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* [SPARK-17699] Support for parsing JSON string columnsMichael Armbrust2016-09-291-0/+23
| | | | | | | | | | | | | | | | | | Spark SQL has great support for reading text files that contain JSON data. However, in many cases the JSON data is just one column amongst others. This is particularly true when reading from sources such as Kafka. This PR adds a new functions `from_json` that converts a string column into a nested `StructType` with a user specified schema. Example usage: ```scala val df = Seq("""{"a": 1}""").toDS() val schema = new StructType().add("a", IntegerType) df.select(from_json($"value", schema) as 'json) // => [json: <a: int>] ``` This PR adds support for java, scala and python. I leveraged our existing JSON parsing support by moving it into catalyst (so that we could define expressions using it). I left SQL out for now, because I'm not sure how users would specify a schema. Author: Michael Armbrust <michael@databricks.com> Closes #15274 from marmbrus/jsonParser.
* [SPARK-17215][SQL] Method `SQLContext.parseDataType(dataTypeString: String)` ↵jiangxingbo2016-08-241-3/+3
| | | | | | | | | | | | | | | | | could be removed. ## What changes were proposed in this pull request? Method `SQLContext.parseDataType(dataTypeString: String)` could be removed, we should use `SparkSession.parseDataType(dataTypeString: String)` instead. This require updating PySpark. ## How was this patch tested? Existing test cases. Author: jiangxingbo <jiangxb1987@gmail.com> Closes #14790 from jiangxb1987/parseDataType.
* [SPARK-16324][SQL] regexp_extract should doc that it returns empty string ↵Sean Owen2016-08-101-1/+5
| | | | | | | | | | | | | | | | when match fails ## What changes were proposed in this pull request? Doc that regexp_extract returns empty string when regex or group does not match ## How was this patch tested? Jenkins test, with a few new test cases Author: Sean Owen <sowen@cloudera.com> Closes #14525 from srowen/SPARK-16324.
* [SPARK-16409][SQL] regexp_extract with optional groups causes NPESean Owen2016-08-071-0/+3
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? regexp_extract actually returns null when it shouldn't when a regex matches but the requested optional group did not. This makes it return an empty string, as apparently designed. ## How was this patch tested? Additional unit test Author: Sean Owen <sowen@cloudera.com> Closes #14504 from srowen/SPARK-16409.
* [SPARK-16772] Correct API doc references to PySpark classes + formatting fixesNicholas Chammas2016-07-281-8/+13
| | | | | | | | | | | | | | | | | | ## What's Been Changed The PR corrects several broken or missing class references in the Python API docs. It also correct formatting problems. For example, you can see [here](http://spark.apache.org/docs/2.0.0/api/python/pyspark.sql.html#pyspark.sql.SQLContext.registerFunction) how Sphinx is not picking up the reference to `DataType`. That's because the reference is relative to the current module, whereas `DataType` is in a different module. You can also see [here](http://spark.apache.org/docs/2.0.0/api/python/pyspark.sql.html#pyspark.sql.SQLContext.createDataFrame) how the formatting for byte, tinyint, and so on is italic instead of monospace. That's because in ReST single backticks just make things italic, unlike in Markdown. ## Testing I tested this PR by [building the Python docs](https://github.com/apache/spark/tree/master/docs#generating-the-documentation-html) and reviewing the results locally in my browser. I confirmed that the broken or missing class references were resolved, and that the formatting was corrected. Author: Nicholas Chammas <nicholas.chammas@gmail.com> Closes #14393 from nchammas/python-docstring-fixes.
* [MINOR][PYSPARK][DOC] Fix wrongly formatted examples in PySpark documentationhyukjinkwon2016-07-061-4/+4
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR fixes wrongly formatted examples in PySpark documentation as below: - **`SparkSession`** - **Before** ![2016-07-06 11 34 41](https://cloud.githubusercontent.com/assets/6477701/16605847/ae939526-436d-11e6-8ab8-6ad578362425.png) - **After** ![2016-07-06 11 33 56](https://cloud.githubusercontent.com/assets/6477701/16605845/ace9ee78-436d-11e6-8923-b76d4fc3e7c3.png) - **`Builder`** - **Before** ![2016-07-06 11 34 44](https://cloud.githubusercontent.com/assets/6477701/16605844/aba60dbc-436d-11e6-990a-c87bc0281c6b.png) - **After** ![2016-07-06 1 26 37](https://cloud.githubusercontent.com/assets/6477701/16607562/586704c0-437d-11e6-9483-e0af93d8f74e.png) This PR also fixes several similar instances across the documentation in `sql` PySpark module. ## How was this patch tested? N/A Author: hyukjinkwon <gurwls223@gmail.com> Closes #14063 from HyukjinKwon/minor-pyspark-builder.
