## What changes were proposed in this pull request?
This pr fixes the behaviour of `format("csv").option("quote", null)` along with one of spark-csv.
Also, it explicitly sets default values for CSV options in python.
## How was this patch tested?
Added tests in CSVSuite.
Author: Takeshi YAMAMURO <linguin.m.s@gmail.com>
Closes#13372 from maropu/SPARK-15585.
## What changes were proposed in this pull request?
This patch moves all user-facing structured streaming classes into sql.streaming. As part of this, I also added some since version annotation to methods and classes that don't have them.
## How was this patch tested?
Updated tests to reflect the moves.
Author: Reynold Xin <rxin@databricks.com>
Closes#13429 from rxin/SPARK-15686.
## What changes were proposed in this pull request?
Currently structured streaming only supports append output mode. This PR adds the following.
- Added support for Complete output mode in the internal state store, analyzer and planner.
- Added public API in Scala and Python for users to specify output mode
- Added checks for unsupported combinations of output mode and DF operations
- Plans with no aggregation should support only Append mode
- Plans with aggregation should support only Update and Complete modes
- Default output mode is Append mode (**Question: should we change this to automatically set to Complete mode when there is aggregation?**)
- Added support for Complete output mode in Memory Sink. So Memory Sink internally supports append and complete, update. But from public API only Complete and Append output modes are supported.
## How was this patch tested?
Unit tests in various test suites
- StreamingAggregationSuite: tests for complete mode
- MemorySinkSuite: tests for checking behavior in Append and Complete modes.
- UnsupportedOperationSuite: tests for checking unsupported combinations of DF ops and output modes
- DataFrameReaderWriterSuite: tests for checking that output mode cannot be called on static DFs
- Python doc test and existing unit tests modified to call write.outputMode.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#13286 from tdas/complete-mode.
## What changes were proposed in this pull request?
This reverts commit c24b6b679c. Sent a PR to run Jenkins tests due to the revert conflicts of `dev/deps/spark-deps-hadoop*`.
## How was this patch tested?
Jenkins unit tests, integration tests, manual tests)
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#13417 from zsxwing/revert-SPARK-11753.
## What changes were proposed in this pull request?
`a` -> `an`
I use regex to generate potential error lines:
`grep -in ' a [aeiou]' mllib/src/main/scala/org/apache/spark/ml/*/*scala`
and review them line by line.
## How was this patch tested?
local build
`lint-java` checking
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes#13317 from zhengruifeng/a_an.
## What changes were proposed in this pull request?
Also sets confs in the underlying sc when using SparkSession.builder.getOrCreate(). This is a bug-fix from a post-merge comment in https://github.com/apache/spark/pull/13289
## How was this patch tested?
Python doc-tests.
Author: Eric Liang <ekl@databricks.com>
Closes#13309 from ericl/spark-15520-1.
## What changes were proposed in this pull request?
This fixes the python SparkSession builder to allow setting confs correctly. This was a leftover TODO from https://github.com/apache/spark/pull/13200.
## How was this patch tested?
Python doc tests.
cc andrewor14
Author: Eric Liang <ekl@databricks.com>
Closes#13289 from ericl/spark-15520.
## What changes were proposed in this pull request?
Jackson suppprts `allowNonNumericNumbers` option to parse non-standard non-numeric numbers such as "NaN", "Infinity", "INF". Currently used Jackson version (2.5.3) doesn't support it all. This patch upgrades the library and make the two ignored tests in `JsonParsingOptionsSuite` passed.
## How was this patch tested?
`JsonParsingOptionsSuite`.
Author: Liang-Chi Hsieh <simonh@tw.ibm.com>
Author: Liang-Chi Hsieh <viirya@appier.com>
Closes#9759 from viirya/fix-json-nonnumric.
## What changes were proposed in this pull request?
in hive, `locate("aa", "aaa", 0)` would yield 0, `locate("aa", "aaa", 1)` would yield 1 and `locate("aa", "aaa", 2)` would yield 2, while in Spark, `locate("aa", "aaa", 0)` would yield 1, `locate("aa", "aaa", 1)` would yield 2 and `locate("aa", "aaa", 2)` would yield 0. This results from the different understanding of the third parameter in udf `locate`. It means the starting index and starts from 1, so when we use 0, the return would always be 0.
