### What changes were proposed in this pull request?
Add `table_identifier` in sql-migration-guide for SHOW CREATE TABLE.
### Why are the changes needed?
To make document more readable.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing test suites.
Closes#31608 from Karl-WangSK/sqldoc.
Lead-authored-by: Karl-WangSK <shikai.wang@linkflowtech.com>
Co-authored-by: ShiKai Wang <wskqing@gmail.com>
Signed-off-by: Yuming Wang <yumwang@ebay.com>
### What changes were proposed in this pull request?
Update public docs of SQL commands about altering cached tables/views. For instance:
<img width="869" alt="Screenshot 2021-02-08 at 15 11 48" src="https://user-images.githubusercontent.com/1580697/107217940-fd3b8980-6a1f-11eb-98b9-9b2e3fe7f4ef.png">
### Why are the changes needed?
To inform users about commands behavior in altering cached tables or views.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By running the command below and manually checking the docs:
```
$ SKIP_API=1 SKIP_SCALADOC=1 SKIP_PYTHONDOC=1 SKIP_RDOC=1 jekyll serve --watch
```
Closes#31524 from MaxGekk/doc-cmd-caching.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This PR fix an issue that `java.sql.RowId` is mapped to `LongType` and prefer `StringType`.
In the current implementation, JDBC RowID type is mapped to `LongType` except for `OracleDialect`, but there is no guarantee to be able to convert RowID to long.
`java.sql.RowId` declares `toString` and the specification of `java.sql.RowId` says
> _all methods on the RowId interface must be fully implemented if the JDBC driver supports the data type_
(https://docs.oracle.com/javase/8/docs/api/java/sql/RowId.html)
So, we should prefer StringType to LongType.
### Why are the changes needed?
This seems to be a potential bug.
### Does this PR introduce _any_ user-facing change?
Yes. RowID is mapped to StringType rather than LongType.
### How was this patch tested?
New test and the existing test case `SPARK-32992: map Oracle's ROWID type to StringType` in `OracleIntegrationSuite` passes.
Closes#31491 from sarutak/rowid-type.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Kousuke Saruta <sarutak@oss.nttdata.com>
### What changes were proposed in this pull request?
This change is to document the newly added streaming table APIs in Structured Streaming Programming Guide.
### Why are the changes needed?
This will help our users when they try to use the new APIs.
### Does this PR introduce _any_ user-facing change?
Yes. Users will see the changes in the programming guide.
### How was this patch tested?
Built the HTML page and verified.
Attached is a screenshot of the section added:
Closes#31590 from bozhang2820/table-api-doc.
Lead-authored-by: Bo Zhang <bo.zhang@databricks.com>
Co-authored-by: Bo Zhang <bozhang2820@gmail.com>
Signed-off-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com>
### What changes were proposed in this pull request?
Explicitly highlight that the table rename command cannot move a table between databases.
### Why are the changes needed?
To inform users about actual behavior of the table rename command.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
```sql
spark-sql> CREATE DATABASE db1;
spark-sql> CREATE DATABASE db2;
spark-sql> CREATE TABLE db1.tbl1 (c0 INT);
spark-sql> ALTER TABLE db1.tbl1 RENAME TO db2.tbl1;
Error in query: RENAME TABLE source and destination databases do not match: 'db1' != 'db2';
spark-sql> ALTER TABLE db1.tbl1 RENAME TO db1.tbl2;
spark-sql> SHOW TABLES IN db1 LIKE '*';
db1 tbl2 false
```
Closes#31586 from MaxGekk/doc-rename-table.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
BasicWriteStatsTracker to probe for a custom Xattr if the size of
the generated file is 0 bytes; if found and parseable use that as
the declared length of the output.
The matching Hadoop patch in HADOOP-17414:
* Returns all S3 object headers as XAttr attributes prefixed "header."
* Sets the custom header x-hadoop-s3a-magic-data-length to the length of
the data in the marker file.
As a result, spark job tracking will correctly report the amount of data uploaded
and yet to materialize.
### Why are the changes needed?
Now that S3 is consistent, it's a lot easier to use the S3A "magic" committer
which redirects a file written to `dest/__magic/job_0011/task_1245/__base/year=2020/output.avro`
to its final destination `dest/year=2020/output.avro` , adding a zero byte marker file at
the end and a json file `dest/__magic/job_0011/task_1245/__base/year=2020/output.avro.pending`
containing all the information for the job committer to complete the upload.
But: the write tracker statictics don't show progress as they measure the length of the
created file, find the marker file and report 0 bytes.
By probing for a specific HTTP header in the marker file and parsing that if
retrieved, the real progress can be reported.
There's a matching change in Hadoop [https://github.com/apache/hadoop/pull/2530](https://github.com/apache/hadoop/pull/2530)
which adds getXAttr API support to the S3A connector and returns the headers; the magic
committer adds the relevant attributes.
If the FS being probed doesn't support the XAttr API, the header is missing
or the value not a positive long then the size of 0 is returned.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
New tests in BasicWriteTaskStatsTrackerSuite which use a filter FS to
implement getXAttr on top of LocalFS; this is used to explore the set of
options:
* no XAttr API implementation (existing tests; what callers would see with
most filesystems)
* no attribute found (HDFS, ABFS without the attribute)
* invalid data of different forms
All of these return Some(0) as file length.
The Hadoop PR verifies XAttr implementation in S3A and that
the commit protocol attaches the header to the files.
External downstream testing has done the full hadoop+spark end
to end operation, with manual review of logs to verify that the
data was successfully collected from the attribute.
Closes#30714 from steveloughran/cdpd/SPARK-33739-magic-commit-tracking-master.