* [SPARK-16289][SQL] Implement posexplode table generating functionDongjoon Hyun2016-06-301-0/+21
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR implements `posexplode` table generating function. Currently, master branch raises the following exception for `map` argument. It's different from Hive. **Before** ```scala scala> sql("select posexplode(map('a', 1, 'b', 2))").show org.apache.spark.sql.AnalysisException: No handler for Hive UDF ... posexplode() takes an array as a parameter; line 1 pos 7 ``` **After** ```scala scala> sql("select posexplode(map('a', 1, 'b', 2))").show +---+---+-----+ |pos|key|value| +---+---+-----+ | 0| a| 1| | 1| b| 2| +---+---+-----+ ``` For `array` argument, `after` is the same with `before`. ``` scala> sql("select posexplode(array(1, 2, 3))").show +---+---+ |pos|col| +---+---+ | 0| 1| | 1| 2| | 2| 3| +---+---+ ``` ## How was this patch tested? Pass the Jenkins tests with newly added testcases. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #13971 from dongjoon-hyun/SPARK-16289.
* [MINOR] Fix Typos 'a -> an'Zheng RuiFeng2016-05-261-1/+1
| | | | | | | | | | | | | | | | | | | ## 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.
* [SPARK-15397][SQL] fix string udf locate as hiveDaoyuan Wang2016-05-231-1/+1
| | | | | | | | | | | | | | ## 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.
* [SPARK-15464][ML][MLLIB][SQL][TESTS] Replace SQLContext and SparkContext ↵WeichenXu2016-05-231-75/+78
| | | | | | | | | | | | | | | | with SparkSession using builder pattern in python test code ## 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.
* [MINOR][SQL][DOCS] Add notes of the deterministic assumption on UDF functionsDongjoon Hyun2016-05-231-0/+3
| | | | | | | | | | | | | | ## 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.
* [SPARK-14639] [PYTHON] [R] Add `bround` function in Python/R.Dongjoon Hyun2016-04-191-3/+16
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This issue aims to expose Scala `bround` function in Python/R API. `bround` function is implemented in SPARK-14614 by extending current `round` function. We used the following semantics from Hive. ```java public static double bround(double input, int scale) { if (Double.isNaN(input) || Double.isInfinite(input)) { return input; } return BigDecimal.valueOf(input).setScale(scale, RoundingMode.HALF_EVEN).doubleValue(); } ``` After this PR, `pyspark` and `sparkR` also support `bround` function. **PySpark** ```python >>> from pyspark.sql.functions import bround >>> sqlContext.createDataFrame([(2.5,)], ['a']).select(bround('a', 0).alias('r')).collect() [Row(r=2.0)] ``` **SparkR** ```r > df = createDataFrame(sqlContext, data.frame(x = c(2.5, 3.5))) > head(collect(select(df, bround(df$x, 0)))) bround(x, 0) 1 2 2 4 ``` ## How was this patch tested? Pass the Jenkins tests (including new testcases). Author: Dongjoon Hyun <dongjoon@apache.org> Closes #12509 from dongjoon-hyun/SPARK-14639.
* [SPARK-14353] Dataset Time Window `window` API for Python, and SQLBurak Yavuz2016-04-051-0/+49
| | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? The `window` function was added to Dataset with [this PR](https://github.com/apache/spark/pull/12008). This PR adds the Python, and SQL, API for this function. With this PR, SQL, Java, and Scala will share the same APIs as in users can use: - `window(timeColumn, windowDuration)` - `window(timeColumn, windowDuration, slideDuration)` - `window(timeColumn, windowDuration, slideDuration, startTime)` In Python, users can access all APIs above, but in addition they can do - In Python: `window(timeColumn, windowDuration, startTime=...)` that is, they can provide the startTime without providing the `slideDuration`. In this case, we will generate tumbling windows. ## How was this patch tested? Unit tests + manual tests Author: Burak Yavuz <brkyvz@gmail.com> Closes #12136 from brkyvz/python-windows.
