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* [MINOR][R] Reorder `Collate` fields in DESCRIPTION filehyukjinkwon2017-04-041-1/+1
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? It seems cran check scripts corrects `R/pkg/DESCRIPTION` and follows the order in `Collate` fields. This PR proposes to fix `catalog.R`'s order so that running this script does not show up a small diff in this file every time. ## How was this patch tested? Manually via `./R/check-cran.sh`. Author: hyukjinkwon <gurwls223@gmail.com> Closes #17528 from HyukjinKwon/minor-reorder-description.
* [SPARK-19825][R][ML] spark.ml R API for FPGrowthzero3232017-04-036-1/+260
| | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Adds SparkR API for FPGrowth: [SPARK-19825](https://issues.apache.org/jira/browse/SPARK-19825): - `spark.fpGrowth` -model training. - `freqItemsets` and `associationRules` methods with new corresponding generics. - Scala helper: `org.apache.spark.ml.r. FPGrowthWrapper` - unit tests. ## How was this patch tested? Feature specific unit tests. Author: zero323 <zero323@users.noreply.github.com> Closes #17170 from zero323/SPARK-19825.
* [SPARK-20159][SPARKR][SQL] Support all catalog API in RFelix Cheung2017-04-026-237/+569
| | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Add a set of catalog API in R ``` "currentDatabase", "listColumns", "listDatabases", "listFunctions", "listTables", "recoverPartitions", "refreshByPath", "refreshTable", "setCurrentDatabase", ``` https://github.com/apache/spark/pull/17483/files#diff-6929e6c5e59017ff954e110df20ed7ff ## How was this patch tested? manual tests, unit tests Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #17483 from felixcheung/rcatalog.
* [SPARK-20123][BUILD] SPARK_HOME variable might have spaces in it(e.g. $SPARK…zuotingbing2017-04-025-36/+36
| | | | | | | | | | | | | | | | JIRA Issue: https://issues.apache.org/jira/browse/SPARK-20123 ## What changes were proposed in this pull request? If $SPARK_HOME or $FWDIR variable contains spaces, then use "./dev/make-distribution.sh --name custom-spark --tgz -Psparkr -Phadoop-2.7 -Phive -Phive-thriftserver -Pmesos -Pyarn" build spark will failed. ## How was this patch tested? manual tests Author: zuotingbing <zuo.tingbing9@zte.com.cn> Closes #17452 from zuotingbing/spark-bulid.
* [SPARK-20105][TESTS][R] Add tests for checkType and type string in ↵hyukjinkwon2017-03-271-0/+53
| | | | | | | | | | | | | | | | | | structField in R ## What changes were proposed in this pull request? It seems `checkType` and the type string in `structField` are not being tested closely. This string format currently seems SparkR-specific (see https://github.com/apache/spark/blob/d1f6c64c4b763c05d6d79ae5497f298dc3835f3e/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala#L93-L131) but resembles SQL type definition. Therefore, it seems nicer if we test positive/negative cases in R side. ## How was this patch tested? Unit tests in `test_sparkSQL.R`. Author: hyukjinkwon <gurwls223@gmail.com> Closes #17439 from HyukjinKwon/r-typestring-tests.
* [MINOR][DOCS] Match several documentation changes in Scala to R/Pythonhyukjinkwon2017-03-261-3/+3
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR proposes to match minor documentations changes in https://github.com/apache/spark/pull/17399 and https://github.com/apache/spark/pull/17380 to R/Python. ## How was this patch tested? Manual tests in Python , Python tests via `./python/run-tests.py --module=pyspark-sql` and lint-checks for Python/R. Author: hyukjinkwon <gurwls223@gmail.com> Closes #17429 from HyukjinKwon/minor-match-doc.