Authored-by: Steve Loughran <stevel@cloudera.com>
Signed-off-by: Thomas Graves <tgraves@apache.org>
### What changes were proposed in this pull request?
In the PR, I propose to update the Spark SQL guide about the SQL configs that are related to datetime rebasing:
- spark.sql.parquet.int96RebaseModeInWrite
- spark.sql.parquet.datetimeRebaseModeInWrite
- spark.sql.parquet.int96RebaseModeInRead
- spark.sql.parquet.datetimeRebaseModeInRead
- spark.sql.avro.datetimeRebaseModeInWrite
- spark.sql.avro.datetimeRebaseModeInRead
Parquet options added by #31489:
- datetimeRebaseMode
- int96RebaseMode
and Avro options added by #31529:
- datetimeRebaseMode
<img width="998" alt="Screenshot 2021-02-17 at 21 42 09" src="https://user-images.githubusercontent.com/1580697/108252043-3afb8900-7169-11eb-8568-511e21fa7f78.png">
### Why are the changes needed?
To inform users about supported DS options and SQL configs.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By generating the doc and manually checking:
```
$ SKIP_API=1 SKIP_SCALADOC=1 SKIP_PYTHONDOC=1 SKIP_RDOC=1 jekyll serve --watch
```
Closes#31564 from MaxGekk/doc-rebase-options.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
1. Put the SQL config `spark.sql.legacy.replaceDatabricksSparkAvro.enabled` to the list of deprecated configs `deprecatedSQLConfigs`
2. Update docs for the Avro datasource
<img width="982" alt="Screenshot 2021-02-17 at 21 04 26" src="https://user-images.githubusercontent.com/1580697/108249890-abed7180-7166-11eb-8cb7-0c246d2a34fc.png">
### Why are the changes needed?
The config exists for enough time. We can deprecate it, and recommend users to use `.format("avro")` instead.
### Does this PR introduce _any_ user-facing change?
Should not except of the warning with the recommendation to use the `avro` format.
### How was this patch tested?
1. By generating docs via:
```
$ SKIP_API=1 SKIP_SCALADOC=1 SKIP_PYTHONDOC=1 SKIP_RDOC=1 jekyll serve --watch
```
2. Manually checking the warning:
```
scala> spark.conf.set("spark.sql.legacy.replaceDatabricksSparkAvro.enabled", false)
21/02/17 21:20:18 WARN SQLConf: The SQL config 'spark.sql.legacy.replaceDatabricksSparkAvro.enabled' has been deprecated in Spark v3.2 and may be removed in the future. Use `.format("avro")` in `DataFrameWriter` or `DataFrameReader` instead.
```
Closes#31578 from MaxGekk/deprecate-replaceDatabricksSparkAvro.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Improving the documentation and release process by pinning Jekyll version by Gemfile and Bundler.
Some files and their responsibilities within this PR:
- `docs/.bundle/config` is used to specify a directory "docs/.local_ruby_bundle" which will be used as destination to install the ruby packages into instead of the global one which requires root access
- `docs/Gemfile` is specifying the required Jekyll version and other top level gem versions
- `docs/Gemfile.lock` is generated by the "bundle install". This file contains the exact resolved versions of all the gems including the top level gems and all the direct and transitive dependencies of those gems. When this file is generated it contains a platform related section "PLATFORMS" (in my case after the generation it was "universal-darwin-19"). Still this file must be under version control as when the version of a gem does not fit to the one specified in `Gemfile` an error comes (i.e. if the `Gemfile.lock` was generated for Jekyll 4.1.0 and its version is updated in the `Gemfile` to 4.2.0 then it triggers the error: "The bundle currently has jekyll locked at 4.1.0."). This is solution is also suggested officially in [its documentation](https://bundler.io/rationale.html#checking-your-code-into-version-control). To get rid of the specific platform (like "universal-darwin-19") first we have to add "ruby" as platform [which means this should work on every platform where Ruby runs](https://guides.rubygems.org/what-is-a-gem/)) by running "bundle lock --add-platform ruby" then the specific platform can be removed by "bundle lock --remove-platform universal-darwin-19".
After this the correct process to update Jekyll version is the following:
1. update the version in `Gemfile`
2. run "bundle update" which updates the `Gemfile.lock`
3. commit both files
This process for version update is tested for details please check the testing section.
### Why are the changes needed?
Using different Jekyll versions can generate different output documents.
This PR standardize the process.
### Does this PR introduce _any_ user-facing change?
No, assuming the release was done via docker by using `do-release-docker.sh`.
In that case there should be no difference at all as the same Jekyll version is specified in the Gemfile.
### How was this patch tested?
#### Testing document generation
Doc generation step was triggered via the docker release:
```
$ ./do-release-docker.sh -d ~/working -n -s docs
...
========================
= Building documentation...
Command: /opt/spark-rm/release-build.sh docs
Log file: docs.log
Skipping publish step.
```
The docs.log contains the followings:
```
Building Spark docs
Fetching gem metadata from https://rubygems.org/.........