* [SPARK-14267] [SQL] [PYSPARK] execute multiple Python UDFs within single batchDavies Liu2016-03-311-2/+1
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR support multiple Python UDFs within single batch, also improve the performance. ```python >>> from pyspark.sql.types import IntegerType >>> sqlContext.registerFunction("double", lambda x: x * 2, IntegerType()) >>> sqlContext.registerFunction("add", lambda x, y: x + y, IntegerType()) >>> sqlContext.sql("SELECT double(add(1, 2)), add(double(2), 1)").explain(True) == Parsed Logical Plan == 'Project [unresolvedalias('double('add(1, 2)), None),unresolvedalias('add('double(2), 1), None)] +- OneRowRelation$ == Analyzed Logical Plan == double(add(1, 2)): int, add(double(2), 1): int Project [double(add(1, 2))#14,add(double(2), 1)#15] +- Project [double(add(1, 2))#14,add(double(2), 1)#15] +- Project [pythonUDF0#16 AS double(add(1, 2))#14,pythonUDF0#18 AS add(double(2), 1)#15] +- EvaluatePython [add(pythonUDF1#17, 1)], [pythonUDF0#18] +- EvaluatePython [double(add(1, 2)),double(2)], [pythonUDF0#16,pythonUDF1#17] +- OneRowRelation$ == Optimized Logical Plan == Project [pythonUDF0#16 AS double(add(1, 2))#14,pythonUDF0#18 AS add(double(2), 1)#15] +- EvaluatePython [add(pythonUDF1#17, 1)], [pythonUDF0#18] +- EvaluatePython [double(add(1, 2)),double(2)], [pythonUDF0#16,pythonUDF1#17] +- OneRowRelation$ == Physical Plan == WholeStageCodegen : +- Project [pythonUDF0#16 AS double(add(1, 2))#14,pythonUDF0#18 AS add(double(2), 1)#15] : +- INPUT +- !BatchPythonEvaluation [add(pythonUDF1#17, 1)], [pythonUDF0#16,pythonUDF1#17,pythonUDF0#18] +- !BatchPythonEvaluation [double(add(1, 2)),double(2)], [pythonUDF0#16,pythonUDF1#17] +- Scan OneRowRelation[] ``` ## How was this patch tested? Added new tests. Using the following script to benchmark 1, 2 and 3 udfs, ``` df = sqlContext.range(1, 1 << 23, 1, 4) double = F.udf(lambda x: x * 2, LongType()) print df.select(double(df.id)).count() print df.select(double(df.id), double(df.id + 1)).count() print df.select(double(df.id), double(df.id + 1), double(df.id + 2)).count() ``` Here is the results: N | Before | After | speed up ---- |------------ | -------------|------ 1 | 22 s | 7 s | 3.1X 2 | 38 s | 13 s | 2.9X 3 | 58 s | 16 s | 3.6X This benchmark ran locally with 4 CPUs. For 3 UDFs, it launched 12 Python before before this patch, 4 process after this patch. After this patch, it will use less memory for multiple UDFs than before (less buffering). Author: Davies Liu <davies@databricks.com> Closes #12057 from davies/multi_udfs.
* [SPARK-14215] [SQL] [PYSPARK] Support chained Python UDFsDavies Liu2016-03-291-5/+11
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR brings the support for chained Python UDFs, for example ```sql select udf1(udf2(a)) select udf1(udf2(a) + 3) select udf1(udf2(a) + udf3(b)) ``` Also directly chained unary Python UDFs are put in single batch of Python UDFs, others may require multiple batches. For example, ```python >>> sqlContext.sql("select double(double(1))").explain() == Physical Plan == WholeStageCodegen : +- Project [pythonUDF#10 AS double(double(1))#9] : +- INPUT +- !BatchPythonEvaluation double(double(1)), [pythonUDF#10] +- Scan OneRowRelation[] >>> sqlContext.sql("select double(double(1) + double(2))").explain() == Physical Plan == WholeStageCodegen : +- Project [pythonUDF#19 AS double((double(1) + double(2)))#16] : +- INPUT +- !BatchPythonEvaluation double((pythonUDF#17 + pythonUDF#18)), [pythonUDF#17,pythonUDF#18,pythonUDF#19] +- !BatchPythonEvaluation double(2), [pythonUDF#17,pythonUDF#18] +- !BatchPythonEvaluation double(1), [pythonUDF#17] +- Scan OneRowRelation[] ``` TODO: will support multiple unrelated Python UDFs in one batch (another PR). ## How was this patch tested? Added new unit tests for chained UDFs. Author: Davies Liu <davies@databricks.com> Closes #12014 from davies/py_udfs.