* [SPARK-19925][SPARKR] Fix SparkR spark.getSparkFiles fails when it was ↵Yanbo Liang2017-03-212-2/+21
| | | | | | | | | | | | | | called on executors. ## What changes were proposed in this pull request? SparkR ```spark.getSparkFiles``` fails when it was called on executors, see details at [SPARK-19925](https://issues.apache.org/jira/browse/SPARK-19925). ## How was this patch tested? Add unit tests, and verify this fix at standalone and yarn cluster. Author: Yanbo Liang <ybliang8@gmail.com> Closes #17274 from yanboliang/spark-19925.
* [SPARK-19237][SPARKR][CORE] On Windows spark-submit should handle when java ↵Felix Cheung2017-03-211-0/+1
| | | | | | | | | | | | | | | | | | | is not installed ## What changes were proposed in this pull request? When SparkR is installed as a R package there might not be any java runtime. If it is not there SparkR's `sparkR.session()` will block waiting for the connection timeout, hanging the R IDE/shell, without any notification or message. ## How was this patch tested? manually - [x] need to test on Windows Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #16596 from felixcheung/rcheckjava.
* [SPARK-20041][DOC] Update docs for NaN handling in approxQuantileZheng RuiFeng2017-03-211-1/+2
| | | | | | | | | | | | ## What changes were proposed in this pull request? Update docs for NaN handling in approxQuantile. ## How was this patch tested? existing tests. Author: Zheng RuiFeng <ruifengz@foxmail.com> Closes #17369 from zhengruifeng/doc_quantiles_nan.
* [SPARK-19949][SQL] unify bad record handling in CSV and JSONWenchen Fan2017-03-201-3/+2
| | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Currently JSON and CSV have exactly the same logic about handling bad records, this PR tries to abstract it and put it in a upper level to reduce code duplication. The overall idea is, we make the JSON and CSV parser to throw a BadRecordException, then the upper level, FailureSafeParser, handles bad records according to the parse mode. Behavior changes: 1. with PERMISSIVE mode, if the number of tokens doesn't match the schema, previously CSV parser will treat it as a legal record and parse as many tokens as possible. After this PR, we treat it as an illegal record, and put the raw record string in a special column, but we still parse as many tokens as possible. 2. all logging is removed as they are not very useful in practice. ## How was this patch tested? existing tests Author: Wenchen Fan <wenchen@databricks.com> Author: hyukjinkwon <gurwls223@gmail.com> Author: Wenchen Fan <cloud0fan@gmail.com> Closes #17315 from cloud-fan/bad-record2.
* [SPARK-20020][SPARKR][FOLLOWUP] DataFrame checkpoint API fix version tagFelix Cheung2017-03-191-1/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? doc only change ## How was this patch tested? manual Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #17356 from felixcheung/rdfcheckpoint2.
* [SPARK-20020][SPARKR] DataFrame checkpoint APIFelix Cheung2017-03-197-5/+70
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Add checkpoint, setCheckpointDir API to R ## How was this patch tested? unit tests, manual tests Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #17351 from felixcheung/rdfcheckpoint.
* [SPARK-19849][SQL] Support ArrayType in to_json to produce JSON arrayhyukjinkwon2017-03-192-6/+16
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR proposes to support an array of struct type in `to_json` as below: ```scala import org.apache.spark.sql.functions._ val df = Seq(Tuple1(Tuple1(1) :: Nil)).toDF("a") df.select(to_json($"a").as("json")).show() ``` ``` +----------+ | json| +----------+ |[{"_1":1}]| +----------+ ``` Currently, it throws an exception as below (a newline manually inserted for readability): ``` org.apache.spark.sql.AnalysisException: cannot resolve 'structtojson(`array`)' due to data type mismatch: structtojson requires that the expression is a struct expression.;; ``` This allows the roundtrip with `from_json` as below: ```scala import org.apache.spark.sql.functions._ import org.apache.spark.sql.types._ val schema = ArrayType(StructType(StructField("a", IntegerType) :: Nil)) val df = Seq("""[{"a":1}, {"a":2}]""").toDF("json").select(from_json($"json", schema).as("array")) df.show() // Read back. df.select(to_json($"array").as("json")).show() ``` ``` +----------+ | array| +----------+ |[[1], [2]]| +----------+ +-----------------+ | json| +-----------------+ |[{"a":1},{"a":2}]| +-----------------+ ``` Also, this PR proposes to rename from `StructToJson` to `StructsToJson ` and `JsonToStruct` to `JsonToStructs`. ## How was this patch tested? Unit tests in `JsonFunctionsSuite` and `JsonExpressionsSuite` for Scala, doctest for Python and test in `test_sparkSQL.R` for R. Author: hyukjinkwon <gurwls223@gmail.com> Closes #17192 from HyukjinKwon/SPARK-19849.