Using bundler 2.2.9
Fetching rb-fsevent 0.10.4
Fetching forwardable-extended 2.6.0
Fetching public_suffix 4.0.6
Fetching colorator 1.1.0
Fetching eventmachine 1.2.7
Fetching http_parser.rb 0.6.0
Fetching ffi 1.14.2
Fetching concurrent-ruby 1.1.8
Installing colorator 1.1.0
Installing forwardable-extended 2.6.0
Installing rb-fsevent 0.10.4
Installing public_suffix 4.0.6
Installing http_parser.rb 0.6.0 with native extensions
Installing eventmachine 1.2.7 with native extensions
Installing concurrent-ruby 1.1.8
Fetching rexml 3.2.4
Fetching liquid 4.0.3
Installing ffi 1.14.2 with native extensions
Installing rexml 3.2.4
Installing liquid 4.0.3
Fetching mercenary 0.4.0
Installing mercenary 0.4.0
Fetching rouge 3.26.0
Installing rouge 3.26.0
Fetching safe_yaml 1.0.5
Installing safe_yaml 1.0.5
Fetching unicode-display_width 1.7.0
Installing unicode-display_width 1.7.0
Fetching webrick 1.7.0
Installing webrick 1.7.0
Fetching pathutil 0.16.2
Fetching kramdown 2.3.0
Fetching terminal-table 2.0.0
Fetching addressable 2.7.0
Fetching i18n 1.8.9
Installing terminal-table 2.0.0
Installing pathutil 0.16.2
Installing i18n 1.8.9
Installing addressable 2.7.0
Installing kramdown 2.3.0
Fetching kramdown-parser-gfm 1.1.0
Installing kramdown-parser-gfm 1.1.0
Fetching rb-inotify 0.10.1
Fetching sassc 2.4.0
Fetching em-websocket 0.5.2
Installing rb-inotify 0.10.1
Installing em-websocket 0.5.2
Installing sassc 2.4.0 with native extensions
Fetching listen 3.4.1
Installing listen 3.4.1
Fetching jekyll-watch 2.2.1
Installing jekyll-watch 2.2.1
Fetching jekyll-sass-converter 2.1.0
Installing jekyll-sass-converter 2.1.0
Fetching jekyll 4.2.0
Installing jekyll 4.2.0
Fetching jekyll-redirect-from 0.16.0
Installing jekyll-redirect-from 0.16.0
Bundle complete! 4 Gemfile dependencies, 30 gems now installed.
Bundled gems are installed into `./.local_ruby_bundle`
```
#### Testing Jekyll (or other gem) update
First locally I reverted Jekyll to 4.1.0:
```
$ rm Gemfile.lock
$ rm -rf .local_ruby_bundle
# edited Gemfile to use version 4.1.0
$ cat Gemfile
source "https://rubygems.org"
gem "jekyll", "4.1.0"
gem "rouge", "3.26.0"
gem "jekyll-redirect-from", "0.16.0"
gem "webrick", "1.7"
$ bundle install
...
```
Testing Jekyll version before the update:
```
$ bundle exec jekyll --version
jekyll 4.1.0
```
Imitating Jekyll update coming from git by reverting my local changes:
```
$ git checkout Gemfile
Updated 1 path from the index
$ cat Gemfile
source "https://rubygems.org"
gem "jekyll", "4.2.0"
gem "rouge", "3.26.0"
gem "jekyll-redirect-from", "0.16.0"
gem "webrick", "1.7"
$ git checkout Gemfile.lock
Updated 1 path from the index
```
Run the install:
```
$ bundle install
...
```
Checking the updated Jekyll version:
```
$ bundle exec jekyll --version
jekyll 4.2.0
```
Closes#31559 from attilapiros/pin-jekyll-version.
Lead-authored-by: “attilapiros” <piros.attila.zsolt@gmail.com>
Co-authored-by: Hyukjin Kwon <gurwls223@gmail.com>
Co-authored-by: Attila Zsolt Piros <2017933+attilapiros@users.noreply.github.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Per discussion in https://issues.apache.org/jira/browse/SPARK-32883?focusedCommentId=17285057&page=com.atlassian.jira.plugin.system.issuetabpanels%3Acomment-tabpanel#comment-17285057, we should add documentation for added new features of full outer and left semi joins into SS programming guide.
* Reworded the section for "Outer Joins with Watermarking", to make it work for full outer join. Updated the code snippet to show up full outer and left semi join.
* Added one section for "Semi Joins with Watermarking", similar to "Outer Joins with Watermarking".
* Updated "Support matrix for joins in streaming queries" to reflect latest fact for full outer and left semi join.
### Why are the changes needed?
Good for users and developers to follow guide to try out these two new features.
### Does this PR introduce _any_ user-facing change?
Yes. They will see the corresponding updated guide.
### How was this patch tested?
No, just documentation change. Previewed the markdown file in browser.
Also attached here for the change to the "Support matrix for joins in streaming queries" table.
<img width="896" alt="Screen Shot 2021-02-16 at 8 12 07 PM" src="https://user-images.githubusercontent.com/4629931/108155275-73c92e80-7093-11eb-9f0b-c8b4bb7321e5.png">
Closes#31572 from c21/ss-doc.
Authored-by: Cheng Su <chengsu@fb.com>
Signed-off-by: Jungtaek Lim <kabhwan.opensource@gmail.com>
### What changes were proposed in this pull request?
This PR changes the type mapping for `money` and `money[]` types for PostgreSQL.
Currently, those types are tried to convert to `DoubleType` and `ArrayType` of `double` respectively.
But the JDBC driver seems not to be able to handle those types properly.
https://github.com/pgjdbc/pgjdbc/issues/100https://github.com/pgjdbc/pgjdbc/issues/1405
Due to these issue, we can get the error like as follows.
money type.
```
[info] org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0) (192.168.1.204 executor driver): org.postgresql.util.PSQLException: Bad value for type double : 1,000.00
[info] at org.postgresql.jdbc.PgResultSet.toDouble(PgResultSet.java:3104)
[info] at org.postgresql.jdbc.PgResultSet.getDouble(PgResultSet.java:2432)
[info] at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$5(JdbcUtils.scala:418)
```
money[] type.