* [SPARK-14061][SQL] implement CreateMapWenchen Fan2016-03-251-0/+20
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? As we have `CreateArray` and `CreateStruct`, we should also have `CreateMap`. This PR adds the `CreateMap` expression, and the DataFrame API, and python API. ## How was this patch tested? various new tests. Author: Wenchen Fan <wenchen@databricks.com> Closes #11879 from cloud-fan/create_map.
* [MINOR] Fix typo in 'hypot' docstringTristan Reid2016-03-091-1/+1
| | | | | | | | | | Minor typo: docstring for pyspark.sql.functions: hypot has extra characters N/A Author: Tristan Reid <treid@netflix.com> Closes #11616 from tristanreid/master.
* [SPARK-12720][SQL] SQL Generation Support for Cube, Rollup, and Grouping Setsgatorsmile2016-03-051-7/+7
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | #### What changes were proposed in this pull request? This PR is for supporting SQL generation for cube, rollup and grouping sets. For example, a query using rollup: ```SQL SELECT count(*) as cnt, key % 5, grouping_id() FROM t1 GROUP BY key % 5 WITH ROLLUP ``` Original logical plan: ``` Aggregate [(key#17L % cast(5 as bigint))#47L,grouping__id#46], [(count(1),mode=Complete,isDistinct=false) AS cnt#43L, (key#17L % cast(5 as bigint))#47L AS _c1#45L, grouping__id#46 AS _c2#44] +- Expand [List(key#17L, value#18, (key#17L % cast(5 as bigint))#47L, 0), List(key#17L, value#18, null, 1)], [key#17L,value#18,(key#17L % cast(5 as bigint))#47L,grouping__id#46] +- Project [key#17L, value#18, (key#17L % cast(5 as bigint)) AS (key#17L % cast(5 as bigint))#47L] +- Subquery t1 +- Relation[key#17L,value#18] ParquetRelation ``` Converted SQL: ```SQL SELECT count( 1) AS `cnt`, (`t1`.`key` % CAST(5 AS BIGINT)), grouping_id() AS `_c2` FROM `default`.`t1` GROUP BY (`t1`.`key` % CAST(5 AS BIGINT)) GROUPING SETS (((`t1`.`key` % CAST(5 AS BIGINT))), ()) ``` #### How was the this patch tested? Added eight test cases in `LogicalPlanToSQLSuite`. Author: gatorsmile <gatorsmile@gmail.com> Author: xiaoli <lixiao1983@gmail.com> Author: Xiao Li <xiaoli@Xiaos-MacBook-Pro.local> Closes #11283 from gatorsmile/groupingSetsToSQL.
* [SPARK-13594][SQL] remove typed operations(e.g. map, flatMap) from python ↵Wenchen Fan2016-03-021-2/+2
| | | | | | | | | | | | | | | | DataFrame ## What changes were proposed in this pull request? Remove `map`, `flatMap`, `mapPartitions` from python DataFrame, to prepare for Dataset API in the future. ## How was this patch tested? existing tests Author: Wenchen Fan <wenchen@databricks.com> Closes #11445 from cloud-fan/python-clean.
* [SPARK-13467] [PYSPARK] abstract python function to simplify pyspark codeWenchen Fan2016-02-241-5/+3
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? When we pass a Python function to JVM side, we also need to send its context, e.g. `envVars`, `pythonIncludes`, `pythonExec`, etc. However, it's annoying to pass around so many parameters at many places. This PR abstract python function along with its context, to simplify some pyspark code and make the logic more clear. ## How was the this patch tested? by existing unit tests. Author: Wenchen Fan <wenchen@databricks.com> Closes #11342 from cloud-fan/python-clean.
