### What changes were proposed in this pull request?
Currently, only the non-static public SQL configurations are dump to public doc, we'd better also add those static public ones as the command `set -v`
This PR force call StaticSQLConf to buildStaticConf.
### Why are the changes needed?
Fix missing SQL configurations in doc
### Does this PR introduce any user-facing change?
NO
### How was this patch tested?
add unit test and verify locally to see if public static SQL conf is in `docs/sql-config.html`
Closes#28274 from yaooqinn/SPARK-31498.
Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
**Hive 2.3.7** fixed these issues:
- HIVE-21508: ClassCastException when initializing HiveMetaStoreClient on JDK10 or newer
- HIVE-21980:Parsing time can be high in case of deeply nested subqueries
- HIVE-22249: Support Parquet through HCatalog
### Why are the changes needed?
Fix CCE during creating HiveMetaStoreClient in JDK11 environment: [SPARK-29245](https://issues.apache.org/jira/browse/SPARK-29245).
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
- [x] Test Jenkins with Hadoop 2.7 (https://github.com/apache/spark/pull/28148#issuecomment-616757840)
- [x] Test Jenkins with Hadoop 3.2 on JDK11 (https://github.com/apache/spark/pull/28148#issuecomment-616294353)
- [x] Manual test with remote hive metastore.
Hive side:
```
export JAVA_HOME=/usr/lib/jdk1.8.0_221
export PATH=$JAVA_HOME/bin:$PATH
cd /usr/lib/hive-2.3.6 # Start Hive metastore with Hive 2.3.6
bin/schematool -dbType derby -initSchema --verbose
bin/hive --service metastore
```
Spark side:
```
export JAVA_HOME=/usr/lib/jdk-11.0.3
export PATH=$JAVA_HOME/bin:$PATH
build/sbt clean package -Phive -Phadoop-3.2 -Phive-thriftserver
export SPARK_PREPEND_CLASSES=true
bin/spark-sql --conf spark.hadoop.hive.metastore.uris=thrift://localhost:9083
```
Closes#28148 from wangyum/SPARK-31381.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR is the follow-up PR of https://github.com/apache/spark/pull/28003
- add a migration guide
- add an end-to-end test case.
### Why are the changes needed?
The original PR made the major behavior change in the user-facing RESET command.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
Added a new end-to-end test
Closes#28265 from gatorsmile/spark-31234followup.
Authored-by: gatorsmile <gatorsmile@gmail.com>
Signed-off-by: gatorsmile <gatorsmile@gmail.com>
### What changes were proposed in this pull request?
This adds newly supported `nfs` volume type description into the document for Apache Spark 3.1.0.
### Why are the changes needed?
To complete the document.
### Does this PR introduce any user-facing change?
Yes. (Doc)
### How was this patch tested?
Manually generate doc and check it.
```
SKIP_API=1 jekyll build
```
Closes#28236 from dongjoon-hyun/SPARK-NFS-DOC.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Update the document and shell script to warn user about the deprecation of multiple workers on the same host support.
### Why are the changes needed?
This is a sub-task of [SPARK-30978](https://issues.apache.org/jira/browse/SPARK-30978), which plans to totally remove support of multiple workers in Spark 3.1. This PR makes the first step to deprecate it firstly in Spark 3.0.
### Does this PR introduce any user-facing change?
Yeah, user see warning when they run start worker script.
### How was this patch tested?
Tested manually.
Closes#27768 from Ngone51/deprecate_spark_worker_instances.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Xingbo Jiang <xingbo.jiang@databricks.com>
### What changes were proposed in this pull request?
Add a SQL example for UDAF
### Why are the changes needed?
To make SQL Reference complete
### Does this PR introduce any user-facing change?
Yes.
Add the following page, also change ```Sql``` to ```SQL``` in the example tab for all the sql examples.
<img width="1110" alt="Screen Shot 2020-04-13 at 6 09 24 PM" src="https://user-images.githubusercontent.com/13592258/79175240-06cd7400-7db2-11ea-8f3e-af71a591a64b.png">
### How was this patch tested?
Manually build and check
Closes#28209 from huaxingao/udf_followup.
Authored-by: Huaxin Gao <huaxing@us.ibm.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR intends to drop the built-in function pages from SQL references. We've already had a complete list of built-in functions in the API documents.
See related discussions for more details:
https://github.com/apache/spark/pull/28170#issuecomment-611917191
### Why are the changes needed?
For better SQL documents.
### Does this PR introduce any user-facing change?
### How was this patch tested?
Manually checked.
Closes#28203 from maropu/DropBuiltinFunctionDocs.
Authored-by: Takeshi Yamamuro <yamamuro@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR intends to clean up the SQL documents in `doc/sql-ref*`.
Main changes are as follows;
- Fixes wrong syntaxes and capitalize sub-titles
- Adds some DDL queries in `Examples` so that users can run examples there
- Makes query output in `Examples` follows the `Dataset.showString` (right-aligned) format
- Adds/Removes spaces, Indents, or blank lines to follow the format below;
```
---
license...
---
### Description
Writes what's the syntax is.
### Syntax
{% highlight sql %}
SELECT...
WHERE... // 4 indents after the second line
...
{% endhighlight %}
### Parameters
<dl>
<dt><code><em>Param Name</em></code></dt>
<dd>
Param Description
</dd>
...
</dl>
### Examples
{% highlight sql %}
-- It is better that users are able to execute example queries here.
-- So, we prepare test data in the first section if possible.
CREATE TABLE t (key STRING, value DOUBLE);
INSERT INTO t VALUES
('a', 1.0), ('a', 2.0), ('b', 3.0), ('c', 4.0);
-- query output has 2 indents and it follows the `Dataset.showString`
-- format (right-aligned).
SELECT * FROM t;
+---+-----+
|key|value|
+---+-----+
| a| 1.0|
| a| 2.0|
| b| 3.0|
| c| 4.0|
+---+-----+
-- Query statements after the second line have 4 indents.
SELECT key, SUM(value)
FROM t
GROUP BY key;
+---+----------+
|key|sum(value)|
+---+----------+
| c| 4.0|
| b| 3.0|
| a| 3.0|
+---+----------+
...
{% endhighlight %}
### Related Statements
* [XXX](xxx.html)
* ...