```
[info] org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0) (192.168.1.204 executor driver): org.postgresql.util.PSQLException: Bad value for type double : $2,000.00
[info] at org.postgresql.jdbc.PgResultSet.toDouble(PgResultSet.java:3104)
[info] at org.postgresql.jdbc.ArrayDecoding$5.parseValue(ArrayDecoding.java:235)
[info] at org.postgresql.jdbc.ArrayDecoding$AbstractObjectStringArrayDecoder.populateFromString(ArrayDecoding.java:122)
[info] at org.postgresql.jdbc.ArrayDecoding.readStringArray(ArrayDecoding.java:764)
[info] at org.postgresql.jdbc.PgArray.buildArray(PgArray.java:310)
[info] at org.postgresql.jdbc.PgArray.getArrayImpl(PgArray.java:171)
[info] at org.postgresql.jdbc.PgArray.getArray(PgArray.java:111)
```
For money type, a known workaround is to treat it as string so this PR do it.
For money[], however, there is no reasonable workaround so this PR remove the support.
### Why are the changes needed?
This is a bug.
### Does this PR introduce _any_ user-facing change?
Yes. As of this PR merged, money type is mapped to `StringType` rather than `DoubleType` and the support for money[] is stopped.
For money type, if the value is less than one thousand, `$100.00` for instance, it works without this change so I also updated the migration guide because it's a behavior change for such small values.
On the other hand, money[] seems not to work with any value but mentioned in the migration guide just in case.
### How was this patch tested?
New test.
Closes#31442 from sarutak/fix-for-money-type.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Kousuke Saruta <sarutak@oss.nttdata.com>
### What changes were proposed in this pull request?
JDBC connection provider API and embedded connection providers already added to the code but no in-depth description about the internals. In this PR I've added both user and developer documentation and additionally added an example custom JDBC connection provider.
### Why are the changes needed?
No documentation and example custom JDBC provider.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
```
cd docs/
SKIP_API=1 jekyll build
```
<img width="793" alt="Screenshot 2021-02-02 at 16 35 43" src="https://user-images.githubusercontent.com/18561820/106623428-e48d2880-6574-11eb-8d14-e5c2aa7c37f1.png">
Closes#31384 from gaborgsomogyi/SPARK-31816.
Authored-by: Gabor Somogyi <gabor.g.somogyi@gmail.com>
Signed-off-by: Takeshi Yamamuro <yamamuro@apache.org>
### What changes were proposed in this pull request?
Passing around the output attributes should have more benefits like keeping the exprID unchanged to avoid bugs when we apply more operators above the command output DataFrame.
This PR did 2 things ：
1. After this pr, a `SHOW TBLPROPERTIES` clause's output shows `key` and `value` columns whether you specify the table property `key`. Before this pr, a `SHOW TBLPROPERTIES` clause's output only show a `value` column when you specify the table property `key`..
2. Keep `SHOW TBLPROPERTIES` command's output attribute exprId unchanged.
### Why are the changes needed?
1. Keep `SHOW TBLPROPERTIES`'s output schema consistence
2. Keep `SHOW TBLPROPERTIES` command's output attribute exprId unchanged.
### Does this PR introduce _any_ user-facing change?
After this pr, a `SHOW TBLPROPERTIES` clause's output shows `key` and `value` columns whether you specify the table property `key`. Before this pr, a `SHOW TBLPROPERTIES` clause's output only show a `value` column when you specify the table property `key`.
Before this PR:
```
sql > SHOW TBLPROPERTIES tabe_name('key')
value
value_of_key
```
After this PR
```
sql > SHOW TBLPROPERTIES tabe_name('key')
key value
key value_of_key
```
### How was this patch tested?
Added UT
Closes#31378 from AngersZhuuuu/SPARK-34240.
Lead-authored-by: Angerszhuuuu <angers.zhu@gmail.com>
Co-authored-by: AngersZhuuuu <angers.zhu@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This follows up #31160 to update score function in the document.
### Why are the changes needed?
Currently we use `f_classif`, `ch2`, `f_regression`, which sound to me the sklearn's naming. It is good to have it but I think it is nice if we have formal score function name with sklearn's ones.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
No, only doc change.
Closes#31531 from viirya/SPARK-34080-minor.
Authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Remove an unnecessary quote in the documentation.
Super trivial.
### Why are the changes needed?
Fix a mistake.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Just doc
Closes#31523 from gengliangwang/removeQuote.
Authored-by: Gengliang Wang <gengliang.wang@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
The current implement of some DDL not unify the output and not pass the output properly to physical command.
Such as: The `ShowTables` output attributes `namespace`, but `ShowTablesCommand` output attributes `database`.
As the query plan, this PR pass the output attributes from `ShowTables` to `ShowTablesCommand`, `ShowTableExtended ` to `ShowTablesCommand`.
Take `show tables` and `show table extended like 'tbl'` as example.
The output before this PR:
`show tables`
|database|tableName|isTemporary|
-- | -- | --
| default| tbl| false|
If catalog is v2 session catalog, the output before this PR:
|namespace|tableName|
-- | --
| default| tbl
`show table extended like 'tbl'`
|database|tableName|isTemporary| information|
-- | -- | -- | --
| default| tbl| false|Database: default...|
The output after this PR:
`show tables`
|namespace|tableName|isTemporary|
-- | -- | --
| default| tbl| false|
`show table extended like 'tbl'`
|namespace|tableName|isTemporary| information|
-- | -- | -- | --
| default| tbl| false|Database: default...|
### Why are the changes needed?
This PR have benefits as follows:
First, Unify schema for the output of SHOW TABLES.
Second, pass the output attributes could keep the expr ID unchanged, so that avoid bugs when we apply more operators above the command output dataframe.