* [MINOR][DOCS] Fix all typos in markdown files of `doc` and similar patterns ↵Dongjoon Hyun2016-02-221-3/+3
| | | | | | | | | | | | | | | | | in other comments ## What changes were proposed in this pull request? This PR tries to fix all typos in all markdown files under `docs` module, and fixes similar typos in other comments, too. ## How was the this patch tested? manual tests. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #11300 from dongjoon-hyun/minor_fix_typos.
* [SPARK-12799] Simplify various string output for expressionsCheng Lian2016-02-211-15/+15
| | | | | | | | | | | | | | | | | | | | | | | | | This PR introduces several major changes: 1. Replacing `Expression.prettyString` with `Expression.sql` The `prettyString` method is mostly an internal, developer faced facility for debugging purposes, and shouldn't be exposed to users. 1. Using SQL-like representation as column names for selected fields that are not named expression (back-ticks and double quotes should be removed) Before, we were using `prettyString` as column names when possible, and sometimes the result column names can be weird. Here are several examples: Expression | `prettyString` | `sql` | Note ------------------ | -------------- | ---------- | --------------- `a && b` | `a && b` | `a AND b` | `a.getField("f")` | `a[f]` | `a.f` | `a` is a struct 1. Adding trait `NonSQLExpression` extending from `Expression` for expressions that don't have a SQL representation (e.g. Scala UDF/UDAF and Java/Scala object expressions used for encoders) `NonSQLExpression.sql` may return an arbitrary user facing string representation of the expression. Author: Cheng Lian <lian@databricks.com> Closes #10757 from liancheng/spark-12799.simplify-expression-string-methods.
* Revert "[SPARK-12567] [SQL] Add aes_{encrypt,decrypt} UDFs"Reynold Xin2016-02-191-37/+0
| | | | This reverts commit 4f9a66481849dc867cf6592d53e0e9782361d20a.
* [SPARK-12567] [SQL] Add aes_{encrypt,decrypt} UDFsKai Jiang2016-02-191-0/+37
| | | | | | Author: Kai Jiang <jiangkai@gmail.com> Closes #10527 from vectorijk/spark-12567.
* [SPARK-13296][SQL] Move UserDefinedFunction into sql.expressions.Reynold Xin2016-02-131-3/+3
| | | | | | | | | | | | | | | | This pull request has the following changes: 1. Moved UserDefinedFunction into expressions package. This is more consistent with how we structure the packages for window functions and UDAFs. 2. Moved UserDefinedPythonFunction into execution.python package, so we don't have a random private class in the top level sql package. 3. Move everything in execution/python.scala into the newly created execution.python package. Most of the diffs are just straight copy-paste. Author: Reynold Xin <rxin@databricks.com> Closes #11181 from rxin/SPARK-13296.
* [SPARK-12962] [SQL] [PySpark] PySpark support covar_samp and covar_popYanbo Liang2016-02-121-6/+35
| | | | | | | | | | PySpark support ```covar_samp``` and ```covar_pop```. cc rxin davies marmbrus Author: Yanbo Liang <ybliang8@gmail.com> Closes #10876 from yanboliang/spark-12962.
* [SPARK-12706] [SQL] grouping() and grouping_id()Davies Liu2016-02-101-0/+44
| | | | | | | | | | | | Grouping() returns a column is aggregated or not, grouping_id() returns the aggregation levels. grouping()/grouping_id() could be used with window function, but does not work in having/sort clause, will be fixed by another PR. The GROUPING__ID/grouping_id() in Hive is wrong (according to docs), we also did it wrongly, this PR change that to match the behavior in most databases (also the docs of Hive). Author: Davies Liu <davies@databricks.com> Closes #10677 from davies/grouping.
* [SPARK-13049] Add First/last with ignore nulls to functions.scalaHerman van Hovell2016-01-311-2/+24
| | | | | | | | | | | | | This PR adds the ability to specify the ```ignoreNulls``` option to the functions dsl, e.g: ```df.select($"id", last($"value", ignoreNulls = true).over(Window.partitionBy($"id").orderBy($"other"))``` This PR is some where between a bug fix (see the JIRA) and a new feature. I am not sure if we should backport to 1.6. cc yhuai Author: Herman van Hovell <hvanhovell@questtec.nl> Closes #10957 from hvanhovell/SPARK-13049.