## How was this patch tested?
tested with modified `StringExpressionsSuite` and `StringFunctionsSuite`
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#13186 from adrian-wang/locate.
## What changes were proposed in this pull request?
Replace SQLContext and SparkContext with SparkSession using builder pattern in python test code.
## How was this patch tested?
Existing test.
Author: WeichenXu <WeichenXu123@outlook.com>
Closes#13242 from WeichenXu123/python_doctest_update_sparksession.
## What changes were proposed in this pull request?
Spark assumes that UDF functions are deterministic. This PR adds explicit notes about that.
## How was this patch tested?
It's only about docs.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#13087 from dongjoon-hyun/SPARK-15282.
## What changes were proposed in this pull request?
There is no way to use the Hive catalog in `pyspark-shell`. This is because we used to create a `SparkContext` before calling `SparkSession.enableHiveSupport().getOrCreate()`, which just gets the existing `SparkContext` instead of creating a new one. As a result, `spark.sql.catalogImplementation` was never propagated.
## How was this patch tested?
Manual.
Author: Andrew Or <andrew@databricks.com>
Closes#13203 from andrewor14/fix-pyspark-shell.
## What changes were proposed in this pull request?
Currently SparkSession.Builder use SQLContext.getOrCreate. It should probably the the other way around, i.e. all the core logic goes in SparkSession, and SQLContext just calls that. This patch does that.
This patch also makes sure config options specified in the builder are propagated to the existing (and of course the new) SparkSession.
## How was this patch tested?
Updated tests to reflect the change, and also introduced a new SparkSessionBuilderSuite that should cover all the branches.
Author: Reynold Xin <rxin@databricks.com>
Closes#13200 from rxin/SPARK-15075.
## What changes were proposed in this pull request?
We use autoBroadcastJoinThreshold + 1L as the default value of size estimation, that is not good in 2.0, because we will calculate the size based on size of schema, then the estimation could be less than autoBroadcastJoinThreshold if you have an SELECT on top of an DataFrame created from RDD.
This PR change the default value to Long.MaxValue.
## How was this patch tested?
Added regression tests.
Author: Davies Liu <davies@databricks.com>
Closes#13183 from davies/fix_default_size.
#### What changes were proposed in this pull request?
This follow-up PR is to address the remaining comments in https://github.com/apache/spark/pull/12385
The major change in this PR is to issue better error messages in PySpark by using the mechanism that was proposed by davies in https://github.com/apache/spark/pull/7135
For example, in PySpark, if we input the following statement:
```python
>>> l = [('Alice', 1)]
>>> df = sqlContext.createDataFrame(l)
>>> df.createTempView("people")
>>> df.createTempView("people")
```
Before this PR, the exception we will get is like
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/xiaoli/IdeaProjects/sparkDelivery/python/pyspark/sql/dataframe.py", line 152, in createTempView
self._jdf.createTempView(name)
File "/Users/xiaoli/IdeaProjects/sparkDelivery/python/lib/py4j-0.10.1-src.zip/py4j/java_gateway.py", line 933, in __call__
File "/Users/xiaoli/IdeaProjects/sparkDelivery/python/pyspark/sql/utils.py", line 63, in deco
return f(*a, **kw)
File "/Users/xiaoli/IdeaProjects/sparkDelivery/python/lib/py4j-0.10.1-src.zip/py4j/protocol.py", line 312, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o35.createTempView.
: org.apache.spark.sql.catalyst.analysis.TempTableAlreadyExistsException: Temporary table 'people' already exists;
at org.apache.spark.sql.catalyst.catalog.SessionCatalog.createTempView(SessionCatalog.scala:324)
at org.apache.spark.sql.SparkSession.createTempView(SparkSession.scala:523)
at org.apache.spark.sql.Dataset.createTempView(Dataset.scala:2328)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:237)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:128)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:211)
at java.lang.Thread.run(Thread.java:745)
```
After this PR, the exception we will get become cleaner:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/xiaoli/IdeaProjects/sparkDelivery/python/pyspark/sql/dataframe.py", line 152, in createTempView
self._jdf.createTempView(name)
File "/Users/xiaoli/IdeaProjects/sparkDelivery/python/lib/py4j-0.10.1-src.zip/py4j/java_gateway.py", line 933, in __call__
File "/Users/xiaoli/IdeaProjects/sparkDelivery/python/pyspark/sql/utils.py", line 75, in deco
raise AnalysisException(s.split(': ', 1)[1], stackTrace)
pyspark.sql.utils.AnalysisException: u"Temporary table 'people' already exists;"
```
#### How was this patch tested?
Fixed an existing PySpark test case
Author: gatorsmile <gatorsmile@gmail.com>
Closes#13126 from gatorsmile/followup-14684.
