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Apache Spark - A unified analytics engine for large-scale data processing
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Jungtaek Lim (HeartSaVioR) 94946e4836 [SPARK-29281][SQL] Correct example of Like/RLike to test the origin intention correctly 
### What changes were proposed in this pull request?

This patch fixes examples of Like/RLike to test its origin intention correctly. The example doesn't consider the default value of spark.sql.parser.escapedStringLiterals: it's false by default.

Please take a look at current example of Like:

d72f39897b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/regexpExpressions.scala (L97-L106)

If spark.sql.parser.escapedStringLiterals=false, then it should fail as there's `\U` in pattern (spark.sql.parser.escapedStringLiterals=false by default) but it doesn't fail.

```
The escape character is '\'. If an escape character precedes a special symbol or another
escape character, the following character is matched literally. It is invalid to escape
any other character.
```

For the query

```
SET spark.sql.parser.escapedStringLiterals=false;
SELECT '%SystemDrive%\Users\John' like '\%SystemDrive\%\Users%';
```

SQL parser removes single `\` (not sure that is intended) so the expressions of Like are constructed as following (I've printed out expression of left and right for Like/RLike):

> LIKE - left `%SystemDrive%UsersJohn` / right `\%SystemDrive\%Users%`

which are no longer having origin intention (see left).

Below query tests the origin intention:

```
SET spark.sql.parser.escapedStringLiterals=false;
SELECT '%SystemDrive%\\Users\\John' like '\%SystemDrive\%\\\\Users%';
```

> LIKE - left `%SystemDrive%\Users\John` / right `\%SystemDrive\%\\Users%`

Note that `\\\\` is needed in pattern as `StringUtils.escapeLikeRegex` requires `\\` to represent normal character of `\`.

Same for RLIKE:

```
SET spark.sql.parser.escapedStringLiterals=true;
SELECT '%SystemDrive%\Users\John' rlike '%SystemDrive%\\Users.*';
```

> RLIKE - left `%SystemDrive%\Users\John` / right `%SystemDrive%\\Users.*`

which is OK, but

```
SET spark.sql.parser.escapedStringLiterals=false;
SELECT '%SystemDrive%\Users\John' rlike '%SystemDrive%\Users.*';
```

> RLIKE - left `%SystemDrive%UsersJohn` / right `%SystemDrive%Users.*`

which no longer haves origin intention.

Below query tests the origin intention:
```
SET spark.sql.parser.escapedStringLiterals=true;
SELECT '%SystemDrive%\\Users\\John' rlike '%SystemDrive%\\\\Users.*';
```

> RLIKE - left `%SystemDrive%\Users\John` / right `%SystemDrive%\\Users.*`

### Why are the changes needed?

Because the example doesn't test the origin intention. Spark is now running automated tests from these examples, so now it's not only documentation issue but also test issue.

### Does this PR introduce any user-facing change?

No, as it only corrects documentation.

### How was this patch tested?

Added debug log (like above) and ran queries from `spark-sql`.

Closes #25957 from HeartSaVioR/SPARK-29281.