```
### Why are the changes needed?
The most changes of this PR are pretty minor, but I think the consistent formats/rules to write documents are important for long-term maintenance in our community
### Does this PR introduce any user-facing change?
Yes.
### How was this patch tested?
Manually checked.
Closes#28151 from maropu/MakeRightAligned.
Authored-by: Takeshi Yamamuro <yamamuro@apache.org>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
This pull request adds SparkR wrapper for `FMRegressor`:
- Supporting ` org.apache.spark.ml.r.FMRegressorWrapper`.
- `FMRegressionModel` S4 class.
- Corresponding `spark.fmRegressor`, `predict`, `summary` and `write.ml` generics.
- Corresponding docs and tests.
### Why are the changes needed?
Feature parity.
### Does this PR introduce any user-facing change?
No (new API).
### How was this patch tested?
New unit tests.
Closes#27571 from zero323/SPARK-30819.
Authored-by: zero323 <mszymkiewicz@gmail.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
Document Spark integration with Hive UDFs/UDAFs/UDTFs
### Why are the changes needed?
To make SQL Reference complete
### Does this PR introduce any user-facing change?
Yes
<img width="1031" alt="Screen Shot 2020-04-02 at 2 22 42 PM" src="https://user-images.githubusercontent.com/13592258/78301971-cc7cf080-74ee-11ea-93c8-7d4c75213b47.png">
### How was this patch tested?
Manually build and check
Closes#28104 from huaxingao/hive-udfs.
Lead-authored-by: Huaxin Gao <huaxing@us.ibm.com>
Co-authored-by: Takeshi Yamamuro <yamamuro@apache.org>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
This PR explicitly mention that the requirement of Iterator of Series to Iterator of Series and Iterator of Multiple Series to Iterator of Series (previously Scalar Iterator pandas UDF).
The actual limitation of this UDF is the same length of the _entire input and output_, instead of each series's length. Namely you can do something as below:
```python
from typing import Iterator, Tuple
import pandas as pd
from pyspark.sql.functions import pandas_udf
pandas_udf("long")
def func(
iterator: Iterator[pd.Series]) -> Iterator[pd.Series]:
return iter([pd.concat(iterator)])
spark.range(100).select(func("id")).show()
```
This characteristic allows you to prefetch the data from the iterator to speed up, compared to the regular Scalar to Scalar (previously Scalar pandas UDF).
### Why are the changes needed?
To document the correct restriction and characteristics of a feature.
### Does this PR introduce any user-facing change?
Yes in the documentation but only in unreleased branches.
### How was this patch tested?
Github Actions should test the documentation build
Closes#28160 from HyukjinKwon/SPARK-30722-followup.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This pull request adds SparkR wrapper for `LinearRegression`
- Supporting `org.apache.spark.ml.rLinearRegressionWrapper`.
- `LinearRegressionModel` S4 class.
- Corresponding `spark.lm` predict, summary and write.ml generics.
- Corresponding docs and tests.
### Why are the changes needed?
Feature parity.
### Does this PR introduce any user-facing change?
No (new API).
### How was this patch tested?
New unit tests.
Closes#27593 from zero323/SPARK-30818.
Authored-by: zero323 <mszymkiewicz@gmail.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
HyukjinKwon have ported back all the PR about version to branch-3.0.
I make a double check and found GraphX table lost version head.
This PR will fix the issue.
HyukjinKwon, please help me merge this PR to master and branch-3.0
### Why are the changes needed?
Add version head of GraphX table
### Does this PR introduce any user-facing change?
'No'.
### How was this patch tested?
Jenkins test.
Closes#28149 from beliefer/fix-head-of-graphx-table.
Authored-by: beliefer <beliefer@163.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Previously, user can issue `SHOW TABLES` to get info of both tables and views.
This PR (SPARK-31113) implements `SHOW VIEWS` SQL command similar to HIVE to get views only.(https://cwiki.apache.org/confluence/display/Hive/LanguageManual+DDL#LanguageManualDDL-ShowViews)
**Hive** -- Only show view names
```
hive> SHOW VIEWS;
OK
view_1
view_2
...
```
**Spark(Hive-Compatible)** -- Only show view names, used in tests and `SparkSQLDriver` for CLI applications
```
SHOW VIEWS IN showdb;
view_1
view_2
...
```
**Spark** -- Show more information database/viewName/isTemporary
```
spark-sql> SHOW VIEWS;
userdb view_1 false
userdb view_2 false
...
```
### Why are the changes needed?
`SHOW VIEWS` command provides better granularity to only get information of views.
### Does this PR introduce any user-facing change?
Add new `SHOW VIEWS` SQL command
### How was this patch tested?
Add new test `show-views.sql` and pass existing tests
Closes#27897 from Eric5553/ShowViews.
Authored-by: Eric Wu <492960551@qq.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This pull request adds SparkR wrapper for `FMClassifier`:
- Supporting ` org.apache.spark.ml.r.FMClassifierWrapper`.
- `FMClassificationModel` S4 class.
- Corresponding `spark.fmClassifier`, `predict`, `summary` and `write.ml` generics.
- Corresponding docs and tests.
### Why are the changes needed?
Feature parity.
### Does this PR introduce any user-facing change?
No (new API).
### How was this patch tested?
New unit tests.
Closes#27570 from zero323/SPARK-30820.
Authored-by: zero323 <mszymkiewicz@gmail.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
Add migration guide for extracting second from datetimes
### Why are the changes needed?
doc the behavior change for extract expression
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
N/A, just passing jenkins
Closes#28140 from yaooqinn/SPARK-29311.
Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This PR intends to improve the SQL document of `GROUP BY`; it added the description about FILTER clauses of aggregate functions.
### Why are the changes needed?
To improve the SQL documents
### Does this PR introduce any user-facing change?
Yes.
<img src="https://user-images.githubusercontent.com/692303/78558612-e2234a80-784d-11ea-9353-b3feac4d57a7.png" width="500">
### How was this patch tested?
Manually checked.
Closes#28134 from maropu/SPARK-31358.
Authored-by: Takeshi Yamamuro <yamamuro@apache.org>
Signed-off-by: Takeshi Yamamuro <yamamuro@apache.org>
### What changes were proposed in this pull request?
This PR fixes the outdated requirement for `spark.dynamicAllocation.enabled=true`.