### Does this PR introduce _any_ user-facing change?
Yes.
The output schema of `SHOW TABLES` replace `database` by `namespace`.
### How was this patch tested?
Jenkins test.
Closes#31245 from beliefer/SPARK-34157.
Lead-authored-by: gengjiaan <gengjiaan@360.cn>
Co-authored-by: beliefer <beliefer@163.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
docs/pyspark-migration-guide.md
### Why are the changes needed?
broken link
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Manually build and check
Closes#31514 from raphaelauv/patch-2.
Authored-by: raphaelauv <raphaelauv@users.noreply.github.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This is a followup of https://github.com/apache/spark/pull/26006
In #26006 , we merged the v1 and v2 SHOW DATABASES/NAMESPACES commands, but we missed a behavior change that the output schema of SHOW DATABASES becomes different.
This PR adds a legacy config to restore the old schema, with a migration guide item to mention this behavior change.
### Why are the changes needed?
Improve backward compatibility
### Does this PR introduce _any_ user-facing change?
No (the legacy config is false by default)
### How was this patch tested?
a new test
Closes#31474 from cloud-fan/command-schema.
Lead-authored-by: Wenchen Fan <cloud0fan@gmail.com>
Co-authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Correct the version of SQL configuration `spark.sql.legacy.parseNullPartitionSpecAsStringLiteral` from 3.2.0 to 3.0.2.
Also, revise the documentation and test case.
### Why are the changes needed?
The release version in https://github.com/apache/spark/pull/31421 was wrong.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Unit tests
Closes#31434 from gengliangwang/reviseVersion.
Authored-by: Gengliang Wang <gengliang.wang@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
In spark, the `count(table.*)` may cause very weird result, for example:
```
select count(*) from (select 1 as a, null as b) t;
output: 1
select count(t.*) from (select 1 as a, null as b) t;
output: 0
```
This is because spark expands `t.*` while converts `*` to count(1), this will confuse
users. After checking the ANSI standard, `count(*)` should always be `count(1)` while `count(t.*)`
is not allowed. What's more, this is also not allowed by common databases, e.g. MySQL, Oracle.
So, this PR proposes to block the ambiguous behavior and print a clear error message for users.
### Why are the changes needed?
to avoid ambiguous behavior and follow ANSI standard and other SQL engines
### Does this PR introduce _any_ user-facing change?
Yes, `count(table.*)` behavior will be blocked and output an error message.
### How was this patch tested?
newly added and existing tests
Closes#31286 from linhongliu-db/fix-table-star.
Authored-by: Linhong Liu <linhong.liu@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This is a follow up for https://github.com/apache/spark/pull/30538.
It adds a legacy conf `spark.sql.legacy.parseNullPartitionSpecAsStringLiteral` in case users wants the legacy behavior.
It also adds document for the behavior change.
### Why are the changes needed?
In case users want the legacy behavior, they can set `spark.sql.legacy.parseNullPartitionSpecAsStringLiteral` as true.
### Does this PR introduce _any_ user-facing change?
Yes, adding a legacy configuration to restore the old behavior.
### How was this patch tested?
Unit test.
Closes#31421 from gengliangwang/legacyNullStringConstant.
Authored-by: Gengliang Wang <gengliang.wang@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR completes snake_case rule at functions APIs across the languages, see also SPARK-10621.
In more details, this PR:
- Adds `count_distinct` in Scala Python, and R, and document that `count_distinct` is encouraged. This was not deprecated because `countDistinct` is pretty commonly used. We could deprecate in the future releases.
- (Scala-specific) adds `typedlit` but doesn't deprecate `typedLit` which is arguably commonly used. Likewise, we could deprecate in the future releases.
- Deprecates and renames:
- `sumDistinct` -> `sum_distinct`
- `bitwiseNOT` -> `bitwise_not`
- `shiftLeft` -> `shiftleft` (matched with SQL name in `FunctionRegistry`)
- `shiftRight` -> `shiftright` (matched with SQL name in `FunctionRegistry`)
- `shiftRightUnsigned` -> `shiftrightunsigned` (matched with SQL name in `FunctionRegistry`)
- (Scala-specific) `callUDF` -> `call_udf`
### Why are the changes needed?
To keep the consistent naming in APIs.
### Does this PR introduce _any_ user-facing change?
Yes, it deprecates some APIs and add new renamed APIs as described above.
### How was this patch tested?
Unittests were added.
Closes#31408 from HyukjinKwon/SPARK-34306.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR aims to remove `internal()` from `spark.kubernetes.executor.podNamePrefix` in order to make it the configuration public.
### Why are the changes needed?
In line with K8s GA, this will allow some users control the full executor pod names officially.
This is useful when we want a custom executor pod name pattern independently from the app name.
### Does this PR introduce _any_ user-facing change?
No, this has been there since Apache Spark 2.3.0.
### How was this patch tested?
N/A.
Closes#31386 from dongjoon-hyun/SPARK-34281.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Add document for the behavior change in SPARK-34052, in SQL migration guide.
### Why are the changes needed?
Document behavior change for Spark users.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
N/A
Closes#31351 from sunchao/SPARK-34052-followup.
Authored-by: Chao Sun <sunchao@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Add notice about keep hive version consistence when config hive jars location
With PR #29881, if we don't keep hive version consistence. we will got below error.
```
Builtin jars can only be used when hive execution version == hive metastore version. Execution: 2.3.8 != Metastore: 1.2.1. Specify a valid path to the correct hive jars using spark.sql.hive.metastore.jars or change spark.sql.hive.metastore.version to 2.3.8.
