that the new code ran without error and gave same output as before.
Author: dardelet <guillaumegorp@gmail.com>
Author: Guillaume Dardelet <dardelet@users.noreply.github.com>
Closes#18491 from dardelet/move-center-calculation-to-distributed-map-kmean.
## What changes were proposed in this pull request?
`SessionState` is designed to be created lazily. However, in reality, it created immediately in `SparkSession.Builder.getOrCreate` ([here](https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/SparkSession.scala#L943)).
This PR aims to recover the lazy behavior by keeping the options into `initialSessionOptions`. The benefit is like the following. Users can start `spark-shell` and use RDD operations without any problems.
**BEFORE**
```scala
$ bin/spark-shell
java.lang.IllegalArgumentException: Error while instantiating 'org.apache.spark.sql.hive.HiveSessionStateBuilder'
...
Caused by: org.apache.spark.sql.AnalysisException:
org.apache.hadoop.hive.ql.metadata.HiveException:
MetaException(message:java.security.AccessControlException:
Permission denied: user=spark, access=READ,
inode="/apps/hive/warehouse":hive:hdfs:drwx------
```
As reported in SPARK-20256, this happens when the warehouse directory is not allowed for this user.
**AFTER**
```scala
$ bin/spark-shell
...
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 2.3.0-SNAPSHOT
/_/
Using Scala version 2.11.8 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_112)
Type in expressions to have them evaluated.
Type :help for more information.
scala> sc.range(0, 10, 1).count()
res0: Long = 10
```
## How was this patch tested?
Manual.
This closes#18512 .
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#18501 from dongjoon-hyun/SPARK-20256.
## What changes were proposed in this pull request?
when creating table like following:
> create table timestamp_test(id int(11), time_stamp timestamp not null default current_timestamp);
The result of Excuting "insert into timestamp_test values (111, null)" is different between Spark and JDBC.
```
mysql> select * from timestamp_test;
+------+---------------------+
| id | time_stamp |
+------+---------------------+
| 111 | 1970-01-01 00:00:00 | -> spark
| 111 | 2017-06-27 19:32:38 | -> mysql
+------+---------------------+
2 rows in set (0.00 sec)
```
Because in such case ```StructField.nullable``` is false, so the generated codes of ```InvokeLike``` and ```BoundReference``` don't check whether the field is null or not. Instead, they directly use ```CodegenContext.INPUT_ROW.getLong(1)```, however, ```UnsafeRow.setNullAt(1)``` will put 0 in the underlying memory.
The PR will ```always``` set ```StructField.nullable``` true after obtaining metadata from jdbc connection, Since we can insert null to not null timestamp column in MySQL. In this way, spark will propagate null to underlying DB engine, and let DB to choose how to process NULL.
## How was this patch tested?
Added tests.
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: YIHAODIAN\wangshuangshuang <wangshuangshuang@yihaodian.com>
Author: Shuangshuang Wang <wsszone@gmail.com>
Closes#18445 from shuangshuangwang/SPARK-19726.
### What changes were proposed in this pull request?
SQLConf is moved to Catalyst. We are adding more and more test cases for verifying the conf-specific behaviors. It is nice to add a helper function to simplify the test cases.
### How was this patch tested?
N/A
Author: gatorsmile <gatorsmile@gmail.com>
Closes#18469 from gatorsmile/withSQLConf.
## What changes were proposed in this pull request?
**Context**
While reviewing https://github.com/apache/spark/pull/17227, I realised here we type-dispatch per record. The PR itself is fine in terms of performance as is but this prints a prefix, `"obj"` in exception message as below:
```
from pyspark.sql.types import *
schema = StructType([StructField('s', IntegerType(), nullable=False)])
spark.createDataFrame([["1"]], schema)
...
TypeError: obj.s: IntegerType can not accept object '1' in type <type 'str'>
```
I suggested to get rid of this but during investigating this, I realised my approach might bring a performance regression as it is a hot path.
Only for SPARK-19507 and https://github.com/apache/spark/pull/17227, It needs more changes to cleanly get rid of the prefix and I rather decided to fix both issues together.
**Propersal**
This PR tried to
- get rid of per-record type dispatch as we do in many code paths in Scala so that it improves the performance (roughly ~25% improvement) - SPARK-21296
This was tested with a simple code `spark.createDataFrame(range(1000000), "int")`. However, I am quite sure the actual improvement in practice is larger than this, in particular, when the schema is complicated.
- improve error message in exception describing field information as prose - SPARK-19507
## How was this patch tested?
Manually tested and unit tests were added in `python/pyspark/sql/tests.py`.
Benchmark - codes: https://gist.github.com/HyukjinKwon/c3397469c56cb26c2d7dd521ed0bc5a3
Error message - codes: https://gist.github.com/HyukjinKwon/b1b2c7f65865444c4a8836435100e398
**Before**
Benchmark:
- Results: https://gist.github.com/HyukjinKwon/4a291dab45542106301a0c1abcdca924
Error message
- Results: https://gist.github.com/HyukjinKwon/57b1916395794ce924faa32b14a3fe19
**After**
Benchmark
- Results: https://gist.github.com/HyukjinKwon/21496feecc4a920e50c4e455f836266e
Error message
- Results: https://gist.github.com/HyukjinKwon/7a494e4557fe32a652ce1236e504a395Closes#17227
Author: hyukjinkwon <gurwls223@gmail.com>
Author: David Gingrich <david@textio.com>
Closes#18521 from HyukjinKwon/python-type-dispatch.
## What changes were proposed in this pull request?
Currently, running the shell below:
```bash
$ ./bin/spark-submit tmp.R a b c
```
with R file, `tmp.R` as below:
```r
#!/usr/bin/env Rscript
library(SparkR)
sparkRSQL.init(sparkR.init(master = "local"))
collect(createDataFrame(list(list(1))))
print(commandArgs(trailingOnly = TRUE))
```
working fine as below:
```bash
_1
1 1
[1] "a" "b" "c"
```
However, it looks not printed in usage documentation as below:
```bash
$ ./bin/spark-submit
```
```
Usage: spark-submit [options] <app jar | python file> [app arguments]
...
```
For `./bin/sparkR`, it looks fine as below:
```bash
$ ./bin/sparkR tmp.R
```
```
Running R applications through 'sparkR' is not supported as of Spark 2.0.
Use ./bin/spark-submit <R file>
```
Running the script below:
```bash
$ ./bin/spark-submit
```
**Before**
```
Usage: spark-submit [options] <app jar | python file> [app arguments]
...
```
**After**
```
Usage: spark-submit [options] <app jar | python file | R file> [app arguments]
...
```
## How was this patch tested?
Manually tested.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#18505 from HyukjinKwon/minor-doc-summit.