### Why are the changes needed?
This is found during 3.0.0 RC1 document review and testing. As described at `spark.dynamicAllocation.shuffleTracking.enabled` in the same table, we can enabled Dynamic Allocation without external shuffle service.
### Does this PR introduce any user-facing change?
Yes. (Doc.)
### How was this patch tested?
Manually generate the doc by `SKIP_API=1 jekyll build`
**BEFORE**
**AFTER**
Closes#28132 from dongjoon-hyun/SPARK-DA-DOC.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR intends to add a new SQL config for controlling a plan explain mode in the events of (e.g., `SparkListenerSQLExecutionStart` and `SparkListenerSQLAdaptiveExecutionUpdate`) SQL listeners. In the current master, the output of `QueryExecution.toString` (this is equivalent to the "extended" explain mode) is stored in these events. I think it is useful to control the content via `SQLConf`. For example, the query "Details" content (TPCDS q66 query) of a SQL tab in a Spark web UI will be changed as follows;
Before this PR:
After this PR:
### Why are the changes needed?
For better usability.
### Does this PR introduce any user-facing change?
Yes; since Spark 3.1, SQL UI data adopts the `formatted` mode for the query plan explain results. To restore the behavior before Spark 3.0, you can set `spark.sql.ui.explainMode` to `extended`.
### How was this patch tested?
Added unit tests.
Closes#28097 from maropu/SPARK-31325.
Authored-by: Takeshi Yamamuro <yamamuro@apache.org>
Signed-off-by: Gengliang Wang <gengliang.wang@databricks.com>
### What changes were proposed in this pull request?
For the stage level scheduling feature, add the ability to optionally merged resource profiles if they were specified on multiple RDD within a stage. There is a config to enable this feature, its off by default (spark.scheduler.resourceProfile.mergeConflicts). When the config is set to true, Spark will merge the profiles selecting the max value of each resource (cores, memory, gpu, etc). further documentation will be added with SPARK-30322.
This also added in the ability to check if an equivalent resource profile already exists. This is so that if a user is running stages and combining the same profiles over and over again we don't get an explosion in the number of profiles.
### Why are the changes needed?
To allow users to specify resource on multiple RDD and not worry as much about if they go into the same stage and fail.
### Does this PR introduce any user-facing change?
Yes, when the config is turned on it now merges the profiles instead of errorring out.
### How was this patch tested?
Unit tests
Closes#28053 from tgravescs/SPARK-29153.
Lead-authored-by: Thomas Graves <tgraves@apache.org>
Co-authored-by: Thomas Graves <tgraves@nvidia.com>
Signed-off-by: Thomas Graves <tgraves@apache.org>
### What changes were proposed in this pull request?
This PR adds description for `Shuffle Write Time` to `web-ui.md`.
### Why are the changes needed?
#27837 added `Shuffle Write Time` metric to task metrics summary but it's not documented yet.
### Does this PR introduce any user-facing change?
Yes.
We can see the description for `Shuffle Write Time` in the new `web-ui.html`.
<img width="956" alt="shuffle-write-time-description" src="https://user-images.githubusercontent.com/4736016/78175342-a9722280-7495-11ea-9cc6-62c6f3619aa3.png">
### How was this patch tested?
Built docs by `SKIP_API=1 jekyll build` in `doc` directory and then confirmed `web-ui.html`.
Closes#28093 from sarutak/SPARK-31073-doc.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Add back the deprecated R APIs removed by https://github.com/apache/spark/pull/22843/ and https://github.com/apache/spark/pull/22815.
These APIs are
- `sparkR.init`
- `sparkRSQL.init`
- `sparkRHive.init`
- `registerTempTable`
- `createExternalTable`
- `dropTempTable`
No need to port the function such as
```r
createExternalTable <- function(x, ...) {
dispatchFunc("createExternalTable(tableName, path = NULL, source = NULL, ...)", x, ...)
}
```
because this was for the backward compatibility when SQLContext exists before assuming from https://github.com/apache/spark/pull/9192, but seems we don't need it anymore since SparkR replaced SQLContext with Spark Session at https://github.com/apache/spark/pull/13635.
### Why are the changes needed?
Amend Spark's Semantic Versioning Policy
### Does this PR introduce any user-facing change?
Yes
The removed R APIs are put back.
### How was this patch tested?
Add back the removed tests
Closes#28058 from huaxingao/r.
Authored-by: Huaxin Gao <huaxing@us.ibm.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR (SPARK-30775) aims to improve the description of the executor metrics in the monitoring documentation.
### Why are the changes needed?
Improve and clarify monitoring documentation by:
- adding reference to the Prometheus end point, as implemented in [SPARK-29064]
- extending the list and descripion of executor metrics, following up from [SPARK-27157]
### Does this PR introduce any user-facing change?
Documentation update.
### How was this patch tested?
n.a.
Closes#27526 from LucaCanali/docPrometheusMetricsFollowupSpark29064.
Authored-by: Luca Canali <luca.canali@cern.ch>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR (SPARK-31293) fixes wrong command examples, parameter descriptions and help message format for Amazon Kinesis integration with Spark Streaming.
### Why are the changes needed?
To improve usability of those commands.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
I ran the fixed commands manually and confirmed they worked as expected.
Closes#28063 from sekikn/SPARK-31293.
Authored-by: Kengo Seki <sekikn@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Fix a broken link and make the relevant docs reference to the new doc
### Why are the changes needed?
### Does this PR introduce any user-facing change?
Yes, make CACHE TABLE, UNCACHE TABLE, CLEAR CACHE, REFRESH TABLE link to the new doc
### How was this patch tested?
Manually build and check
Closes#28065 from huaxingao/spark-30363-follow-up.
Authored-by: Huaxin Gao <huaxing@us.ibm.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
This PR adds "Pandas Function API" into the menu.
### Why are the changes needed?
To be consistent and to make easier to navigate.
### Does this PR introduce any user-facing change?
No, master only.
### How was this patch tested?
Manually verified by `SKIP_API=1 jekyll build`.