```
### Why are the changes needed?
Make config doc detail
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Not need
Closes#31317 from AngersZhuuuu/SPARK-32852-followup.
Authored-by: Angerszhuuuu <angers.zhu@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This is a follow up of the PRs https://github.com/apache/spark/pull/31066 and https://github.com/apache/spark/pull/31304 that changed behavior of some commands regarding to table cache refreshing. The PR updates the SQL migration guide, in particular, the item which describes new behavior.
### Why are the changes needed?
To inform users about command behavior changes.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
N/A
Closes#31309 from MaxGekk/refreshTable-sql-migration-guide.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR changes cache refreshing of v1 tables in v1 commands. In particular, v1 table dependents are not removed from the cache after this PR. Comparing to current implementation, we just clear cached data of all dependents and keep them in the cache. So, the next actions will fill in the cached data of the original v1 table and its dependents. In more details:
1. Modified the `CatalogImpl.refreshTable()` method to use `recacheByPlan()` instead of `lookupCachedData()`, `uncacheQuery()` and `cacheQuery()`. Users can call this method via public API like `spark.catalog.refreshTable()`.
2. Rewritten the part in `CatalogImpl.refreshTable()` which was responsible for table meta-data refreshing because this code stopped to work properly after removing of the second `sparkSession.table(tableIdent)`.
3. Added new private method `invalidateCachedTable()` to `SessionCatalog`. Comparing to the existing `SessionCatalog.refreshTable`, it invalidates the relation cache only. If we called `SessionCatalog.refreshTable` from `CatalogImpl.refreshTable()`, we would refresh temporary and global temporary views twice (that could lead to refreshing file index twice).
### Why are the changes needed?
1. This should improve user experience with table/view caching. For example, let's imagine that an user has cached v1 table and cached view based on the table. And the user passed the table to external library which drops/renames/adds partitions in the v1 table. Unfortunately, the user gets the view uncached after that even he/she hasn't uncached the view explicitly.
2. To improve code maintenance.
3. To reduce the amount of calls to Hive external catalog.
4. Also this should speed up table recaching.
5. To have the same behavior as for v2 tables supported by https://github.com/apache/spark/pull/31172
### Does this PR introduce _any_ user-facing change?
From the view of the correctness of query results, there are no behavior changes but the changes might influence on consuming memory and query execution time. For example:
Before:
```scala
scala> sql("CREATE TABLE tbl (c int)")
scala> sql("CACHE TABLE tbl")
scala> sql("CREATE VIEW v AS SELECT * FROM tbl")
scala> sql("CACHE TABLE v")
scala> spark.catalog.isCached("v")
res6: Boolean = true
scala> spark.catalog.refreshTable("tbl")
scala> spark.catalog.isCached("v")
res8: Boolean = false
```
After:
```scala
scala> spark.catalog.refreshTable("tbl")
scala> spark.catalog.isCached("v")
res8: Boolean = true
```
### How was this patch tested?
1. Added new unit tests that create a view, a temporary view and a global temporary view on top of v1/v2 tables, and refresh the base table via `ALTER TABLE .. ADD/DROP/RENAME PARTITION`.
2. By running the unified test suites:
```
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *AlterTableAddPartitionSuite"
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *AlterTableDropPartitionSuite"
# build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *AlterTableRenamePartitionSuite"
```
Closes#31206 from MaxGekk/refreshTable-recache-by-plan.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
When ruby version is 3.0, jekyll server will failed with
```
yi.zhu$ SKIP_API=1 jekyll serve --watch
Configuration file: /Users/yi.zhu/Documents/project/Angerszhuuuu/spark/docs/_config.yml
Source: /Users/yi.zhu/Documents/project/Angerszhuuuu/spark/docs
Destination: /Users/yi.zhu/Documents/project/Angerszhuuuu/spark/docs/_site
Incremental build: disabled. Enable with --incremental
Generating...
done in 5.085 seconds.
Auto-regeneration: enabled for '/Users/yi.zhu/Documents/project/Angerszhuuuu/spark/docs'
------------------------------------------------
Jekyll 4.2.0 Please append `--trace` to the `serve` command
for any additional information or backtrace.
------------------------------------------------
<internal:/usr/local/Cellar/ruby/3.0.0_1/lib/ruby/3.0.0/rubygems/core_ext/kernel_require.rb>:85:in `require': cannot load such file -- webrick (LoadError)
from <internal:/usr/local/Cellar/ruby/3.0.0_1/lib/ruby/3.0.0/rubygems/core_ext/kernel_require.rb>:85:in `require'
from /Users/yi.zhu/.gem/ruby/3.0.0/gems/jekyll-4.2.0/lib/jekyll/commands/serve/servlet.rb:3:in `<top (required)>'
from /Users/yi.zhu/.gem/ruby/3.0.0/gems/jekyll-4.2.0/lib/jekyll/commands/serve.rb:179:in `require_relative'
from /Users/yi.zhu/.gem/ruby/3.0.0/gems/jekyll-4.2.0/lib/jekyll/commands/serve.rb:179:in `setup'
from /Users/yi.zhu/.gem/ruby/3.0.0/gems/jekyll-4.2.0/lib/jekyll/commands/serve.rb💯in `process'
from /Users/yi.zhu/.gem/ruby/3.0.0/gems/jekyll-4.2.0/lib/jekyll/command.rb:91:in `block in process_with_graceful_fail'
from /Users/yi.zhu/.gem/ruby/3.0.0/gems/jekyll-4.2.0/lib/jekyll/command.rb:91:in `each'
from /Users/yi.zhu/.gem/ruby/3.0.0/gems/jekyll-4.2.0/lib/jekyll/command.rb:91:in `process_with_graceful_fail'
from /Users/yi.zhu/.gem/ruby/3.0.0/gems/jekyll-4.2.0/lib/jekyll/commands/serve.rb:86:in `block (2 levels) in init_with_program'
from /Users/yi.zhu/.gem/ruby/3.0.0/gems/mercenary-0.4.0/lib/mercenary/command.rb:221:in `block in execute'
from /Users/yi.zhu/.gem/ruby/3.0.0/gems/mercenary-0.4.0/lib/mercenary/command.rb:221:in `each'
from /Users/yi.zhu/.gem/ruby/3.0.0/gems/mercenary-0.4.0/lib/mercenary/command.rb:221:in `execute'
from /Users/yi.zhu/.gem/ruby/3.0.0/gems/mercenary-0.4.0/lib/mercenary/program.rb:44:in `go'
from /Users/yi.zhu/.gem/ruby/3.0.0/gems/mercenary-0.4.0/lib/mercenary.rb:21:in `program'
from /Users/yi.zhu/.gem/ruby/3.0.0/gems/jekyll-4.2.0/exe/jekyll:15:in `<top (required)>'
from /usr/local/bin/jekyll:23:in `load'
from /usr/local/bin/jekyll:23:in `<main>'