* [SPARK-18817][SPARKR][SQL] change derby log output to temp dirFelix Cheung2017-03-193-1/+54
| | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Passes R `tempdir()` (this is the R session temp dir, shared with other temp files/dirs) to JVM, set System.Property for derby home dir to move derby.log ## How was this patch tested? Manually, unit tests With this, these are relocated to under /tmp ``` # ls /tmp/RtmpG2M0cB/ derby.log ``` And they are removed automatically when the R session is ended. Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #16330 from felixcheung/rderby.
* [MINOR][R] Reorder `Collate` fields in DESCRIPTION filehyukjinkwon2017-03-191-1/+1
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? It seems cran check scripts corrects `R/pkg/DESCRIPTION` and follows the order in `Collate` fields. This PR proposes to fix this so that running this script does not show up a diff in this file. ## How was this patch tested? Manually via `./R/check-cran.sh`. Author: hyukjinkwon <gurwls223@gmail.com> Closes #17349 from HyukjinKwon/minor-cran.
* [SPARK-19654][SPARKR][SS] Structured Streaming API for RFelix Cheung2017-03-188-5/+573
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Add "experimental" API for SS in R ## How was this patch tested? manual, unit tests Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #16982 from felixcheung/rss.
* [SPARK-19828][R] Support array type in from_json in Rhyukjinkwon2017-03-142-2/+22
| | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Since we could not directly define the array type in R, this PR proposes to support array types in R as string types that are used in `structField` as below: ```R jsonArr <- "[{\"name\":\"Bob\"}, {\"name\":\"Alice\"}]" df <- as.DataFrame(list(list("people" = jsonArr))) collect(select(df, alias(from_json(df$people, "array<struct<name:string>>"), "arrcol"))) ``` prints ```R arrcol 1 Bob, Alice ``` ## How was this patch tested? Unit tests in `test_sparkSQL.R`. Author: hyukjinkwon <gurwls223@gmail.com> Closes #17178 from HyukjinKwon/SPARK-19828.
* [SPARK-19391][SPARKR][ML] Tweedie GLM API for SparkRactuaryzhang2017-03-143-10/+102
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Port Tweedie GLM #16344 to SparkR felixcheung yanboliang ## How was this patch tested? new test in SparkR Author: actuaryzhang <actuaryzhang10@gmail.com> Closes #16729 from actuaryzhang/sparkRTweedie.
* [SPARK-19282][ML][SPARKR] RandomForest Wrapper and GBT Wrapper return param ↵Xin Ren2017-03-122-4/+17
| | | | | | | | | | | | | | | | | | | | | | "maxDepth" to R models ## What changes were proposed in this pull request? RandomForest R Wrapper and GBT R Wrapper return param `maxDepth` to R models. Below 4 R wrappers are changed: * `RandomForestClassificationWrapper` * `RandomForestRegressionWrapper` * `GBTClassificationWrapper` * `GBTRegressionWrapper` ## How was this patch tested? Test manually on my local machine. Author: Xin Ren <iamshrek@126.com> Closes #17207 from keypointt/SPARK-19282.
