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author | Xiangrui Meng <meng@databricks.com> | 2015-05-20 20:30:39 -0700 |
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committer | Xiangrui Meng <meng@databricks.com> | 2015-05-20 20:30:39 -0700 |
commit | ddec173cba63df723cd94508121d8c06d8c153c6 (patch) | |
tree | 6732b44d12440832ebf30bcddf8936781b9b728d | |
parent | 42c592adb381ff20832cce55e0849ed68dd7eee4 (diff) | |
download | spark-ddec173cba63df723cd94508121d8c06d8c153c6.tar.gz spark-ddec173cba63df723cd94508121d8c06d8c153c6.tar.bz2 spark-ddec173cba63df723cd94508121d8c06d8c153c6.zip |
[SPARK-7774] [MLLIB] add sqlContext to MLlibTestSparkContext
to simplify test suites that require a SQLContext.
Author: Xiangrui Meng <meng@databricks.com>
Closes #6303 from mengxr/SPARK-7774 and squashes the following commits:
0622b5a [Xiangrui Meng] update some other test suites
e1f9b8d [Xiangrui Meng] add sqlContext to MLlibTestSparkContext
14 files changed, 20 insertions, 79 deletions
diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala index 97f9749cb4..9f77d5f3ef 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala @@ -23,18 +23,16 @@ import org.apache.spark.mllib.classification.LogisticRegressionSuite._ import org.apache.spark.mllib.linalg.Vector import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.mllib.util.TestingUtils._ -import org.apache.spark.sql.{DataFrame, Row, SQLContext} +import org.apache.spark.sql.{DataFrame, Row} class LogisticRegressionSuite extends FunSuite with MLlibTestSparkContext { - @transient var sqlContext: SQLContext = _ @transient var dataset: DataFrame = _ @transient var binaryDataset: DataFrame = _ private val eps: Double = 1e-5 override def beforeAll(): Unit = { super.beforeAll() - sqlContext = new SQLContext(sc) dataset = sqlContext.createDataFrame(generateLogisticInput(1.0, 1.0, nPoints = 100, seed = 42)) diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/OneVsRestSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/OneVsRestSuite.scala index 990cfb08af..770b56890f 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/classification/OneVsRestSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/classification/OneVsRestSuite.scala @@ -21,24 +21,23 @@ import org.scalatest.FunSuite import org.apache.spark.ml.attribute.NominalAttribute import org.apache.spark.ml.util.MetadataUtils -import org.apache.spark.mllib.classification.LogisticRegressionSuite._ import org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS +import org.apache.spark.mllib.classification.LogisticRegressionSuite._ import org.apache.spark.mllib.evaluation.MulticlassMetrics import org.apache.spark.mllib.regression.LabeledPoint import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.rdd.RDD -import org.apache.spark.sql.{DataFrame, SQLContext} +import org.apache.spark.sql.DataFrame class OneVsRestSuite extends FunSuite with MLlibTestSparkContext { - @transient var sqlContext: SQLContext = _ @transient var dataset: DataFrame = _ @transient var rdd: RDD[LabeledPoint] = _ override def beforeAll(): Unit = { super.beforeAll() - sqlContext = new SQLContext(sc) + val nPoints = 1000 // The following weights and xMean/xVariance are computed from iris dataset with lambda=0.2. diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala index caf1b75959..8f6c6b39dc 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala @@ -20,18 +20,14 @@ package org.apache.spark.ml.feature import org.scalatest.FunSuite import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.mllib.util.TestingUtils._ -import org.apache.spark.sql.{DataFrame, Row, SQLContext} - +import org.apache.spark.sql.{DataFrame, Row} class BinarizerSuite extends FunSuite with MLlibTestSparkContext { @transient var data: Array[Double] = _ - @transient var sqlContext: SQLContext = _ override def beforeAll(): Unit = { super.beforeAll() - sqlContext = new SQLContext(sc) data = Array(0.1, -0.5, 0.2, -0.3, 0.8, 0.7, -0.1, -0.4) } diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala index 20d2f3ac66..0391bd8427 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala @@ -25,17 +25,10 @@ import org.apache.spark.SparkException import org.apache.spark.mllib.linalg.Vectors import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.mllib.util.TestingUtils._ -import org.apache.spark.sql.{DataFrame, Row, SQLContext} +import org.apache.spark.sql.