## What changes were proposed in this pull request?
This patch is a follow-up to https://github.com/apache/spark/pull/13104 and adds documentation to clarify the semantics of read.text with respect to partitioning.
## How was this patch tested?
N/A
Author: Reynold Xin <rxin@databricks.com>
Closes#13184 from rxin/SPARK-14463.
## What changes were proposed in this pull request?
The PySpark SQL `test_column_name_with_non_ascii` wants to test non-ascii column name. But it doesn't actually test it. We need to construct an unicode explicitly using `unicode` under Python 2.
## How was this patch tested?
Existing tests.
Author: Liang-Chi Hsieh <simonh@tw.ibm.com>
Closes#13134 from viirya/correct-non-ascii-colname-pytest.
## What changes were proposed in this pull request?
Update the unit test code, examples, and documents to remove calls to deprecated method `dataset.registerTempTable`.
## How was this patch tested?
This PR only changes the unit test code, examples, and comments. It should be safe.
This is a follow up of PR https://github.com/apache/spark/pull/12945 which was merged.
Author: Sean Zhong <seanzhong@databricks.com>
Closes#13098 from clockfly/spark-15171-remove-deprecation.
## What changes were proposed in this pull request?
**createDataFrame** returns inconsistent types for column names.
```python
>>> from pyspark.sql.types import StructType, StructField, StringType
>>> schema = StructType([StructField(u"col", StringType())])
>>> df1 = spark.createDataFrame([("a",)], schema)
>>> df1.columns # "col" is str
['col']
>>> df2 = spark.createDataFrame([("a",)], [u"col"])
>>> df2.columns # "col" is unicode
[u'col']
```
The reason is only **StructField** has the following code.
```
if not isinstance(name, str):
name = name.encode('utf-8')
```
This PR adds the same logic into **createDataFrame** for consistency.
```
if isinstance(schema, list):
schema = [x.encode('utf-8') if not isinstance(x, str) else x for x in schema]
```
## How was this patch tested?
Pass the Jenkins test (with new python doctest)
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#13097 from dongjoon-hyun/SPARK-15244.
## What changes were proposed in this pull request?
Deprecates registerTempTable and add dataset.createTempView, dataset.createOrReplaceTempView.
## How was this patch tested?
Unit tests.
Author: Sean Zhong <seanzhong@databricks.com>
Closes#12945 from clockfly/spark-15171.
## What changes were proposed in this pull request?
Seems db573fc743 did not remove withHiveSupport from readwrite.py
Author: Yin Huai <yhuai@databricks.com>
Closes#13069 from yhuai/fixPython.
## What changes were proposed in this pull request?
This is a followup of https://github.com/apache/spark/pull/12851
Remove `SparkSession.withHiveSupport` in PySpark and instead use `SparkSession.builder. enableHiveSupport`
## How was this patch tested?
Existing tests.
Author: Sandeep Singh <sandeep@techaddict.me>
Closes#13063 from techaddict/SPARK-15072-followup.
## What changes were proposed in this pull request?
When a CSV begins with:
- `,,`
OR
- `"","",`
meaning that the first column names are either empty or blank strings and `header` is specified to be `true`, then the column name is replaced with `C` + the index number of that given column. For example, if you were to read in the CSV:
```
"","second column"
"hello", "there"
```
Then column names would become `"C0", "second column"`.
This behavior aligns with what currently happens when `header` is specified to be `false` in recent versions of Spark.
### Current Behavior in Spark <=1.6
In Spark <=1.6, a CSV with a blank column name becomes a blank string, `""`, meaning that this column cannot be accessed. However the CSV reads in without issue.
### Current Behavior in Spark 2.0
Spark throws a NullPointerError and will not read in the file.