* [SPARK-19601][SQL] Fix CollapseRepartition rule to preserve shuffle-enabled ↵Xiao Li2017-03-081-2/+2
| | | | | | | | | | | | | | | | | | | | | | | | | | | Repartition ### What changes were proposed in this pull request? Observed by felixcheung in https://github.com/apache/spark/pull/16739, when users use the shuffle-enabled `repartition` API, they expect the partition they got should be the exact number they provided, even if they call shuffle-disabled `coalesce` later. Currently, `CollapseRepartition` rule does not consider whether shuffle is enabled or not. Thus, we got the following unexpected result. ```Scala val df = spark.range(0, 10000, 1, 5) val df2 = df.repartition(10) assert(df2.coalesce(13).rdd.getNumPartitions == 5) assert(df2.coalesce(7).rdd.getNumPartitions == 5) assert(df2.coalesce(3).rdd.getNumPartitions == 3) ``` This PR is to fix the issue. We preserve shuffle-enabled Repartition. ### How was this patch tested? Added a test case Author: Xiao Li <gatorsmile@gmail.com> Closes #16933 from gatorsmile/CollapseRepartition.
* [SPARK-19818][SPARKR] rbind should check for name consistency of input data ↵actuaryzhang2017-03-062-1/+14
| | | | | | | | | | | | | | frames ## What changes were proposed in this pull request? Added checks for name consistency of input data frames in union. ## How was this patch tested? new test. Author: actuaryzhang <actuaryzhang10@gmail.com> Closes #17159 from actuaryzhang/sparkRUnion.
* [SPARK-19795][SPARKR] add column functions to_json, from_jsonFelix Cheung2017-03-054-7/+103
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Add column functions: to_json, from_json, and tests covering error cases. ## How was this patch tested? unit tests, manual Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #17134 from felixcheung/rtojson.
* [SPARK-19550][SPARKR][DOCS] Update R document to use JDK8Yuming Wang2017-03-041-1/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Update R document to use JDK8. ## How was this patch tested? manual tests Author: Yuming Wang <wgyumg@gmail.com> Closes #17162 from wangyum/SPARK-19550.
* [SPARK-18352][DOCS] wholeFile JSON update doc and programming guideFelix Cheung2017-03-021-3/+7
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Update doc for R, programming guide. Clarify default behavior for all languages. ## How was this patch tested? manually Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #17128 from felixcheung/jsonwholefiledoc.
* [DOC][MINOR][SPARKR] Update SparkR doc for names, columns and colnamesactuaryzhang2017-03-012-2/+8
| | | | | | | | | | | | Update R doc: 1. columns, names and colnames returns a vector of strings, not **list** as in current doc. 2. `colnames<-` does allow the subset assignment, so the length of `value` can be less than the number of columns, e.g., `colnames(df)[1] <- "a"`. felixcheung Author: actuaryzhang <actuaryzhang10@gmail.com> Closes #17115 from actuaryzhang/sparkRMinorDoc.
* [SPARK-19460][SPARKR] Update dataset used in R documentation, examples to ↵wm624@hotmail.com2017-02-285-52/+57
| | | | | | | | | | | | | | | | reduce warning noise and confusions ## What changes were proposed in this pull request? Replace `iris` dataset with `Titanic` or other dataset in example and document. ## How was this patch tested? Manual and existing test Author: wm624@hotmail.com <wm624@hotmail.com> Closes #17032 from wangmiao1981/example.
* [SPARK-19660][CORE][SQL] Replace the configuration property names that are ↵Yuming Wang2017-02-282-2/+2
| | | | | | | | | | | | | | | | | | | | | | deprecated in the version of Hadoop 2.6 ## What changes were proposed in this pull request? Replace all the Hadoop deprecated configuration property names according to [DeprecatedProperties](https://hadoop.apache.org/docs/r2.6.0/hadoop-project-dist/hadoop-common/DeprecatedProperties.html). except: https://github.com/apache/spark/blob/v2.1.0/python/pyspark/sql/tests.py#L1533 https://github.com/apache/spark/blob/v2.1.0/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala#L987 https://github.com/apache/spark/blob/v2.1.0/sql/core/src/main/scala/org/apache/spark/sql/execution/command/SetCommand.scala#L45 https://github.com/apache/spark/blob/v2.1.0/sql/core/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala#L614 ## How was this patch tested? Existing tests Author: Yuming Wang <wgyumg@gmail.com> Closes #16990 from wangyum/HadoopDeprecatedProperties.