Closes#28054 from HyukjinKwon/followup-spark-30722.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Based on the discussion in the mailing list [[Proposal] Modification to Spark's Semantic Versioning Policy](http://apache-spark-developers-list.1001551.n3.nabble.com/Proposal-Modification-to-Spark-s-Semantic-Versioning-Policy-td28938.html) , this PR is to add back the following APIs whose maintenance cost are relatively small.
- HiveContext
- createExternalTable APIs
### Why are the changes needed?
Avoid breaking the APIs that are commonly used.
### Does this PR introduce any user-facing change?
Adding back the APIs that were removed in 3.0 branch does not introduce the user-facing changes, because Spark 3.0 has not been released.
### How was this patch tested?
add a new test suite for createExternalTable APIs.
Closes#27815 from gatorsmile/addAPIsBack.
Lead-authored-by: gatorsmile <gatorsmile@gmail.com>
Co-authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: gatorsmile <gatorsmile@gmail.com>
### What changes were proposed in this pull request?
Skew join handling comes with an overhead: we need to read some data repeatedly. We should treat a partition as skewed if it's large enough so that it's beneficial to do so.
Currently the size threshold is the advisory partition size, which is 64 MB by default. This is not large enough for the skewed partition size threshold.
This PR adds a new config for the threshold and set default value as 256 MB.
### Why are the changes needed?
Avoid skew join handling that may introduce a perf regression.
### Does this PR introduce any user-facing change?
no
### How was this patch tested?
existing tests
Closes#27967 from cloud-fan/aqe.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Currently, ResetCommand clear all configurations, including sql configs, static sql configs and spark context level configs.
for example:
```sql
spark-sql> set xyz=abc;
xyz abc
spark-sql> set;
spark.app.id local-1585055396930
spark.app.name SparkSQL::10.242.189.214
spark.driver.host 10.242.189.214
spark.driver.port 65094
spark.executor.id driver
spark.jars
spark.master local[*]
spark.sql.catalogImplementation hive
spark.sql.hive.version 1.2.1
spark.submit.deployMode client
xyz abc
spark-sql> reset;
spark-sql> set;
spark-sql> set spark.sql.hive.version;
spark.sql.hive.version 1.2.1
spark-sql> set spark.app.id;
spark.app.id <undefined>
```
In this PR, we restore spark confs to RuntimeConfig after it is cleared
### Why are the changes needed?
reset command overkills configs which are static.
### Does this PR introduce any user-facing change?
yes, the ResetCommand do not change static configs now
### How was this patch tested?
add ut
Closes#28003 from yaooqinn/SPARK-31234.
Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Update ml-guide to include ```MulticlassClassificationEvaluator``` weight support in highlights
### Why are the changes needed?
```MulticlassClassificationEvaluator``` weight support is very important, so should include it in highlights
### Does this PR introduce any user-facing change?
Yes
after:
### How was this patch tested?
manually build and check
Closes#28031 from huaxingao/highlights-followup.
Authored-by: Huaxin Gao <huaxing@us.ibm.com>
Signed-off-by: zhengruifeng <ruifengz@foxmail.com>
### What changes were proposed in this pull request?
Spark introduced CHAR type for hive compatibility but it only works for hive tables. CHAR type is never documented and is treated as STRING type for non-Hive tables.
However, this leads to confusing behaviors
**Apache Spark 3.0.0-preview2**
```
spark-sql> CREATE TABLE t(a CHAR(3));
spark-sql> INSERT INTO TABLE t SELECT 'a ';
spark-sql> SELECT a, length(a) FROM t;
a 2
```
**Apache Spark 2.4.5**
```
spark-sql> CREATE TABLE t(a CHAR(3));
spark-sql> INSERT INTO TABLE t SELECT 'a ';
spark-sql> SELECT a, length(a) FROM t;
a 3
```
According to the SQL standard, `CHAR(3)` should guarantee all the values are of length 3. Since `CHAR(3)` is treated as STRING so Spark doesn't guarantee it.
This PR forbids CHAR type in non-Hive tables as it's not supported correctly.
### Why are the changes needed?
avoid confusing/wrong behavior
### Does this PR introduce any user-facing change?
yes, now users can't create/alter non-Hive tables with CHAR type.
### How was this patch tested?
new tests
Closes#27902 from cloud-fan/char.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
https://github.com/apache/spark/pull/26412 introduced a behavior change that `date_add`/`date_sub` functions can't accept string and double values in the second parameter. This is reasonable as it's error-prone to cast string/double to int at runtime.
However, using string literals as function arguments is very common in SQL databases. To avoid breaking valid use cases that the string literal is indeed an integer, this PR proposes to add ansi_cast for string literal in date_add/date_sub functions. If the string value is not a valid integer, we fail at query compiling time because of constant folding.
### Why are the changes needed?
avoid breaking changes
### Does this PR introduce any user-facing change?
Yes, now 3.0 can run `date_add('2011-11-11', '1')` like 2.4
### How was this patch tested?
new tests.
Closes#27965 from cloud-fan/string.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
`INSERT OVERWRITE DIRECTORY` can only use file format (class implements `org.apache.spark.sql.execution.datasources.FileFormat`). This PR fixes it and other minor improvement.
### Why are the changes needed?
### Does this PR introduce any user-facing change?
### How was this patch tested?
Closes#27891 from cloud-fan/doc.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Change BLAS for part of level-1 routines(axpy, dot, scal(double, denseVector)) from java implementation to NativeBLAS when vector size>256
### Why are the changes needed?
In current ML BLAS.scala, all level-1 routines are fixed to use java
implementation. But NativeBLAS(intel MKL, OpenBLAS) can bring up to 11X
performance improvement based on performance test which apply direct
calls against these methods. We should provide a way to allow user take
advantage of NativeBLAS for level-1 routines. Here we do it through
switching to NativeBLAS for these methods from f2jBLAS.
### Does this PR introduce any user-facing change?
Yes, methods axpy, dot, scal in level-1 routines will switch to NativeBLAS when it has more than nativeL1Threshold(fixed value 256) elements and will fallback to f2jBLAS if native BLAS is not properly configured in system.
### How was this patch tested?
Perf test direct calls level-1 routines
Closes#27546 from yma11/SPARK-30773.