{DataFrame, Row} class BucketizerSuite extends FunSuite with MLlibTestSparkContext { - @transient private var sqlContext: SQLContext = _ - - override def beforeAll(): Unit = { - super.beforeAll() - sqlContext = new SQLContext(sc) - } - test("Bucket continuous features, without -inf,inf") { // Check a set of valid feature values. val splits = Array(-0.5, 0.0, 0.5) diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/IDFSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/IDFSuite.scala index eaee3443c1..f85e854716 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/IDFSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/IDFSuite.scala @@ -22,17 +22,10 @@ import org.scalatest.FunSuite import org.apache.spark.mllib.linalg.{DenseVector, SparseVector, Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.mllib.util.TestingUtils._ -import org.apache.spark.sql.{Row, SQLContext} +import org.apache.spark.sql.Row class IDFSuite extends FunSuite with MLlibTestSparkContext { - @transient var sqlContext: SQLContext = _ - - override def beforeAll(): Unit = { - super.beforeAll() - sqlContext = new SQLContext(sc) - } - def scaleDataWithIDF(dataSet: Array[Vector], model: Vector): Array[Vector] = { dataSet.map { case data: DenseVector => diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/OneHotEncoderSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/OneHotEncoderSuite.scala index 92ec407b98..056b9eda86 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/OneHotEncoderSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/OneHotEncoderSuite.scala @@ -21,16 +21,10 @@ import org.scalatest.FunSuite import org.apache.spark.mllib.linalg.Vector import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.sql.{DataFrame, SQLContext} +import org.apache.spark.sql.DataFrame class OneHotEncoderSuite extends FunSuite with MLlibTestSparkContext { - private var sqlContext: SQLContext = _ - - override def beforeAll(): Unit = { - super.beforeAll() - sqlContext = new SQLContext(sc) - } def stringIndexed(): DataFrame = { val data = sc.parallelize(Seq((0, "a"), (1, "b"), (2, "c"), (3, "a"), (4, "a"), (5, "c")), 2) diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/PolynomialExpansionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/PolynomialExpansionSuite.scala index c1d64fba0a..aa230ca073 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/PolynomialExpansionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/PolynomialExpansionSuite.scala @@ -18,22 +18,15 @@ package org.apache.spark.ml.feature import org.scalatest.FunSuite +import org.scalatest.exceptions.TestFailedException import org.apache.spark.mllib.linalg.{DenseVector, SparseVector, Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.mllib.util.TestingUtils._ -import org.apache.spark.sql.{Row, SQLContext} -import org.scalatest.exceptions.TestFailedException +import org.apache.spark.sql.Row class PolynomialExpansionSuite extends FunSuite with MLlibTestSparkContext { - @transient var sqlContext: SQLContext = _ - - override def beforeAll(): Unit = { - super.beforeAll() - sqlContext = new SQLContext(sc) - } - test("Polynomial expansion with default parameter") { val data = Array( Vectors.sparse(3, Seq((0, -2.0), (1, 2.3))), diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala index b6939e5870..89c2fe4557 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala @@ -21,15 +21,8 @@ import org.scalatest.FunSuite import org.apache.spark.ml.attribute.{Attribute, NominalAttribute} import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.sql.SQLContext class StringIndexerSuite extends FunSuite with MLlibTestSparkContext { - private var sqlContext: SQLContext = _ - - override def beforeAll(): Unit = { - super.beforeAll() - sqlContext = new SQLContext(sc) - } test("StringIndexer") { val data = sc.parallelize(Seq((0, "a"), (1, "b"), (2, "c"), (3, "a"), (4, "a"), (5, "c")), 2) diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/TokenizerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/TokenizerSuite.scala index d186ead8f5..a46d08d651 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/TokenizerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/TokenizerSuite.scala @@ -22,7 +22,7 @@ import scala.beans.BeanInfo import org.scalatest.FunSuite import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.sql.{DataFrame, Row, SQLContext} +import org.apache.spark.sql.{DataFrame, Row} @BeanInfo case class TokenizerTestData(rawText: String, wantedTokens: Array[String]) @@ -30,13 +30,6 @@ case class TokenizerTestData(rawText: String, wantedTokens: Array[String]) class RegexTokenizerSuite extends FunSuite with MLlibTestSparkContext { import org.apache.spark.ml.feature.RegexTokenizerSuite._ - @transient var sqlContext: SQLContext = _ - - override def beforeAll(): Unit = { - super.beforeAll() - sqlContext = new SQLContext(sc) - } - test("RegexTokenizer") { val tokenizer = new RegexTokenizer() .setInputCol("rawText") diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala index 0db27607bc..d0cd62c5e4 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala @@ -22,17 +22,10 @@ import org.scalatest.FunSuite import org.apache.spark.SparkException import org.apache.spark.mllib.linalg.