* [SPARK-19682][SPARKR] Issue warning (or error) when subset method "[[" takes ↵actuaryzhang2017-02-232-0/+20
| | | | | | | | | | | | | | | | vector index ## What changes were proposed in this pull request? The `[[` method is supposed to take a single index and return a column. This is different from base R which takes a vector index. We should check for this and issue warning or error when vector index is supplied (which is very likely given the behavior in base R). Currently I'm issuing a warning message and just take the first element of the vector index. We could change this to an error it that's better. ## How was this patch tested? new tests Author: actuaryzhang <actuaryzhang10@gmail.com> Closes #17017 from actuaryzhang/sparkRSubsetter.
* [SPARK-19616][SPARKR] weightCol and aggregationDepth should be improved for ↵wm624@hotmail.com2017-02-224-14/+35
| | | | | | | | | | | | | | | | | some SparkR APIs ## What changes were proposed in this pull request? This is a follow-up PR of #16800 When doing SPARK-19456, we found that "" should be consider a NULL column name and should not be set. aggregationDepth should be exposed as an expert parameter. ## How was this patch tested? Existing tests. Author: wm624@hotmail.com <wm624@hotmail.com> Closes #16945 from wangmiao1981/svc.
* [SPARK-19639][SPARKR][EXAMPLE] Add spark.svmLinear example and update vignetteswm624@hotmail.com2017-02-171-0/+22
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? We recently add the spark.svmLinear API for SparkR. We need to add an example and update the vignettes. ## How was this patch tested? Manually run example. Author: wm624@hotmail.com <wm624@hotmail.com> Closes #16969 from wangmiao1981/example.
* [SPARK-18285][SPARKR] SparkR approxQuantile supports input multiple columnsYanbo Liang2017-02-173-14/+31
| | | | | | | | | | | | ## What changes were proposed in this pull request? SparkR ```approxQuantile``` supports input multiple columns. ## How was this patch tested? Unit test. Author: Yanbo Liang <ybliang8@gmail.com> Closes #16951 from yanboliang/spark-19619.
* [SPARK-19399][SPARKR] Add R coalesce API for DataFrame and ColumnFelix Cheung2017-02-157-14/+106
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Add coalesce on DataFrame for down partitioning without shuffle and coalesce on Column ## How was this patch tested? manual, unit tests Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #16739 from felixcheung/rcoalesce.
* [SPARK-19456][SPARKR] Add LinearSVC R APIwm624@hotmail.com2017-02-155-4/+188
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Linear SVM classifier is newly added into ML and python API has been added. This JIRA is to add R side API. Marked as WIP, as I am designing unit tests. ## How was this patch tested? Please review http://spark.apache.org/contributing.html before opening a pull request. Author: wm624@hotmail.com <wm624@hotmail.com> Closes #16800 from wangmiao1981/svc.
* [SPARK-19387][SPARKR] Tests do not run with SparkR source package in CRAN checkFelix Cheung2017-02-144-7/+21
| | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? - this is cause by changes in SPARK-18444, SPARK-18643 that we no longer install Spark when `master = ""` (default), but also related to SPARK-18449 since the real `master` value is not known at the time the R code in `sparkR.session` is run. (`master` cannot default to "local" since it could be overridden by spark-submit commandline or spark config) - as a result, while running SparkR as a package in IDE is working fine, CRAN check is not as it is launching it via non-interactive script - fix is to add check to the beginning of each test and vignettes; the same would also work by changing `sparkR.session()` to `sparkR.session(master = "local")` in tests, but I think being more explicit is better. ## How was this patch tested? Tested this by reverting version to 2.1, since it needs to download the release jar with matching version. But since there are changes in 2.2 (specifically around SparkR ML) that are incompatible with 2.1, some tests are failing in this config. Will need to port this to branch-2.1 and retest with 2.1 release jar. manually as: ``` # modify DESCRIPTION to revert version to 2.1.0 SPARK_HOME=/usr/spark R CMD build pkg # run cran check without SPARK_HOME R CMD check --as-cran SparkR_2.1.0.tar.gz ``` Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #16720 from felixcheung/rcranchecktest.
