8c198e246d
## What changes were proposed in this pull request? This PR introduces the new SparkSession API for SparkR. `sparkR.session.getOrCreate()` and `sparkR.session.stop()` "getOrCreate" is a bit unusual in R but it's important to name this clearly. SparkR implementation should - SparkSession is the main entrypoint (vs SparkContext; due to limited functionality supported with SparkContext in SparkR) - SparkSession replaces SQLContext and HiveContext (both a wrapper around SparkSession, and because of API changes, supporting all 3 would be a lot more work) - Changes to SparkSession is mostly transparent to users due to SPARK-10903 - Full backward compatibility is expected - users should be able to initialize everything just in Spark 1.6.1 (`sparkR.init()`), but with deprecation warning - Mostly cosmetic changes to parameter list - users should be able to move to `sparkR.session.getOrCreate()` easily - An advanced syntax with named parameters (aka varargs aka "...") is supported; that should be closer to the Builder syntax that is in Scala/Python (which unfortunately does not work in R because it will look like this: `enableHiveSupport(config(config(master(appName(builder(), "foo"), "local"), "first", "value"), "next, "value"))` - Updating config on an existing SparkSession is supported, the behavior is the same as Python, in which config is applied to both SparkContext and SparkSession - Some SparkSession changes are not matched in SparkR, mostly because it would be breaking API change: `catalog` object, `createOrReplaceTempView` - Other SQLContext workarounds are replicated in SparkR, eg. `tables`, `tableNames` - `sparkR` shell is updated to use the SparkSession entrypoint (`sqlContext` is removed, just like with Scale/Python) - All tests are updated to use the SparkSession entrypoint - A bug in `read.jdbc` is fixed TODO - [x] Add more tests - [ ] Separate PR - update all roxygen2 doc coding example - [ ] Separate PR - update SparkR programming guide ## How was this patch tested? unit tests, manual tests shivaram sun-rui rxin Author: Felix Cheung <felixcheung_m@hotmail.com> Author: felixcheung <felixcheung_m@hotmail.com> Closes #13635 from felixcheung/rsparksession.
111 lines
4.4 KiB
R
111 lines
4.4 KiB
R
#
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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context("parallelize() and collect()")
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# Mock data
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numVector <- c(-10:97)
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numList <- list(sqrt(1), sqrt(2), sqrt(3), 4 ** 10)
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strVector <- c("Dexter Morgan: I suppose I should be upset, even feel",
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"violated, but I'm not. No, in fact, I think this is a friendly",
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"message, like \"Hey, wanna play?\" and yes, I want to play. ",
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"I really, really do.")
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strList <- list("Dexter Morgan: Blood. Sometimes it sets my teeth on edge, ",
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"other times it helps me control the chaos.",
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"Dexter Morgan: Harry and Dorris Morgan did a wonderful job ",
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"raising me. But they're both dead now. I didn't kill them. Honest.")
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numPairs <- list(list(1, 1), list(1, 2), list(2, 2), list(2, 3))
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strPairs <- list(list(strList, strList), list(strList, strList))
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# JavaSparkContext handle
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sparkSession <- sparkR.session()
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jsc <- callJStatic("org.apache.spark.sql.api.r.SQLUtils", "getJavaSparkContext", sparkSession)
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# Tests
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test_that("parallelize() on simple vectors and lists returns an RDD", {
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numVectorRDD <- parallelize(jsc, numVector, 1)
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numVectorRDD2 <- parallelize(jsc, numVector, 10)
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numListRDD <- parallelize(jsc, numList, 1)
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numListRDD2 <- parallelize(jsc, numList, 4)
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strVectorRDD <- parallelize(jsc, strVector, 2)
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strVectorRDD2 <- parallelize(jsc, strVector, 3)
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strListRDD <- parallelize(jsc, strList, 4)
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strListRDD2 <- parallelize(jsc, strList, 1)
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rdds <- c(numVectorRDD,
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numVectorRDD2,
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numListRDD,
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numListRDD2,
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strVectorRDD,
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strVectorRDD2,
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strListRDD,
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strListRDD2)
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for (rdd in rdds) {
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expect_is(rdd, "RDD")
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expect_true(.hasSlot(rdd, "jrdd")
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&& inherits(rdd@jrdd, "jobj")
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&& isInstanceOf(rdd@jrdd, "org.apache.spark.api.java.JavaRDD"))
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}
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})
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test_that("collect(), following a parallelize(), gives back the original collections", {
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numVectorRDD <- parallelize(jsc, numVector, 10)
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expect_equal(collect(numVectorRDD), as.list(numVector))
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numListRDD <- parallelize(jsc, numList, 1)
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numListRDD2 <- parallelize(jsc, numList, 4)
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expect_equal(collect(numListRDD), as.list(numList))
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expect_equal(collect(numListRDD2), as.list(numList))
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strVectorRDD <- parallelize(jsc, strVector, 2)
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strVectorRDD2 <- parallelize(jsc, strVector, 3)
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expect_equal(collect(strVectorRDD), as.list(strVector))
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expect_equal(collect(strVectorRDD2), as.list(strVector))
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strListRDD <- parallelize(jsc, strList, 4)
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strListRDD2 <- parallelize(jsc, strList, 1)
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expect_equal(collect(strListRDD), as.list(strList))
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expect_equal(collect(strListRDD2), as.list(strList))
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})
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test_that("regression: collect() following a parallelize() does not drop elements", {
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# 10 %/% 6 = 1, ceiling(10 / 6) = 2
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collLen <- 10
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numPart <- 6
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expected <- runif(collLen)
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actual <- collect(parallelize(jsc, expected, numPart))
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expect_equal(actual, as.list(expected))
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})
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test_that("parallelize() and collect() work for lists of pairs (pairwise data)", {
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# use the pairwise logical to indicate pairwise data
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numPairsRDDD1 <- parallelize(jsc, numPairs, 1)
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numPairsRDDD2 <- parallelize(jsc, numPairs, 2)
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numPairsRDDD3 <- parallelize(jsc, numPairs, 3)
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expect_equal(collect(numPairsRDDD1), numPairs)
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expect_equal(collect(numPairsRDDD2), numPairs)
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expect_equal(collect(numPairsRDDD3), numPairs)
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# can also leave out the parameter name, if the params are supplied in order
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strPairsRDDD1 <- parallelize(jsc, strPairs, 1)
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strPairsRDDD2 <- parallelize(jsc, strPairs, 2)
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expect_equal(collect(strPairsRDDD1), strPairs)
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expect_equal(collect(strPairsRDDD2), strPairs)
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})
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