#### Reproduction in 2.0
https://databricks-prod-cloudfront.cloud.databricks.com/public/4027ec902e239c93eaaa8714f173bcfc/346304/2828750690305044/484361/latest.html
## How was this patch tested?
A new test was added to `CSVSuite` to account for this issue. We then have asserts that test for being able to select both the empty column names as well as the regular column names.
Author: Bill Chambers <bill@databricks.com>
Author: Bill Chambers <wchambers@ischool.berkeley.edu>
Closes#13041 from anabranch/master.
This PR:
* Corrects the documentation for the `properties` parameter, which is supposed to be a dictionary and not a list.
* Generally clarifies the Python docstring for DataFrameReader.jdbc() by pulling from the [Scala docstrings](b281377647/sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala (L201-L251)) and rephrasing things.
* Corrects minor Sphinx typos.
Author: Nicholas Chammas <nicholas.chammas@gmail.com>
Closes#13034 from nchammas/SPARK-15256.
## What changes were proposed in this pull request?
Earlier we removed experimental tag for Scala/Java DataFrames, but haven't done so for Python. This patch removes the experimental flag for Python and declares them stable.
## How was this patch tested?
N/A.
Author: Reynold Xin <rxin@databricks.com>
Closes#13062 from rxin/SPARK-15278.
## What changes were proposed in this pull request?
Before:
Creating a hiveContext was failing
```python
from pyspark.sql import HiveContext
hc = HiveContext(sc)
```
with
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "spark-2.0/python/pyspark/sql/context.py", line 458, in __init__
sparkSession = SparkSession.withHiveSupport(sparkContext)
File "spark-2.0/python/pyspark/sql/session.py", line 192, in withHiveSupport
jsparkSession = sparkContext._jvm.SparkSession.withHiveSupport(sparkContext._jsc.sc())
File "spark-2.0/python/lib/py4j-0.9.2-src.zip/py4j/java_gateway.py", line 1048, in __getattr__
py4j.protocol.Py4JError: org.apache.spark.sql.SparkSession.withHiveSupport does not exist in the JVM
```
Now:
```python
>>> from pyspark.sql import HiveContext
>>> hc = HiveContext(sc)
>>> hc.range(0, 100)
DataFrame[id: bigint]
>>> hc.range(0, 100).count()
100
```
## How was this patch tested?
Existing Tests, tested manually in python shell
Author: Sandeep Singh <sandeep@techaddict.me>
Closes#13056 from techaddict/SPARK-15270.
## What changes were proposed in this pull request?
Use SparkSession instead of SQLContext in Python TestSuites
## How was this patch tested?
Existing tests
Author: Sandeep Singh <sandeep@techaddict.me>
Closes#13044 from techaddict/SPARK-15037-python.
## What changes were proposed in this pull request?
This PR removes the old `json(path: String)` API which is covered by the new `json(paths: String*)`.
## How was this patch tested?
Jenkins tests (existing tests should cover this)
Author: hyukjinkwon <gurwls223@gmail.com>
Author: Hyukjin Kwon <gurwls223@gmail.com>
Closes#13040 from HyukjinKwon/SPARK-15250.
## What changes were proposed in this pull request?
This patch removes experimental tag from DataFrameReader and DataFrameWriter, and explicitly tags a few methods added for structured streaming as experimental.
## How was this patch tested?
N/A
Author: Reynold Xin <rxin@databricks.com>
Closes#13038 from rxin/SPARK-15261.
Since we cannot really trust if the underlying external catalog can throw exceptions when there is an invalid metadata operation, let's do it in SessionCatalog.
- [X] The first step is to unify the error messages issued in Hive-specific Session Catalog and general Session Catalog.
- [X] The second step is to verify the inputs of metadata operations for partitioning-related operations. This is moved to a separate PR: https://github.com/apache/spark/pull/12801
- [X] The third step is to add database existence verification in `SessionCatalog`
- [X] The fourth step is to add table existence verification in `SessionCatalog`
- [X] The fifth step is to add function existence verification in `SessionCatalog`
Add test cases and verify the error messages we issued
Author: gatorsmile <gatorsmile@gmail.com>
Author: xiaoli <lixiao1983@gmail.com>
Author: Xiao Li <xiaoli@Xiaos-MacBook-Pro.local>
Closes#12385 from gatorsmile/verifySessionAPIs.
## What changes were proposed in this pull request?
See title.
## How was this patch tested?
PySpark tests.