* [SPARK-19342][SPARKR] bug fixed in collect method for collecting timestamp ↵titicaca2017-02-123-4/+43
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | column ## What changes were proposed in this pull request? Fix a bug in collect method for collecting timestamp column, the bug can be reproduced as shown in the following codes and outputs: ``` library(SparkR) sparkR.session(master = "local") df <- data.frame(col1 = c(0, 1, 2), col2 = c(as.POSIXct("2017-01-01 00:00:01"), NA, as.POSIXct("2017-01-01 12:00:01"))) sdf1 <- createDataFrame(df) print(dtypes(sdf1)) df1 <- collect(sdf1) print(lapply(df1, class)) sdf2 <- filter(sdf1, "col1 > 0") print(dtypes(sdf2)) df2 <- collect(sdf2) print(lapply(df2, class)) ``` As we can see from the printed output, the column type of col2 in df2 is converted to numeric unexpectedly, when NA exists at the top of the column. This is caused by method `do.call(c, list)`, if we convert a list, i.e. `do.call(c, list(NA, as.POSIXct("2017-01-01 12:00:01"))`, the class of the result is numeric instead of POSIXct. Therefore, we need to cast the data type of the vector explicitly. ## How was this patch tested? The patch can be tested manually with the same code above. Author: titicaca <fangzhou.yang@hotmail.com> Closes #16689 from titicaca/sparkr-dev.
* [SPARK-19464][BUILD][HOTFIX] run-tests should use hadoop2.6Dongjoon Hyun2017-02-081-3/+0
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? After SPARK-19464, **SparkPullRequestBuilder** fails because it still tries to use hadoop2.3. **BEFORE** https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/72595/console ``` ======================================================================== Building Spark ======================================================================== [error] Could not find hadoop2.3 in the list. Valid options are ['hadoop2.6', 'hadoop2.7'] Attempting to post to Github... > Post successful. ``` **AFTER** https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/72595/console ``` ======================================================================== Building Spark ======================================================================== [info] Building Spark (w/Hive 1.2.1) using SBT with these arguments: -Phadoop-2.6 -Pmesos -Pkinesis-asl -Pyarn -Phive-thriftserver -Phive test:package streaming-kafka-0-8-assembly/assembly streaming-flume-assembly/assembly streaming-kinesis-asl-assembly/assembly Using /usr/java/jdk1.8.0_60 as default JAVA_HOME. Note, this will be overridden by -java-home if it is set. ``` ## How was this patch tested? Pass the existing test. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #16858 from dongjoon-hyun/hotfix_run-tests.
* [SPARK-16609] Add to_date/to_timestamp with format functionsanabranch2017-02-074-8/+80
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This pull request adds two new user facing functions: - `to_date` which accepts an expression and a format and returns a date. - `to_timestamp` which accepts an expression and a format and returns a timestamp. For example, Given a date in format: `2016-21-05`. (YYYY-dd-MM) ### Date Function *Previously* ``` to_date(unix_timestamp(lit("2016-21-05"), "yyyy-dd-MM").cast("timestamp")) ``` *Current* ``` to_date(lit("2016-21-05"), "yyyy-dd-MM") ``` ### Timestamp Function *Previously* ``` unix_timestamp(lit("2016-21-05"), "yyyy-dd-MM").cast("timestamp") ``` *Current* ``` to_timestamp(lit("2016-21-05"), "yyyy-dd-MM") ``` ### Tasks - [X] Add `to_date` to Scala Functions - [x] Add `to_date` to Python Functions - [x] Add `to_date` to SQL Functions - [X] Add `to_timestamp` to Scala Functions - [x] Add `to_timestamp` to Python Functions - [x] Add `to_timestamp` to SQL Functions - [x] Add function to R ## How was this patch tested? - [x] Add Functions to `DateFunctionsSuite` - Test new `ParseToTimestamp` Expression (*not necessary*) - Test new `ParseToDate` Expression (*not necessary*) - [x] Add test for R - [x] Add test for Python in test.py Please review http://spark.apache.org/contributing.html before opening a pull request. Author: anabranch <wac.chambers@gmail.com> Author: Bill Chambers <bill@databricks.com> Author: anabranch <bill@databricks.com> Closes #16138 from anabranch/SPARK-16609.