Lead-authored-by: yan ma <yan.ma@intel.com>
Co-authored-by: Ma Yan <yan.ma@intel.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
Fix errors and missing parts for datetime pattern document
1. The pattern we use is similar to DateTimeFormatter and SimpleDateFormat but not identical. So we shouldn't use any of them in the API docs but use a link to the doc of our own.
2. Some pattern letters are missing
3. Some pattern letters are explicitly banned - Set('A', 'c', 'e', 'n', 'N')
4. the second fraction pattern different logic for parsing and formatting
### Why are the changes needed?
fix and improve doc
### Does this PR introduce any user-facing change?
yes, new and updated doc
### How was this patch tested?
pass Jenkins
viewed locally with `jekyll serve`
Closes#27956 from yaooqinn/SPARK-31189.
Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
A followup of https://github.com/apache/spark/pull/27936 to update document.
### Why are the changes needed?
correct document
### Does this PR introduce any user-facing change?
no
### How was this patch tested?
N/A
Closes#27950 from cloud-fan/null.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Takeshi Yamamuro <yamamuro@apache.org>
### What changes were proposed in this pull request?
The meaning of 'u' was day number of the week in SimpleDateFormat, it was changed to year in DateTimeFormatter. Now we keep the old meaning of 'u' by substituting 'u' to 'e' internally and use DateTimeFormatter to parse the pattern string. In DateTimeFormatter, the 'e' and 'c' also represents day-of-week. e.g.
```sql
select date_format(timestamp '2019-10-06', 'yyyy-MM-dd uuuu');
select date_format(timestamp '2019-10-06', 'yyyy-MM-dd uuee');
select date_format(timestamp '2019-10-06', 'yyyy-MM-dd eeee');
```
Because of the substitution, they all goes to `.... eeee` silently. The users may congitive problems of their meanings, so we should mark them as illegal pattern characters to stay the same as before.
This pr move the method `convertIncompatiblePattern` from `DatetimeUtils` to `DateTimeFormatterHelper` object, since it is quite specific for `DateTimeFormatterHelper` class.
And 'e' and 'c' char checking in this method.
Besides,`convertIncompatiblePattern` has a bug that will lose the last `'` if it ends with it, this pr fixes this too. e.g.
```sql
spark-sql> select date_format(timestamp "2019-10-06", "yyyy-MM-dd'S'");
20/03/18 11:19:45 ERROR SparkSQLDriver: Failed in [select date_format(timestamp "2019-10-06", "yyyy-MM-dd'S'")]
java.lang.IllegalArgumentException: Pattern ends with an incomplete string literal: uuuu-MM-dd'S
spark-sql> select to_timestamp("2019-10-06S", "yyyy-MM-dd'S'");
NULL
```
### Why are the changes needed?
avoid vagueness
bug fix
### Does this PR introduce any user-facing change?
no, these are not exposed yet
### How was this patch tested?
add ut
Closes#27939 from yaooqinn/SPARK-31176.
Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This PR will add the user guide for AQE and the detailed configurations about the three mainly features in AQE.
### Why are the changes needed?
Add the detailed configurations.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
only add doc no need ut.
Closes#27616 from JkSelf/aqeuserguide.
Authored-by: jiake <ke.a.jia@intel.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
The current migration guide of SQL is too long for most readers to find the needed info. This PR is to group the items in the migration guide of Spark SQL based on the corresponding components.
Note. This PR does not change the contents of the migration guides. Attached figure is the screenshot after the change.
### Why are the changes needed?
The current migration guide of SQL is too long for most readers to find the needed info.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
N/A
Closes#27909 from gatorsmile/migrationGuideReorg.
Authored-by: gatorsmile <gatorsmile@gmail.com>
Signed-off-by: Takeshi Yamamuro <yamamuro@apache.org>
### What changes were proposed in this pull request?
Since we reverted the original change in https://github.com/apache/spark/pull/27540, this PR is to remove the corresponding migration guide made in the commit https://github.com/apache/spark/pull/24948
### Why are the changes needed?
N/A
### Does this PR introduce any user-facing change?
N/A
### How was this patch tested?
N/A
Closes#27896 from gatorsmile/SPARK-28093Followup.
Authored-by: gatorsmile <gatorsmile@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
When loading DataFrames from JDBC datasource with Kerberos authentication, remote executors (yarn-client/cluster etc. modes) fail to establish a connection due to lack of Kerberos ticket or ability to generate it.
This is a real issue when trying to ingest data from kerberized data sources (SQL Server, Oracle) in enterprise environment where exposing simple authentication access is not an option due to IT policy issues.
In this PR I've added Postgres support (other supported databases will come in later PRs).
What this PR contains:
* Added `keytab` and `principal` JDBC options
* Added `ConnectionProvider` trait and it's impementations:
* `BasicConnectionProvider` => unsecure connection
* `PostgresConnectionProvider` => postgres secure connection
* Added `ConnectionProvider` tests
* Added `PostgresKrbIntegrationSuite` docker integration test
* Created `SecurityUtils` to concentrate re-usable security related functionalities
* Documentation
### Why are the changes needed?
Missing JDBC kerberos support.
### Does this PR introduce any user-facing change?
Yes, 2 additional JDBC options added:
* keytab
* principal
If both provided then Spark does kerberos authentication.
### How was this patch tested?
To demonstrate the functionality with a standalone application I've created this repository: https://github.com/gaborgsomogyi/docker-kerberos
* Additional + existing unit tests
* Additional docker integration test
* Test on cluster manually
* `SKIP_API=1 jekyll build`
Closes#27637 from gaborgsomogyi/SPARK-30874.
Authored-by: Gabor Somogyi <gabor.g.somogyi@gmail.com>
Signed-off-by: Marcelo Vanzin <vanzin@apache.org>
### What changes were proposed in this pull request?
spark.sql.legacy.timeParser.enabled should be removed from SQLConf and the migration guide
spark.sql.legacy.timeParsePolicy is the right one
### Why are the changes needed?
fix doc
### Does this PR introduce any user-facing change?
no
### How was this patch tested?
Pass the jenkins
Closes#27889 from yaooqinn/SPARK-31131.
Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
1.Add version information to the configuration of `Status`.
2.Update the docs of `Status`.
3.By the way supplementary documentation about https://github.com/apache/spark/pull/27847
I sorted out some information show below.