Author: Andrew Or <andrew@databricks.com>
Closes#12917 from andrewor14/deprecate-hive-context-python.
## What changes were proposed in this pull request?
Currently we return RuntimeConfig itself to facilitate chaining. However, it makes the output in interactive environments (e.g. notebooks, scala repl) weird because it'd show the response of calling set as a RuntimeConfig itself.
## How was this patch tested?
Updated unit tests.
Author: Reynold Xin <rxin@databricks.com>
Closes#12902 from rxin/SPARK-15126.
## What changes were proposed in this pull request?
This is a python port of corresponding Scala builder pattern code. `sql.py` is modified as a target example case.
## How was this patch tested?
Manual.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#12860 from dongjoon-hyun/SPARK-15084.
# What changes were proposed in this pull request?
Support partitioning in the file stream sink. This is implemented using a new, but simpler code path for writing parquet files - both unpartitioned and partitioned. This new code path does not use Output Committers, as we will eventually write the file names to the metadata log for "committing" them.
This patch duplicates < 100 LOC from the WriterContainer. But its far simpler that WriterContainer as it does not involve output committing. In addition, it introduces the new APIs in FileFormat and OutputWriterFactory in an attempt to simplify the APIs (not have Job in the `FileFormat` API, not have bucket and other stuff in the `OutputWriterFactory.newInstance()` ).
# Tests
- New unit tests to test the FileStreamSinkWriter for partitioned and unpartitioned files
- New unit test to partially test the FileStreamSink for partitioned files (does not test recovery of partition column data, as that requires change in the StreamFileCatalog, future PR).
- Updated FileStressSuite to test number of records read from partitioned output files.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#12409 from tdas/streaming-partitioned-parquet.
## What changes were proposed in this pull request?
https://issues.apache.org/jira/browse/SPARK-15050
This PR adds function parameters for Python API for reading and writing `csv()`.
## How was this patch tested?
This was tested by `./dev/run_tests`.
Author: hyukjinkwon <gurwls223@gmail.com>
Author: Hyukjin Kwon <gurwls223@gmail.com>
Closes#12834 from HyukjinKwon/SPARK-15050.
## What changes were proposed in this pull request?
This PR adds the explanation and documentation for CSV options for reading and writing.
## How was this patch tested?
Style tests with `./dev/run_tests` for documentation style.
Author: hyukjinkwon <gurwls223@gmail.com>
Author: Hyukjin Kwon <gurwls223@gmail.com>
Closes#12817 from HyukjinKwon/SPARK-13425.
## What changes were proposed in this pull request?
1. Remove all the `spark.setConf` etc. Just expose `spark.conf`
2. Make `spark.conf` take in things set in the core `SparkConf` as well, otherwise users may get confused
This was done for both the Python and Scala APIs.
## How was this patch tested?
`SQLConfSuite`, python tests.
This one fixes the failed tests in #12787Closes#12787
Author: Andrew Or <andrew@databricks.com>
Author: Yin Huai <yhuai@databricks.com>
Closes#12798 from yhuai/conf-api.
## What changes were proposed in this pull request?
Addresses comments in #12765.
## How was this patch tested?
Python tests.
Author: Andrew Or <andrew@databricks.com>
Closes#12784 from andrewor14/python-followup.
## What changes were proposed in this pull request?
The `catalog` and `conf` APIs were exposed in `SparkSession` in #12713 and #12669. This patch adds those to the python API.
## How was this patch tested?
Python tests.
Author: Andrew Or <andrew@databricks.com>
Closes#12765 from andrewor14/python-spark-session-more.
## What changes were proposed in this pull request?
This PR adds Python APIs for:
- `ContinuousQueryManager`
- `ContinuousQueryException`
The `ContinuousQueryException` is a very basic wrapper, it doesn't provide the functionality that the Scala side provides, but it follows the same pattern for `AnalysisException`.
For `ContinuousQueryManager`, all APIs are provided except for registering listeners.
This PR also attempts to fix test flakiness by stopping all active streams just before tests.
## How was this patch tested?
Python Doc tests and unit tests
Author: Burak Yavuz <brkyvz@gmail.com>
Closes#12673 from brkyvz/pyspark-cqm.