* [SPARK-12642][SQL] improve the hash expression to be decoupled from unsafe rowWenchen Fan2016-01-131-1/+1
| | | | | | | | https://issues.apache.org/jira/browse/SPARK-12642 Author: Wenchen Fan <wenchen@databricks.com> Closes #10694 from cloud-fan/hash-expr.
* [SPARK-12480][FOLLOW-UP] use a single column vararg for hashWenchen Fan2016-01-051-0/+12
| | | | | | | | | | address comments in #10435 This makes the API easier to use if user programmatically generate the call to hash, and they will get analysis exception if the arguments of hash is empty. Author: Wenchen Fan <wenchen@databricks.com> Closes #10588 from cloud-fan/hash.
* [SPARK-12600][SQL] Remove deprecated methods in Spark SQLReynold Xin2016-01-041-24/+0
| | | | | | Author: Reynold Xin <rxin@databricks.com> Closes #10559 from rxin/remove-deprecated-sql.
* Doc typo: ltrim = trim from left end, not rightpshearer2015-12-211-1/+1
| | | | | | Author: pshearer <pshearer@massmutual.com> Closes #10414 from pshearer/patch-1.
* [SPARK-11980][SPARK-10621][SQL] Fix json_tuple and add test cases forgatorsmile2015-11-251-10/+34
| | | | | | | | | | | | | | Added Python test cases for the function `isnan`, `isnull`, `nanvl` and `json_tuple`. Fixed a bug in the function `json_tuple` rxin , could you help me review my changes? Please let me know anything is missing. Thank you! Have a good Thanksgiving day! Author: gatorsmile <gatorsmile@gmail.com> Closes #9977 from gatorsmile/json_tuple.
* [SPARK-10621][SQL] Consistent naming for functions in SQL, Python, ScalaReynold Xin2015-11-241-17/+94
| | | | | | Author: Reynold Xin <rxin@databricks.com> Closes #9948 from rxin/SPARK-10621.
* [SPARK-11836][SQL] udf/cast should not create new SQLContextDavies Liu2015-11-231-3/+4
| | | | | | | | They should use the existing SQLContext. Author: Davies Liu <davies@databricks.com> Closes #9914 from davies/create_udf.
* [SPARK-11567] [PYTHON] Add Python API for corr Aggregate functionfelixcheung2015-11-101-0/+16
| | | | | | | | | | like `df.agg(corr("col1", "col2")` davies Author: felixcheung <felixcheung_m@hotmail.com> Closes #9536 from felixcheung/pyfunc.
* [SPARK-9830][SQL] Remove AggregateExpression1 and Aggregate Operator used to ↵Yin Huai2015-11-101-1/+1
| | | | | | | | | | | | | | | | | | | evaluate AggregateExpression1s https://issues.apache.org/jira/browse/SPARK-9830 This PR contains the following main changes. * Removing `AggregateExpression1`. * Removing `Aggregate` operator, which is used to evaluate `AggregateExpression1`. * Removing planner rule used to plan `Aggregate`. * Linking `MultipleDistinctRewriter` to analyzer. * Renaming `AggregateExpression2` to `AggregateExpression` and `AggregateFunction2` to `AggregateFunction`. * Updating places where we create aggregate expression. The way to create aggregate expressions is `AggregateExpression(aggregateFunction, mode, isDistinct)`. * Changing `val`s in `DeclarativeAggregate`s that touch children of this function to `lazy val`s (when we create aggregate expression in DataFrame API, children of an aggregate function can be unresolved). Author: Yin Huai <yhuai@databricks.com> Closes #9556 from yhuai/removeAgg1.