Item name | Since version | JIRA ID | Commit ID | Note
-- | -- | -- | -- | --
spark.appStateStore.asyncTracking.enable | 2.3.0 | SPARK-20653 | 772e4648d95bda3353723337723543c741ea8476#diff-9ab674b7af7b2097f7d28cb6f5fd1e8c |
spark.ui.liveUpdate.period | 2.3.0 | SPARK-20644 | c7f38e5adb88d43ef60662c5d6ff4e7a95bff580#diff-9ab674b7af7b2097f7d28cb6f5fd1e8c |
spark.ui.liveUpdate.minFlushPeriod | 2.4.2 | SPARK-27394 | a8a2ba11ac10051423e58920062b50f328b06421#diff-9ab674b7af7b2097f7d28cb6f5fd1e8c |
spark.ui.retainedJobs | 1.2.0 | SPARK-2321 | 9530316887612dca060a128fca34dd5a6ab2a9a9#diff-1f32bcb61f51133bd0959a4177a066a5 |
spark.ui.retainedStages | 0.9.0 | None | 112c0a1776bbc866a1026a9579c6f72f293414c4#diff-1f32bcb61f51133bd0959a4177a066a5 | 0.9.0-incubating-SNAPSHOT
spark.ui.retainedTasks | 2.0.1 | SPARK-15083 | 55db26245d69bb02b7d7d5f25029b1a1cd571644#diff-6bdad48cfc34314e89599655442ff210 |
spark.ui.retainedDeadExecutors | 2.0.0 | SPARK-7729 | 9f4263392e492b5bc0acecec2712438ff9a257b7#diff-a0ba36f9b1f9829bf3c4689b05ab6cf2 |
spark.ui.dagGraph.retainedRootRDDs | 2.1.0 | SPARK-17171 | cc87280fcd065b01667ca7a59a1a32c7ab757355#diff-3f492c527ea26679d4307041b28455b8 |
spark.metrics.appStatusSource.enabled | 3.0.0 | SPARK-30060 | 60f20e5ea2000ab8f4a593b5e4217fd5637c5e22#diff-9f796ae06b0272c1f0a012652a5b68d0 |
### Why are the changes needed?
Supplemental configuration version information.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
Exists UT
Closes#27848 from beliefer/add-version-to-status-config.
Lead-authored-by: beliefer <beliefer@163.com>
Co-authored-by: Jiaan Geng <beliefer@163.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
A few improvements to the sql ref SELECT doc:
1. correct the syntax of SELECT query
2. correct the default of null sort order
3. correct the GROUP BY syntax
4. several minor fixes
### Why are the changes needed?
refine document
### Does this PR introduce any user-facing change?
N/A
### How was this patch tested?
N/A
Closes#27866 from cloud-fan/doc.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR reverts https://github.com/apache/spark/pull/26051 and https://github.com/apache/spark/pull/26066
### Why are the changes needed?
There is no standard requiring that `size(null)` must return null, and returning -1 looks reasonable as well. This is kind of a cosmetic change and we should avoid it if it breaks existing queries. This is similar to reverting TRIM function parameter order change.
### Does this PR introduce any user-facing change?
Yes, change the behavior of `size(null)` back to be the same as 2.4.
### How was this patch tested?
N/A
Closes#27834 from cloud-fan/revert.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
In Spark version 2.4 and earlier, datetime parsing, formatting and conversion are performed by using the hybrid calendar (Julian + Gregorian).
Since the Proleptic Gregorian calendar is de-facto calendar worldwide, as well as the chosen one in ANSI SQL standard, Spark 3.0 switches to it by using Java 8 API classes (the java.time packages that are based on ISO chronology ). The switching job is completed in SPARK-26651.
But after the switching, there are some patterns not compatible between Java 8 and Java 7, Spark needs its own definition on the patterns rather than depends on Java API.
In this PR, we achieve this by writing the document and shadow the incompatible letters. See more details in [SPARK-31030](https://issues.apache.org/jira/browse/SPARK-31030)
### Why are the changes needed?
For backward compatibility.
### Does this PR introduce any user-facing change?
No.
After we define our own datetime parsing and formatting patterns, it's same to old Spark version.
### How was this patch tested?
Existing and new added UT.
Locally document test:
Closes#27830 from xuanyuanking/SPARK-31030.
Authored-by: Yuanjian Li <xyliyuanjian@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This PR makes the following refinements to the workflow for building docs:
* Install Python and Ruby consistently using pyenv and rbenv across both the docs README and the release Dockerfile.
* Pin the Python and Ruby versions we use.
* Pin all direct Python and Ruby dependency versions.
* Eliminate any use of `sudo pip`, which the Python community discourages, or `sudo gem`.
### Why are the changes needed?
This PR should increase the consistency and reproducibility of the doc-building process by managing Python and Ruby in a more consistent way, and by eliminating unused or outdated code.
Here's a possible example of an issue building the docs that would be addressed by the changes in this PR: https://github.com/apache/spark/pull/27459#discussion_r376135719
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
Manual tests:
* I was able to build the Docker image successfully, minus the final part about `RUN useradd`.
* I am unable to run `do-release-docker.sh` because I am not a committer and don't have the required GPG key.
* I built the docs locally and viewed them in the browser.
I think I need a committer to more fully test out these changes.
Closes#27534 from nchammas/SPARK-30731-building-docs.
Authored-by: Nicholas Chammas <nicholas.chammas@liveramp.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
Updating ML docs for 3.0 changes
### Why are the changes needed?
I am auditing 3.0 ML changes, found some docs are missing or not updated. Need to update these.
### Does this PR introduce any user-facing change?
Yes, doc changes
### How was this patch tested?
Manually build and check
Closes#27762 from huaxingao/spark-doc.