Authored-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2019-09-29 03:05:49 +09:00
.github [SPARK-29199][INFRA] Add linters and license/dependency checkers to GitHub Action 2019-09-21 08:13:00 -07:00
assembly [SPARK-27300][GRAPH] Add Spark Graph modules and dependencies 2019-06-09 00:26:26 -07:00
bin [SPARK-28525][DEPLOY] Allow Launcher to be applied Java options 2019-07-30 12:45:32 -07:00
build [SPARK-29159][BUILD] Increase ReservedCodeCacheSize to 1G 2019-09-19 00:24:15 -07:00
common [SPARK-25341][CORE] Support rolling back a shuffle map stage and re-generate the shuffle files 2019-09-23 16:16:52 +08:00
conf [SPARK-29032][CORE] Add PrometheusServlet to monitor Master/Worker/Driver 2019-09-13 21:31:21 +00:00
core [SPARK-29263][SCHEDULER] Update availableSlots in resourceOffers() before checking available slots for barrier taskSet 2019-09-27 11:18:32 -07:00
data [SPARK-22666][ML][SQL] Spark datasource for image format 2018-09-05 11:59:00 -07:00
dev [SPARK-29226][BUILD] Upgrade jackson-databind to 2.9.10 and fix vulnerabilities 2019-09-24 22:05:13 -07:00
docs [SPARK-29275][SQL][DOC] Describe special date/timestamp values in the SQL migration guide 2019-09-27 10:36:20 -07:00
examples [SPARK-28980][CORE][SQL][STREAMING][MLLIB] Remove most items deprecated in Spark 2.2.0 or earlier, for Spark 3 2019-09-09 10:19:40 -05:00
external [SPARK-27748][SS][FOLLOWUP] Correct the order of logging token as debug log 2019-09-26 08:32:03 -07:00
graph [SPARK-27300][GRAPH] Add Spark Graph modules and dependencies 2019-06-09 00:26:26 -07:00
graphx [SPARK-29042][CORE] Sampling-based RDD with unordered input should be INDETERMINATE 2019-09-13 14:07:00 -07:00
hadoop-cloud [SPARK-28903][STREAMING][PYSPARK][TESTS] Fix AWS JDK version conflict that breaks Pyspark Kinesis tests 2019-08-31 10:29:46 -05:00
launcher [SPARK-29070][CORE] Make SparkLauncher log full spark-submit command line 2019-09-27 11:32:22 -07:00
licenses [SPARK-27557][DOC] Add copy button to Python API docs for easier copying of code-blocks 2019-05-01 11:26:18 -05:00
licenses-binary [SPARK-28772][BUILD][MLLIB] Update breeze to 1.0 2019-09-20 20:31:26 -07:00
mllib [SPARK-29258][ML][PYSPARK] parity between ml.evaluator and mllib.metrics 2019-09-27 13:30:03 +08:00
mllib-local [SPARK-29121][ML][MLLIB] Support for dot product operation on Vector(s) 2019-09-21 14:26:54 -05:00
project [SPARK-28957][SQL] Copy any "spark.hive.foo=bar" spark properties into hadoop conf as "hive.foo=bar" 2019-09-25 15:54:44 +08:00
python [SPARK-29240][PYTHON] Pass Py4J column instance to support PySpark column in element_at function 2019-09-27 11:04:55 -07:00
R [SPARK-28678][DOC] Specify that array indices start at 1 for function slice in R Scala Python 2019-09-24 18:57:54 +09:00
repl [MINOR][BUILD] Fix about 15 misc build warnings 2019-09-19 11:37:42 -07:00
resource-managers [SPARK-28937][SPARK-28936][KUBERNETES] Reduce test flakyness 2019-09-20 10:08:16 -07:00
sbin [SPARK-28164] Fix usage description of start-slave.sh 2019-06-26 12:42:33 -05:00
sql [SPARK-29281][SQL] Correct example of Like/RLike to test the origin intention correctly 2019-09-29 03:05:49 +09:00
streaming [SPARK-23197][STREAMING][TESTS] Fix ReceiverSuite."receiver_life_cycle" to not rely on timing 2019-09-25 10:59:08 -07:00
tools [SPARK-25956] Make Scala 2.12 as default Scala version in Spark 3.0 2018-11-14 16:22:23 -08:00
.gitattributes [SPARK-3870] EOL character enforcement 2014-10-31 12:39:52 -07:00
.gitignore [SPARK-27371][CORE] Support GPU-aware resources scheduling in Standalone 2019-08-09 07:49:03 -05:00
appveyor.yml [SPARK-28759][BUILD] Upgrade scala-maven-plugin to 4.2.0 and fix build profile on AppVeyor 2019-08-30 09:39:15 -07:00
CONTRIBUTING.md [MINOR][DOCS] Tighten up some key links to the project and download pages to use HTTPS 2019-05-21 10:56:42 -07:00
LICENSE [SPARK-27557][DOC] Add copy button to Python API docs for easier copying of code-blocks 2019-05-01 11:26:18 -05:00
LICENSE-binary [SPARK-29016][BUILD] Update LICENSE and NOTICE for Hive 2.3 2019-09-23 09:19:04 -07:00
NOTICE [SPARK-23654][BUILD] remove jets3t as a dependency of spark 2018-08-16 12:34:23 -07:00
NOTICE-binary [SPARK-29016][BUILD] Update LICENSE and NOTICE for Hive 2.3 2019-09-23 09:19:04 -07:00
pom.xml [SPARK-29226][BUILD] Upgrade jackson-databind to 2.9.10 and fix vulnerabilities 2019-09-24 22:05:13 -07:00
README.md [SPARK-28473][DOC] Stylistic consistency of build command in README 2019-07-23 16:29:46 -07:00
scalastyle-config.xml [SPARK-25986][BUILD] Add rules to ban throw Errors in application code 2018-11-14 13:05:18 -08:00

README.md

Apache Spark

Spark is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing.

https://spark.apache.org/

Jenkins Build AppVeyor Build PySpark Coverage

Online Documentation

You can find the latest Spark documentation, including a programming guide, on the project web page. This README file only contains basic setup instructions.

Building Spark

Spark is built using Apache Maven. To build Spark and its example programs, run:

./build/mvn -DskipTests clean package

(You do not need to do this if you downloaded a pre-built package.)

You can build Spark using more than one thread by using the -T option with Maven, see "Parallel builds in Maven 3". More detailed documentation is available from the project site, at "Building Spark".

For general development tips, including info on developing Spark using an IDE, see "Useful Developer Tools".

Interactive Scala Shell

The easiest way to start using Spark is through the Scala shell:

./bin/spark-shell

Try the following command, which should return 1,000,000,000:

scala> spark.range(1000 * 1000 * 1000).count()

Interactive Python Shell

Alternatively, if you prefer Python, you can use the Python shell:

./bin/pyspark

And run the following command, which should also return 1,000,000,000:

>>> spark.range(1000 * 1000 * 1000).count()

Example Programs

Spark also comes with several sample programs in the examples directory. To run one of them, use ./bin/run-example <class> [params]. For example:

./bin/run-example SparkPi

will run the Pi example locally.

You can set the MASTER environment variable when running examples to submit examples to a cluster. This can be a mesos:// or spark:// URL, "yarn" to run on YARN, and "local" to run locally with one thread, or "local[N]" to run locally with N threads. You can also use an abbreviated class name if the class is in the examples package. For instance:

MASTER=spark://host:7077 ./bin/run-example SparkPi

Many of the example programs print usage help if no params are given.

Running Tests

Testing first requires building Spark. Once Spark is built, tests can be run using:

./dev/run-tests

Please see the guidance on how to run tests for a module, or individual tests.

There is also a Kubernetes integration test, see resource-managers/kubernetes/integration-tests/README.md

A Note About Hadoop Versions

Spark uses the Hadoop core library to talk to HDFS and other Hadoop-supported storage systems. Because the protocols have changed in different versions of Hadoop, you must build Spark against the same version that your cluster runs.

Please refer to the build documentation at "Specifying the Hadoop Version and Enabling YARN" for detailed guidance on building for a particular distribution of Hadoop, including building for particular Hive and Hive Thriftserver distributions.

Configuration

Please refer to the Configuration Guide in the online documentation for an overview on how to configure Spark.

Contributing

Please review the Contribution to Spark guide for information on how to get started contributing to the project.