```
This issue is solved in https://github.com/jekyll/jekyll/issues/8523
### Why are the changes needed?
Fix build issue
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Not need
Closes#31263 from AngersZhuuuu/SPARK-34181.
Lead-authored-by: Angerszhuuuu <angers.zhu@gmail.com>
Co-authored-by: AngersZhuuuu <angers.zhu@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Update Avro dependency to version 1.10.1
### Why are the changes needed?
To catch up multiple improvements of Avro as well as fix security issues on transitive dependencies.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Since there were no API changes required we just run the tests
Closes#31232 from iemejia/SPARK-27733-avro-upgrade.
Authored-by: Ismaël Mejía <iemejia@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR aims to add a note for Apache Arrow project's `PyArrow` compatibility for Python 3.9.
### Why are the changes needed?
Although Apache Spark documentation claims `Spark runs on Java 8/11, Scala 2.12, Python 3.6+ and R 3.5+.`,
Apache Arrow's `PyArrow` is not compatible with Python 3.9.x yet. Without installing `PyArrow` library, PySpark UTs passed without any problem. So, it would be enough to add a note for this limitation and the compatibility link of Apache Arrow website.
- https://arrow.apache.org/docs/python/install.html#python-compatibility
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
**BEFORE**
<img width="804" alt="Screen Shot 2021-01-19 at 1 45 07 PM" src="https://user-images.githubusercontent.com/9700541/105096867-8fbdbe00-5a5c-11eb-88f7-8caae2427583.png">
**AFTER**
<img width="908" alt="Screen Shot 2021-01-19 at 7 06 41 PM" src="https://user-images.githubusercontent.com/9700541/105121661-85fe7f80-5a89-11eb-8af7-1b37e12c55c1.png">
Closes#31251 from dongjoon-hyun/SPARK-34162.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR is the 3rd try to upgrade Scala 2.12.x in order to see the feasibility.
- https://github.com/apache/spark/pull/27929 (Upgrade Scala to 2.12.11, wangyum )
- https://github.com/apache/spark/pull/30940 (Upgrade Scala to 2.12.12, viirya )
`silencer` library is updated accordingly. And, Kafka version upgrade is required because it fails like the following.
```
[info] KafkaDataConsumerSuite:
[info] org.apache.spark.streaming.kafka010.KafkaDataConsumerSuite *** ABORTED *** (1 second, 580 milliseconds)
[info] java.lang.NoClassDefFoundError: scala/math/Ordering$$anon$7
[info] at kafka.api.ApiVersion$.orderingByVersion(ApiVersion.scala:45)
```
### Why are the changes needed?
Apache Spark was stuck to 2.12.10 due to the regression in Scala 2.12.11 and 2.12.12. This will bring all the bug fixes.
- https://github.com/scala/scala/releases/tag/v2.12.13
- https://github.com/scala/scala/releases/tag/v2.12.12
- https://github.com/scala/scala/releases/tag/v2.12.11
### Does this PR introduce _any_ user-facing change?
Yes, but this is a bug-fixed version.
### How was this patch tested?
Pass the CIs.
Closes#31223 from dongjoon-hyun/SPARK-31168.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Hive 2.3.8 changes:
HIVE-19662: Upgrade Avro to 1.8.2
HIVE-24324: Remove deprecated API usage from Avro
HIVE-23980: Shade Guava from hive-exec in Hive 2.3
HIVE-24436: Fix Avro NULL_DEFAULT_VALUE compatibility issue
HIVE-24512: Exclude calcite in packaging.
HIVE-22708: Fix for HttpTransport to replace String.equals
HIVE-24551: Hive should include transitive dependencies from calcite after shading it
HIVE-24553: Exclude calcite from test-jar dependency of hive-exec
### Why are the changes needed?
Upgrade Avro and Parquet to latest version.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing test add test try to upgrade Parquet to 1.11.1 and Avro to 1.10.1: https://github.com/apache/spark/pull/30517Closes#30657 from wangyum/SPARK-33696.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR aims to update the Parquet website link from http://parquet.io to https://parquet.apache.orc
### Why are the changes needed?
The old website goes to the incubator site.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
N/A
Closes#31208 from williamhyun/minor-parquet.
Authored-by: William Hyun <williamhyun3@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Add UnivariateFeatureSelector
### Why are the changes needed?
Have one UnivariateFeatureSelector, so we don't need to have three Feature Selectors.