Authored-by: Huaxin Gao <huaxing@us.ibm.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
This pr intends to support 32 or more grouping attributes for GROUPING_ID. In the current master, an integer overflow can occur to compute grouping IDs;
e75d9afb2f/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala (L613)
For example, the query below generates wrong grouping IDs in the master;
```
scala> val numCols = 32 // or, 31
scala> val cols = (0 until numCols).map { i => s"c$i" }
scala> sql(s"create table test_$numCols (${cols.map(c => s"$c int").mkString(",")}, v int) using parquet")
scala> val insertVals = (0 until numCols).map { _ => 1 }.mkString(",")
scala> sql(s"insert into test_$numCols values ($insertVals,3)")
scala> sql(s"select grouping_id(), sum(v) from test_$numCols group by grouping sets ((${cols.mkString(",")}), (${cols.init.mkString(",")}))").show(10, false)
scala> sql(s"drop table test_$numCols")
// numCols = 32
+-------------+------+
|grouping_id()|sum(v)|
+-------------+------+
|0 |3 |
|0 |3 | // Wrong Grouping ID
+-------------+------+
// numCols = 31
+-------------+------+
|grouping_id()|sum(v)|
+-------------+------+
|0 |3 |
|1 |3 |
+-------------+------+
```
To fix this issue, this pr change code to use long values for `GROUPING_ID` instead of int values.
### Why are the changes needed?
To support more cases in `GROUPING_ID`.
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
Added unit tests.
Closes#26918 from maropu/FixGroupingIdIssue.
Authored-by: Takeshi Yamamuro <yamamuro@apache.org>
Signed-off-by: Takeshi Yamamuro <yamamuro@apache.org>
### What changes were proposed in this pull request?
This PR intends to fix typos and phrases in the `/docs` directory. To find them, I run the Intellij typo checker.
### Why are the changes needed?
For better documents.
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
N/A
Closes#27819 from maropu/TypoFix-20200306.
Authored-by: Takeshi Yamamuro <yamamuro@apache.org>
Signed-off-by: Gengliang Wang <gengliang.wang@databricks.com>
### What changes were proposed in this pull request?
rename the config and make it non-internal.
### Why are the changes needed?
Now we fail the query if duplicated map keys are detected, and provide a legacy config to deduplicate it. However, we must provide a way to get users out of this situation, instead of just rejecting to run the query. This exit strategy should always be there, while legacy config indicates that it may be removed someday.
### Does this PR introduce any user-facing change?
no, just rename a config which was added in 3.0
### How was this patch tested?
add more tests for the fail behavior.
Closes#27772 from cloud-fan/map.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
-c is short for --conf, it was introduced since v1.1.0 but hidden from users until now
### Why are the changes needed?
### Does this PR introduce any user-facing change?
no
expose hidden feature
### How was this patch tested?
Nah
Closes#27802 from yaooqinn/conf.
Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Fix the migration guide document for `spark.sql.legacy.ctePrecedence.enabled`, which is introduced in #27579.
### Why are the changes needed?
The config value changed.
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
Document only.
Closes#27782 from xuanyuanking/SPARK-30829-follow.
Authored-by: Yuanjian Li <xyliyuanjian@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
ForEachBatch Java example was incorrect
### Why are the changes needed?
Example did not compile
### Does this PR introduce any user-facing change?
Yes, to docs.
### How was this patch tested?
In IDE.
Closes#27740 from roland1982/foreachwriter_java_example_fix.
Authored-by: roland-ondeviceresearch <roland@ondeviceresearch.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
Remove automatically resource coordination support from Standalone.
### Why are the changes needed?
Resource coordination is mainly designed for the scenario where multiple workers launched on the same host. However, it's, actually, a non-existed scenario for today's Spark. Because, Spark now can start multiple executors in a single Worker, while it only allow one executor per Worker at very beginning. So, now, it really help nothing for user to launch multiple workers on the same host. Thus, it's not worth for us to bring over complicated implementation and potential high maintain cost for such an impossible scenario.
### Does this PR introduce any user-facing change?
No, it's Spark 3.0 feature.
### How was this patch tested?
Pass Jenkins.
Closes#27722 from Ngone51/abandon_coordination.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Xingbo Jiang <xingbo.jiang@databricks.com>
### What changes were proposed in this pull request?
1.Add version information to the configuration of `Kryo`.
2.Update the docs of `Kryo`.
I sorted out some information show below.
Item name | Since version | JIRA ID | Commit ID | Note
-- | -- | -- | -- | --
spark.kryo.registrationRequired | 1.1.0 | SPARK-2102 | efdaeb111917dd0314f1d00ee8524bed1e2e21ca#diff-1f81c62dad0e2dfc387a974bb08c497c |
spark.kryo.registrator | 0.5.0 | None | 91c07a33d90ab0357e8713507134ecef5c14e28a#diff-792ed56b3398163fa14e8578549d0d98 | This is not a release version, do we need to record it?
spark.kryo.classesToRegister | 1.2.0 | SPARK-1813 | 6bb56faea8d238ea22c2de33db93b1b39f492b3a#diff-529fc5c06b9731c1fbda6f3db60b16aa |
spark.kryo.unsafe | 2.1.0 | SPARK-928 | bc167a2a53f5a795d089e8a884569b1b3e2cd439#diff-1f81c62dad0e2dfc387a974bb08c497c |
spark.kryo.pool | 3.0.0 | SPARK-26466 | 38f030725c561979ca98b2a6cc7ca6c02a1f80ed#diff-a3c6b992784f9abeb9f3047d3dcf3ed9 |
spark.kryo.referenceTracking | 0.8.0 | None | 0a8cc309211c62f8824d76618705c817edcf2424#diff-1f81c62dad0e2dfc387a974bb08c497c |
spark.kryoserializer.buffer | 1.4.0 | SPARK-5932 | 2d222fb39dd978e5a33cde6ceb59307cbdf7b171#diff-1f81c62dad0e2dfc387a974bb08c497c |
spark.kryoserializer.buffer.max | 1.4.0 | SPARK-5932 | 2d222fb39dd978e5a33cde6ceb59307cbdf7b171#diff-1f81c62dad0e2dfc387a974bb08c497c |
### Why are the changes needed?
Supplemental configuration version information.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
Exists UT
Closes#27734 from beliefer/add-version-to-kryo-config.
Authored-by: beliefer <beliefer@163.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Rename `spark.sql.legacy.addDirectory.recursive.enabled` to `spark.sql.legacy.addSingleFileInAddFile`
### Why are the changes needed?
To follow the naming convention
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
Existing UTs.
Closes#27725 from iRakson/SPARK-30234_CONFIG.
Authored-by: iRakson <raksonrakesh@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Renamed configuration from `spark.sql.legacy.useHashOnMapType` to `spark.sql.legacy.allowHashOnMapType`.