* [SPARK-9301][SQL] Add collect_set and collect_list aggregate functionsNick Buroojy2015-11-091-11/+14
| | | | | | | | | | | | | | | | | | | | | For now they are thin wrappers around the corresponding Hive UDAFs. One limitation with these in Hive 0.13.0 is they only support aggregating primitive types. I chose snake_case here instead of camelCase because it seems to be used in the majority of the multi-word fns. Do we also want to add these to `functions.py`? This approach was recommended here: https://github.com/apache/spark/pull/8592#issuecomment-154247089 marmbrus rxin Author: Nick Buroojy <nick.buroojy@civitaslearning.com> Closes #9526 from nburoojy/nick/udaf-alias. (cherry picked from commit a6ee4f989d020420dd08b97abb24802200ff23b2) Signed-off-by: Michael Armbrust <michael@databricks.com>
* [SPARK-11467][SQL] add Python API for stddev/varianceDavies Liu2015-11-031-0/+17
| | | | | | | | Add Python API for stddev/stddev_pop/stddev_samp/variance/var_pop/var_samp/skewness/kurtosis Author: Davies Liu <davies@databricks.com> Closes #9424 from davies/py_var.
* [SPARK-10577] [PYSPARK] DataFrame hint for broadcast joinJian Feng2015-09-211-0/+9
| | | | | | | | https://issues.apache.org/jira/browse/SPARK-10577 Author: Jian Feng <jzhang.chs@gmail.com> Closes #8801 from Jianfeng-chs/master.
* [SPARK-10373] [PYSPARK] move @since into pyspark from sqlDavies Liu2015-09-081-2/+1
| | | | | | | | cc mengxr Author: Davies Liu <davies@databricks.com> Closes #8657 from davies/move_since.
* [DOCS] [SQL] [PYSPARK] Fix typo in ntile functionMoussa Taifi2015-08-191-1/+1
| | | | | | | | Fix typo in ntile function. Author: Moussa Taifi <moutai10@gmail.com> Closes #8261 from moutai/patch-2.
* [SPARK-9978] [PYSPARK] [SQL] fix Window.orderBy and doc of ntile()Davies Liu2015-08-141-3/+4
| | | | | | Author: Davies Liu <davies@databricks.com> Closes #8213 from davies/fix_window.
* [SPARK-9907] [SQL] Python crc32 is mistakenly calling md5Reynold Xin2015-08-121-2/+2
| | | | | | Author: Reynold Xin <rxin@databricks.com> Closes #8138 from rxin/SPARK-9907.
* [SPARK-9691] [SQL] PySpark SQL rand function treats seed 0 as no seedYin Huai2015-08-061-2/+2
| | | | | | | | | | | | | https://issues.apache.org/jira/browse/SPARK-9691 jkbradley rxin Author: Yin Huai <yhuai@databricks.com> Closes #7999 from yhuai/pythonRand and squashes the following commits: 4187e0c [Yin Huai] Regression test. a985ef9 [Yin Huai] Use "if seed is not None" instead "if seed" because "if seed" returns false when seed is 0.
* [SPARK-8266] [SQL] add function translatezhichao.li2015-08-061-0/+16
| | | | | | | | | | | | | | | | | ![translate](http://www.w3resource.com/PostgreSQL/postgresql-translate-function.png) Author: zhichao.li <zhichao.li@intel.com> Closes #7709 from zhichao-li/translate and squashes the following commits: 9418088 [zhichao.li] refine checking condition f2ab77a [zhichao.li] clone string 9d88f2d [zhichao.li] fix indent 6aa2962 [zhichao.li] style e575ead [zhichao.li] add python api 9d4bab0 [zhichao.li] add special case for fodable and refactor unittest eda7ad6 [zhichao.li] update to use TernaryExpression cdfd4be [zhichao.li] add function translate
* [SPARK-8231] [SQL] Add array_containsPedro Rodriguez2015-08-041-0/+17
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR is based on #7580 , thanks to EntilZha PR for work on https://issues.apache.org/jira/browse/SPARK-8231 Currently, I have an initial implementation for contains. Based on discussion on JIRA, it should behave same as Hive: https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDFArrayContains.java#L102-L128 Main points are: 1. If the array is empty, null, or the value is null, return false 2. If there is a type mismatch, throw error 3. If comparison is not supported, throw error Closes #7580 Author: Pedro Rodriguez <prodriguez@trulia.com> Author: Pedro Rodriguez <ski.rodriguez@gmail.com> Author: Davies Liu <davies@databricks.com> Closes #7949 from davies/array_contains and squashes the following commits: d3c08bc [Davies Liu] use foreach() to avoid copy bc3d1fe [Davies Liu] fix array_contains 719e37d [Davies Liu] Merge branch 'master' of github.com:apache/spark into array_contains e352cf9 [Pedro Rodriguez] fixed diff from master 4d5b0ff [Pedro Rodriguez] added docs and another type check ffc0591 [Pedro Rodriguez] fixed unit test 7a22deb [Pedro Rodriguez] Changed test to use strings instead of long/ints which are different between python 2 an 3 b5ffae8 [Pedro Rodriguez] fixed pyspark test 4e7dce3 [Pedro Rodriguez] added more docs 3082399 [Pedro Rodriguez] fixed unit test 46f9789 [Pedro Rodriguez] reverted change d3ca013 [Pedro Rodriguez] Fixed type checking to match hive behavior, then added tests to insure this 8528027 [Pedro Rodriguez] added more tests 686e029 [Pedro Rodriguez] fix scala style d262e9d [Pedro Rodriguez] reworked type checking code and added more tests 2517a58 [Pedro Rodriguez] removed unused import 28b4f71 [Pedro Rodriguez] fixed bug with type conversions and re-added tests 12f8795 [Pedro Rodriguez] fix scala style checks e8a20a9 [Pedro Rodriguez] added python df (broken atm) 65b562c [Pedro Rodriguez] made array_contains nullable false 33b45aa [Pedro Rodriguez] reordered test 9623c64 [Pedro Rodriguez] fixed test 4b4425b [Pedro Rodriguez] changed Arrays in tests to Seqs 72cb4b1 [Pedro Rodriguez] added checkInputTypes and docs 69c46fb [Pedro Rodriguez] added tests and codegen 9e0bfc4 [Pedro Rodriguez] initial attempt at implementation
* [SPARK-9513] [SQL] [PySpark] Add python API for DataFrame functionsDavies Liu2015-08-041-247/+602
| | | | | | | | | | | | | | | | | This adds Python API for those DataFrame functions that is introduced in 1.5. There is issue with serialize byte_array in Python 3, so some of functions (for BinaryType) does not have tests. cc rxin Author: Davies Liu <davies@databricks.com> Closes #7922 from davies/python_functions and squashes the following commits: 8ad942f [Davies Liu] fix test 5fb6ec3 [Davies Liu] fix bugs 3495ed3 [Davies Liu] fix issues ea5f7bb [Davies Liu] Add python API for DataFrame functions
* [SPARK-8269] [SQL] string function: initcapHuJiayin2015-08-011-0/+12
| | | | | | | | | | | | | | | | | | | | | | | | This PR is based on #7208 , thanks to HuJiayin Closes #7208 Author: HuJiayin <jiayin.hu@intel.com> Author: Davies Liu <davies@databricks.com> Closes #7850 from davies/initcap and squashes the following commits: 54472e9 [Davies Liu] fix python test 17ffe51 [Davies Liu] Merge branch 'master' of github.com:apache/spark into initcap ca46390 [Davies Liu] Merge branch 'master' of github.com:apache/spark into initcap 3a906e4 [Davies Liu] implement title case in UTF8String 8b2506a [HuJiayin] Update functions.py 2cd43e5 [HuJiayin] fix python style check b616c0e [HuJiayin] add python api 1f5a0ef [HuJiayin] add codegen 7e0c604 [HuJiayin] Merge branch 'master' of https://github.com/apache/spark into initcap 6a0b958 [HuJiayin] add column c79482d [HuJiayin] support soundex 7ce416b [HuJiayin] support initcap rebase code
* [SPARK-8263] [SQL] substr/substring should also support binary typezhichao.li2015-08-011-1/+17
| | | | | | | | | | | | | | | | | This is based on #7641, thanks to zhichao-li Closes #7641 Author: zhichao.li <zhichao.li@intel.com> Author: Davies Liu <davies@databricks.com> Closes #7848 from davies/substr and squashes the following commits: 461b709 [Davies Liu] remove bytearry from tests b45377a [Davies Liu] Merge branch 'master' of github.com:apache/spark into substr 01d795e [zhichao.li] scala style 99aa130 [zhichao.li] add substring to dataframe 4f68bfe [zhichao.li] add binary type support for substring
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