{DenseVector, SparseVector, Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.sql.{Row, SQLContext} +import org.apache.spark.sql.Row class VectorAssemblerSuite extends FunSuite with MLlibTestSparkContext { - @transient var sqlContext: SQLContext = _ - - override def beforeAll(): Unit = { - super.beforeAll() - sqlContext = new SQLContext(sc) - } - test("assemble") { import org.apache.spark.ml.feature.VectorAssembler.assemble assert(assemble(0.0) === Vectors.sparse(1, Array.empty, Array.empty)) diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala index 38dc83b124..b11b029c63 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala @@ -26,15 +26,12 @@ import org.apache.spark.ml.attribute._ import org.apache.spark.mllib.linalg.{SparseVector, Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.rdd.RDD -import org.apache.spark.sql.{DataFrame, SQLContext} - +import org.apache.spark.sql.DataFrame class VectorIndexerSuite extends FunSuite with MLlibTestSparkContext { import VectorIndexerSuite.FeatureData - @transient var sqlContext: SQLContext = _ - // identical, of length 3 @transient var densePoints1: DataFrame = _ @transient var sparsePoints1: DataFrame = _ @@ -86,7 +83,6 @@ class VectorIndexerSuite extends FunSuite with MLlibTestSparkContext { checkPair(densePoints1Seq, sparsePoints1Seq) checkPair(densePoints2Seq, sparsePoints2Seq) - sqlContext = new SQLContext(sc) densePoints1 = sqlContext.createDataFrame(sc.parallelize(densePoints1Seq, 2).map(FeatureData)) sparsePoints1 = sqlContext.createDataFrame(sc.parallelize(sparsePoints1Seq, 2).map(FeatureData)) densePoints2 = sqlContext.createDataFrame(sc.parallelize(densePoints2Seq, 2).map(FeatureData)) diff --git a/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala index 6cc6ec94eb..9a35555e52 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala @@ -38,14 +38,12 @@ import org.apache.spark.util.Utils class ALSSuite extends FunSuite with MLlibTestSparkContext with Logging { - private var sqlContext: SQLContext = _ private var tempDir: File = _ override def beforeAll(): Unit = { super.beforeAll() tempDir = Utils.createTempDir() sc.setCheckpointDir(tempDir.getAbsolutePath) - sqlContext = new SQLContext(sc) } override def afterAll(): Unit = { diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala index 80323ef520..50a78631fa 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala @@ -22,11 +22,10 @@ import org.scalatest.FunSuite import org.apache.spark.mllib.linalg.DenseVector import org.apache.spark.mllib.util.{LinearDataGenerator, MLlibTestSparkContext} import org.apache.spark.mllib.util.TestingUtils._ -import org.apache.spark.sql.{Row, SQLContext, DataFrame} +import org.apache.spark.sql.{DataFrame, Row} class LinearRegressionSuite extends FunSuite with MLlibTestSparkContext { - @transient var sqlContext: SQLContext = _ @transient var dataset: DataFrame = _ /** @@ -41,7 +40,6 @@ class LinearRegressionSuite extends FunSuite with MLlibTestSparkContext { */ override def beforeAll(): Unit = { super.beforeAll() - sqlContext = new SQLContext(sc) dataset = sqlContext.createDataFrame( sc.parallelize(LinearDataGenerator.generateLinearInput( 6.3, Array(4.7, 7.2), Array(0.9, -1.3), Array(0.7, 1.2), 10000, 42, 0.1), 2)) diff --git a/mllib/src/test/scala/org/apache/spark/mllib/util/MLlibTestSparkContext.scala b/mllib/src/test/scala/org/apache/spark/mllib/util/MLlibTestSparkContext.scala index b658889476..5d1796ef65 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/util/MLlibTestSparkContext.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/util/MLlibTestSparkContext.scala @@ -17,13 +17,14 @@ package org.apache.spark.mllib.util -import org.scalatest.Suite -import org.scalatest.BeforeAndAfterAll +import org.scalatest.{BeforeAndAfterAll, Suite} import org.apache.spark.{SparkConf, SparkContext} +import org.apache.spark.sql.SQLContext trait MLlibTestSparkContext extends BeforeAndAfterAll { self: Suite => @transient var sc: SparkContext = _ + @transient var sqlContext: SQLContext = _ override def beforeAll() { super.beforeAll() @@ -31,12 +32,15 @@ trait MLlibTestSparkContext extends BeforeAndAfterAll { self: Suite => .setMaster("local[2]") .setAppName("MLlibUnitTest") sc = new SparkContext(conf) + sqlContext = new SQLContext(sc) } override def afterAll() { + sqlContext = null if (sc != null) { sc.stop() } + sc = null super.afterAll() } } |