* [SPARK-19452][SPARKR] Fix bug in the name assignment methodactuaryzhang2017-02-052-4/+10
| | | | | | | | | | | | ## What changes were proposed in this pull request? The names method fails to check for validity of the assignment values. This can be fixed by calling colnames within names. ## How was this patch tested? new tests. Author: actuaryzhang <actuaryzhang10@gmail.com> Closes #16794 from actuaryzhang/sparkRNames.
* [SPARK-19386][SPARKR][FOLLOWUP] fix error in vignettesactuaryzhang2017-02-031-2/+2
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Current version has error in vignettes: ``` model <- spark.bisectingKmeans(df, Sepal_Length ~ Sepal_Width, k = 4) summary(kmeansModel) ``` `kmeansModel` does not exist... felixcheung wangmiao1981 Author: actuaryzhang <actuaryzhang10@gmail.com> Closes #16799 from actuaryzhang/sparkRVignettes.
* [SPARK-19386][SPARKR][DOC] Bisecting k-means in SparkR documentationkrishnakalyan32017-02-031-0/+14
| | | | | | | | | ## What changes were proposed in this pull request? Update programming guide, example and vignette with Bisecting k-means. Author: krishnakalyan3 <krishnakalyan3@gmail.com> Closes #16767 from krishnakalyan3/bisecting-kmeans.
* [SPARK-19319][SPARKR] SparkR Kmeans summary returns error when the cluster ↵wm624@hotmail.com2017-01-312-10/+21
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | size doesn't equal to k ## What changes were proposed in this pull request When Kmeans using initMode = "random" and some random seed, it is possible the actual cluster size doesn't equal to the configured `k`. In this case, summary(model) returns error due to the number of cols of coefficient matrix doesn't equal to k. Example: > col1 <- c(1, 2, 3, 4, 0, 1, 2, 3, 4, 0) > col2 <- c(1, 2, 3, 4, 0, 1, 2, 3, 4, 0) > col3 <- c(1, 2, 3, 4, 0, 1, 2, 3, 4, 0) > cols <- as.data.frame(cbind(col1, col2, col3)) > df <- createDataFrame(cols) > > model2 <- spark.kmeans(data = df, ~ ., k = 5, maxIter = 10, initMode = "random", seed = 22222, tol = 1E-5) > > summary(model2) Error in `colnames<-`(`*tmp*`, value = c("col1", "col2", "col3")) : length of 'dimnames' [2] not equal to array extent In addition: Warning message: In matrix(coefficients, ncol = k) : data length [9] is not a sub-multiple or multiple of the number of rows [2] Fix: Get the actual cluster size in the summary and use it to build the coefficient matrix. ## How was this patch tested? Add unit tests. Author: wm624@hotmail.com <wm624@hotmail.com> Closes #16666 from wangmiao1981/kmeans.
* [SPARK-19395][SPARKR] Convert coefficients in summary to matrixactuaryzhang2017-01-316-22/+34
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? The `coefficients` component in model summary should be 'matrix' but the underlying structure is indeed list. This affects several models except for 'AFTSurvivalRegressionModel' which has the correct implementation. The fix is to first `unlist` the coefficients returned from the `callJMethod` before converting to matrix. An example illustrates the issues: ``` data(iris) df <- createDataFrame(iris) model <- spark.glm(df, Sepal_Length ~ Sepal_Width, family = "gaussian") s <- summary(model) > str(s$coefficients) List of 8 $ : num 6.53 $ : num -0.223 $ : num 0.479 $ : num 0.155 $ : num 13.6 $ : num -1.44 $ : num 0 $ : num 0.152 - attr(*, "dim")= int [1:2] 2 4 - attr(*, "dimnames")=List of 2 ..$ : chr [1:2] "(Intercept)" "Sepal_Width" ..$ : chr [1:4] "Estimate" "Std. Error" "t value" "Pr(>|t|)" > s$coefficients[, 2] $`(Intercept)` [1] 0.4788963 $Sepal_Width [1] 0.1550809 ``` This shows that the underlying structure of coefficients is still `list`. felixcheung wangmiao1981 Author: actuaryzhang <actuaryzhang10@gmail.com> Closes #16730 from actuaryzhang/sparkRCoef.