## What changes were proposed in this pull request?
```
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/__ / .__/\_,_/_/ /_/\_\ version 2.0.0-SNAPSHOT
/_/
Using Python version 2.7.5 (default, Mar 9 2014 22:15:05)
SparkSession available as 'spark'.
>>> spark
<pyspark.sql.session.SparkSession object at 0x101f3bfd0>
>>> spark.sql("SHOW TABLES").show()
...
+---------+-----------+
|tableName|isTemporary|
+---------+-----------+
| src| false|
+---------+-----------+
>>> spark.range(1, 10, 2).show()
+---+
| id|
+---+
| 1|
| 3|
| 5|
| 7|
| 9|
+---+
```
**Note**: This API is NOT complete in its current state. In particular, for now I left out the `conf` and `catalog` APIs, which were added later in Scala. These will be added later before 2.0.
## How was this patch tested?
Python tests.
Author: Andrew Or <andrew@databricks.com>
Closes#12746 from andrewor14/python-spark-session.
## What changes were proposed in this pull request?
This removes the class `HiveContext` itself along with all code usages associated with it. The bulk of the work was already done in #12485. This is mainly just code cleanup and actually removing the class.
Note: A couple of things will break after this patch. These will be fixed separately.
- the python HiveContext
- all the documentation / comments referencing HiveContext
- there will be no more HiveContext in the REPL (fixed by #12589)
## How was this patch tested?
No change in functionality.
Author: Andrew Or <andrew@databricks.com>
Closes#12585 from andrewor14/delete-hive-context.
## What changes were proposed in this pull request?
In Python, sqlContext.getConf didn't allow getting the system default (getConf with one parameter).
Now the following are supported:
```
sqlContext.getConf(confName) # System default if not locally set, this is new
sqlContext.getConf(confName, myDefault) # myDefault if not locally set, old behavior
```
I also added doctests to this function. The original behavior does not change.
## How was this patch tested?
Manually, but doctests were added.
Author: mathieu longtin <mathieu.longtin@nuance.com>
Closes#12488 from mathieulongtin/pyfixgetconf3.
## What changes were proposed in this pull request?
In Python, the `option` and `options` method of `DataFrameReader` and `DataFrameWriter` were sending the string "None" instead of `null` when passed `None`, therefore making it impossible to send an actual `null`. This fixes that problem.
This is based on #11305 from mathieulongtin.
## How was this patch tested?
Added test to readwriter.py.
Author: Liang-Chi Hsieh <simonh@tw.ibm.com>
Author: mathieu longtin <mathieu.longtin@nuance.com>
Closes#12494 from viirya/py-df-none-option.
## What changes were proposed in this pull request?
Expand the possible ways to interact with the contents of a `pyspark.sql.types.StructType` instance.
- Iterating a `StructType` will iterate its fields
- `[field.name for field in my_structtype]`
- Indexing with a string will return a field by name
- `my_structtype['my_field_name']`
- Indexing with an integer will return a field by position
- `my_structtype[0]`
- Indexing with a slice will return a new `StructType` with just the chosen fields:
- `my_structtype[1:3]`
- The length is the number of fields (should also provide "truthiness" for free)
- `len(my_structtype) == 2`
## How was this patch tested?
Extended the unit test coverage in the accompanying `tests.py`.
Author: Sheamus K. Parkes <shea.parkes@milliman.com>
Closes#12251 from skparkes/pyspark-structtype-enhance.
## What changes were proposed in this pull request?
This patch provides a first cut of python APIs for structured streaming. This PR provides the new classes:
- ContinuousQuery
- Trigger
- ProcessingTime
in pyspark under `pyspark.sql.streaming`.
In addition, it contains the new methods added under:
- `DataFrameWriter`
a) `startStream`
b) `trigger`
c) `queryName`
- `DataFrameReader`
a) `stream`
- `DataFrame`
a) `isStreaming`
This PR doesn't contain all methods exposed for `ContinuousQuery`, for example:
- `exception`
- `sourceStatuses`
- `sinkStatus`
They may be added in a follow up.
This PR also contains some very minor doc fixes in the Scala side.
## How was this patch tested?
Python doc tests
TODO:
- [ ] verify Python docs look good
Author: Burak Yavuz <brkyvz@gmail.com>
Author: Burak Yavuz <burak@databricks.com>
Closes#12320 from brkyvz/stream-python.