### Why are the changes needed?
Better readability of configuration.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
Existing UTs.
Closes#27719 from iRakson/SPARK-27619_FOLLOWUP.
Authored-by: iRakson <raksonrakesh@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This PR groups all hive upgrade related migration guides inside Spark 3.0 together.
Also add another behavior change of `ScriptTransform` in the new Hive section.
### Why are the changes needed?
Make the doc more clearly to user.
### Does this PR introduce any user-facing change?
No, new doc for Spark 3.0.
### How was this patch tested?
N/A.
Closes#27670 from Ngone51/hive_migration.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
1.Add version information to the configuration of `Python`.
2.Update the docs of `Python`.
I sorted out some information show below.
Item name | Since version | JIRA ID | Commit ID | Note
-- | -- | -- | -- | --
spark.python.worker.reuse | 1.2.0 | SPARK-3030 | 2aea0da84c58a179917311290083456dfa043db7#diff-0a67bc4d171abe4df8eb305b0f4123a2 |
spark.python.task.killTimeout | 2.2.2 | SPARK-22535 | be68f86e11d64209d9e325ce807025318f383bea#diff-0a67bc4d171abe4df8eb305b0f4123a2 |
spark.python.use.daemon | 2.3.0 | SPARK-22554 | 57c5514de9dba1c14e296f85fb13fef23ce8c73f#diff-9008ad45db34a7eee2e265a50626841b |
spark.python.daemon.module | 2.4.0 | SPARK-22959 | afae8f2bc82597593595af68d1aa2d802210ea8b#diff-9008ad45db34a7eee2e265a50626841b |
spark.python.worker.module | 2.4.0 | SPARK-22959 | afae8f2bc82597593595af68d1aa2d802210ea8b#diff-9008ad45db34a7eee2e265a50626841b |
spark.executor.pyspark.memory | 2.4.0 | SPARK-25004 | 7ad18ee9f26e75dbe038c6034700f9cd4c0e2baa#diff-6bdad48cfc34314e89599655442ff210 |
### Why are the changes needed?
Supplemental configuration version information.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
Exists UT
Closes#27704 from beliefer/add-version-to-python-config.
Authored-by: beliefer <beliefer@163.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
1.Add version information to the configuration of `R`.
2.Update the docs of `R`.
I sorted out some information show below.
Item name | Since version | JIRA ID | Commit ID | Note
-- | -- | -- | -- | --
spark.r.backendConnectionTimeout | 2.1.0 | SPARK-17919 | 2881a2d1d1a650a91df2c6a01275eba14a43b42a#diff-025470e1b7094d7cf4a78ea353fb3981 |
spark.r.numRBackendThreads | 1.4.0 | SPARK-8282 | 28e8a6ea65fd08ab9cefc4d179d5c66ffefd3eb4#diff-697f7f2fc89808e0113efc71ed235db2 |
spark.r.heartBeatInterval | 2.1.0 | SPARK-17919 | 2881a2d1d1a650a91df2c6a01275eba14a43b42a#diff-fe903bf14db371aa320b7cc516f2463c |
spark.sparkr.r.command | 1.5.3 | SPARK-10971 | 9695f452e86a88bef3bcbd1f3c0b00ad9e9ac6e1#diff-025470e1b7094d7cf4a78ea353fb3981 |
spark.r.command | 1.5.3 | SPARK-10971 | 9695f452e86a88bef3bcbd1f3c0b00ad9e9ac6e1#diff-025470e1b7094d7cf4a78ea353fb3981 |
### Why are the changes needed?
Supplemental configuration version information.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
Exists UT
Closes#27708 from beliefer/add-version-to-R-config.
Authored-by: beliefer <beliefer@163.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
`hash()` and `xxhash64()` cannot be used on elements of `Maptype`. A new configuration `spark.sql.legacy.useHashOnMapType` is introduced to allow users to restore the previous behaviour.
When `spark.sql.legacy.useHashOnMapType` is set to false:
```
scala> spark.sql("select hash(map())");
org.apache.spark.sql.AnalysisException: cannot resolve 'hash(map())' due to data type mismatch: input to function hash cannot contain elements of MapType; line 1 pos 7;
'Project [unresolvedalias(hash(map(), 42), None)]
+- OneRowRelation
```
when `spark.sql.legacy.useHashOnMapType` is set to true :
```
scala> spark.sql("set spark.sql.legacy.useHashOnMapType=true");
res3: org.apache.spark.sql.DataFrame = [key: string, value: string]
scala> spark.sql("select hash(map())").first()
res4: org.apache.spark.sql.Row = [42]
```
### Why are the changes needed?
As discussed in Jira, SparkSql's map hashcodes depends on their order of insertion which is not consistent with the normal scala behaviour which might confuse users.
Code snippet from JIRA :
```
val a = spark.createDataset(Map(1->1, 2->2) :: Nil)
val b = spark.createDataset(Map(2->2, 1->1) :: Nil)
// Demonstration of how Scala Map equality is unaffected by insertion order:
assert(Map(1->1, 2->2).hashCode() == Map(2->2, 1->1).hashCode())
assert(Map(1->1, 2->2) == Map(2->2, 1->1))
assert(a.first() == b.first())
// In contrast, this will print two different hashcodes:
println(Seq(a, b).map(_.selectExpr("hash(*)").first()))
```
Also `MapType` is prohibited for aggregation / joins / equality comparisons #7819 and set operations #17236.
### Does this PR introduce any user-facing change?
Yes. Now users cannot use hash functions on elements of `mapType`. To restore the previous behaviour set `spark.sql.legacy.useHashOnMapType` to true.
### How was this patch tested?
UT added.
Closes#27580 from iRakson/SPARK-27619.
Authored-by: iRakson <raksonrakesh@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
Huaxin Gao
Kent Yao
Takeshi Yamamuro
Yuming Wang
gatorsmile
Dongjoon Hyun
yi.wu
zero323
HyukjinKwon
Gengliang Wang
beliefer
Eric Wu
Thomas Graves
Kousuke Saruta
Luca Canali
Kengo Seki
Wenchen Fan
yan ma
jiake
Gabor Somogyi
Yuanjian Li
Qianyang Yu
Nicholas Chammas
roland-ondeviceresearch
iRakson