* [SPARKR][DOCS] update R API doc for subset/extractFelix Cheung2017-01-305-9/+20
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? With extract `[[` or replace `[[<-`, the parameter `i` is a column index, that needs to be corrected in doc. Also a few minor updates: examples, links. ## How was this patch tested? manual Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #16721 from felixcheung/rsubsetdoc.
* [SPARK-19324][SPARKR] Spark VJM stdout output is getting dropped in SparkRFelix Cheung2017-01-272-4/+9
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This affects mostly running job from the driver in client mode when results are expected to be through stdout (which should be somewhat rare, but possible) Before: ``` > a <- as.DataFrame(cars) > b <- group_by(a, "dist") > c <- count(b) > sparkR.callJMethod(c$countjc, "explain", TRUE) NULL ``` After: ``` > a <- as.DataFrame(cars) > b <- group_by(a, "dist") > c <- count(b) > sparkR.callJMethod(c$countjc, "explain", TRUE) count#11L NULL ``` Now, `column.explain()` doesn't seem very useful (we can get more extensive output with `DataFrame.explain()`) but there are other more complex examples with calls of `println` in Scala/JVM side, that are getting dropped. ## How was this patch tested? manual Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #16670 from felixcheung/rjvmstdout.
* [SPARK-19333][SPARKR] Add Apache License headers to R filesFelix Cheung2017-01-272-0/+34
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? add header ## How was this patch tested? Manual run to check vignettes html is created properly Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #16709 from felixcheung/rfilelicense.
* [SPARK-18788][SPARKR] Add API for getNumPartitionsFelix Cheung2017-01-267-31/+59
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? With doc to say this would convert DF into RDD ## How was this patch tested? unit tests, manual tests Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #16668 from felixcheung/rgetnumpartitions.
* [SPARK-18821][SPARKR] Bisecting k-means wrapper in SparkRwm624@hotmail.com2017-01-265-5/+202
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Add R wrapper for bisecting Kmeans. As JIRA is down, I will update title to link with corresponding JIRA later. ## How was this patch tested? Add new unit tests. Author: wm624@hotmail.com <wm624@hotmail.com> Closes #16566 from wangmiao1981/bk.
* [SPARK-18823][SPARKR] add support for assigning to columnFelix Cheung2017-01-242-13/+55
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Support for ``` df[[myname]] <- 1 df[[2]] <- df$eruptions ``` ## How was this patch tested? manual tests, unit tests Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #16663 from felixcheung/rcolset.
* [SPARK-19291][SPARKR][ML] spark.gaussianMixture supports output log-likelihood.Yanbo Liang2017-01-212-2/+10
| | | | | | | | | | | | ## What changes were proposed in this pull request? ```spark.gaussianMixture``` supports output total log-likelihood for the model like R ```mvnormalmixEM```. ## How was this patch tested? R unit test. Author: Yanbo Liang <ybliang8@gmail.com> Closes #16646 from yanboliang/spark-19291.
* [SPARK-19231][SPARKR] add error handling for download and untar for Spark ↵Felix Cheung2017-01-181-15/+40
| | | | | | | | | | | | | | | | release ## What changes were proposed in this pull request? When R is starting as a package and it needs to download the Spark release distribution we need to handle error for download and untar, and clean up, otherwise it will get stuck. ## How was this patch tested? manually Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #16589 from felixcheung/rtarreturncode.
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