### Does this PR introduce _any_ user-facing change?
Yes
```
selector = UnivariateFeatureSelector(featureCols=["x", "y", "z"], labelCol=["target"], featureType="categorical", labelType="continuous", selectorType="numTopFeatures", numTopFeatures=100)
```
Or
numTopFeatures
```
selector = UnivariateFeatureSelector(featureCols=["x", "y", "z"], labelCol=["target"], scoreFunction="f_classif", selectorType="numTopFeatures", numTopFeatures=100)
```
### How was this patch tested?
Add Unit test
Closes#31160 from huaxingao/UnivariateSelector.
Authored-by: Huaxin Gao <huaxing@us.ibm.com>
Signed-off-by: Weichen Xu <weichen.xu@databricks.com>
### What changes were proposed in this pull request?
This PR aims to strip auto-generated cast. The main logic is:
1. Add tag if Cast is specified by user.
2. Wrap `PrettyAttribute` in usePrettyExpression.
### Why are the changes needed?
Make sql consistent with dsl. Here is an inconsistent example before this PR:
```
-- output field name: FLOOR(1)
spark.emptyDataFrame.select(floor(lit(1)))
-- output field name: FLOOR(CAST(1 AS DOUBLE))
spark.sql("select floor(1)")
```
Note that, we don't remove the `Cast` so the auto-generated `Cast` can still work. The only changed place is `usePrettyExpression`, we use `PrettyAttribute` replace `Cast` to give a better sql string.
### Does this PR introduce _any_ user-facing change?
Yes, the default field name may change.
### How was this patch tested?
Add test and pass exists test.
Closes#31034 from ulysses-you/SPARK-33989.
Authored-by: ulysses-you <ulyssesyou18@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This is a followup PR for SPARK-33690 (#30647) .
In addition to the original PR, this PR intends to escape the following meta-characters in `Dataset#showString`.
* `\r` (carrige ret)
* `\f` (form feed)
* `\b` (backspace)
* `\u000B` (vertical tab)
* `\u0007` (bell)
### Why are the changes needed?
To avoid breaking the layout of `Dataset#showString`.
`\u0007` does not break the layout of `Dataset#showString` but it's noisy (beeps for each row) so it should be also escaped.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Modified the existing tests.
I also build the documents and check the generated html for `sql-migration-guide.md`.
Closes#31144 from sarutak/escape-metacharacters-in-getRows.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
Add min threshold time speculation config
### Why are the changes needed?
When we turn on speculation with default configs we have the last 10% of the tasks subject to speculation. There are a lot of stages where the stage runs for few seconds to minutes. Also in general we don't want to speculate tasks that run within a minimum threshold. By setting a minimum threshold for speculation config gives us better control for speculative tasks
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Unit test
Closes#30710 from redsanket/SPARK-33741.
Lead-authored-by: schintap <schintap@verizonmedia.com>
Co-authored-by: Sanket Chintapalli <chintapalli.sanketreddy@gmail.com>
Signed-off-by: Thomas Graves <tgraves@apache.org>
### What changes were proposed in this pull request?
This patch adds a few description to SS doc about offset reset and data loss.
### Why are the changes needed?
During recent SS test, the behavior of gradual reducing input rows are confusing me. Comparing with Flink, I do not see a similar behavior. After looking into the code and doing some tests, I feel it is better to add some more description there in SS doc.
### Does this PR introduce _any_ user-facing change?
No, doc only.
### How was this patch tested?
Doc only.
Closes#31089 from viirya/ss-minor-5.
Authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR tweaks the width of left-menu of Spark SQL Guide.
When I view the Spark SQL Guide with browsers on macOS, the title `Spark SQL Guide` looks prettily.
But I often use Pop!_OS, an Ubuntu variant, and the title is overlapped with browsers on it.
After this change, the title is no longer overlapped.
### Why are the changes needed?
For the pretty layout.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Built the document with `cd docs && SKIP_API=1 jekyll build` and confirmed the layout.
Closes#31091 from sarutak/modify-layout-sparksql-guide.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
Kafka delegation token is obtained with `AdminClient` where security settings can be set. Keystore and trustrore type however can't be set. In this PR I've added these new configurations. This can be useful when the type is different. A good example is to make Spark FIPS compliant where the default JKS is not accepted.
### Why are the changes needed?
Missing configurations.
### Does this PR introduce _any_ user-facing change?
Yes, adding 2 additional config parameters.
### How was this patch tested?
Existing + modified unit tests + simple Kafka to Kafka app on cluster.
Closes#31070 from gaborgsomogyi/SPARK-34032.
Authored-by: Gabor Somogyi <gabor.g.somogyi@gmail.com>
Signed-off-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com>
### What changes were proposed in this pull request?
This PR proposes to:
- Add a link of quick start in PySpark docs into "Programming Guides" in Spark main docs
- `ML` / `MLlib` -> `MLlib (DataFrame-based)` / `MLlib (RDD-based)` in API reference page
- Mention other user guides as well because the guide such as [ML](http://spark.apache.org/docs/latest/ml-guide.html) and [SQL](http://spark.apache.org/docs/latest/sql-programming-guide.html).
- Mention other migration guides as well because PySpark can get affected by it.
### Why are the changes needed?
For better documentation.
### Does this PR introduce _any_ user-facing change?
It fixes user-facing docs. However, it's not released out yet.
### How was this patch tested?
Manually tested by running:
```bash
cd docs
SKIP_SCALADOC=1 SKIP_RDOC=1 SKIP_SQLDOC=1 jekyll serve --watch
```
Closes#31082 from HyukjinKwon/SPARK-34041.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
