[SPARK-13841][SQL] Removes Dataset.collectRows()/takeRows()

## What changes were proposed in this pull request?

This PR removes two methods, `collectRows()` and `takeRows()`, from `Dataset[T]`. These methods were added in PR #11443, and were later considered not useful.

## How was this patch tested?

Existing tests should do the work.

Author: Cheng Lian <lian@databricks.com>

Closes #11678 from liancheng/remove-collect-rows-and-take-rows.

13 files changed, 17 insertions, 14 deletions

diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaBinarizerExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaBinarizerExample.java
index d554377975..0a6e9c2a1f 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaBinarizerExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaBinarizerExample.java
@@ -58,7 +58,7 @@ public class JavaBinarizerExample {
       .setThreshold(0.5);
     Dataset<Row> binarizedDataFrame = binarizer.transform(continuousDataFrame);
     Dataset<Row> binarizedFeatures = binarizedDataFrame.select("binarized_feature");
-    for (Row r : binarizedFeatures.collectRows()) {
+    for (Row r : binarizedFeatures.collectAsList()) {
       Double binarized_value = r.getDouble(0);
       System.out.println(binarized_value);
     }
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaCrossValidatorExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaCrossValidatorExample.java
index 90bc94c45b..07edeb3e52 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaCrossValidatorExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaCrossValidatorExample.java
@@ -117,7 +117,7 @@ public class JavaCrossValidatorExample {
 
     // Make predictions on test documents. cvModel uses the best model found (lrModel).
     Dataset<Row> predictions = cvModel.transform(test);
-    for (Row r: predictions.select("id", "text", "probability", "prediction").collectRows()) {
+    for (Row r: predictions.select("id", "text", "probability", "prediction").collectAsList()) {
       System.out.println("(" + r.get(0) + ", " + r.get(1) + ") --> prob=" + r.get(2)
           + ", prediction=" + r.get(3));
     }
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java
index e8ae100d68..8a10dd48aa 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java
@@ -85,7 +85,7 @@ public class JavaDeveloperApiExample {
     // Make predictions on test documents. cvModel uses the best model found (lrModel).
     Dataset<Row> results = model.transform(test);
     double sumPredictions = 0;
-    for (Row r : results.select("features", "label", "prediction").collectRows()) {
+    for (Row r : results.select("features", "label", "prediction").collectAsList()) {
       sumPredictions += r.getDouble(2);
     }
     if (sumPredictions != 0.0) {
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaEstimatorTransformerParamExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaEstimatorTransformerParamExample.java
index f13698ae5e..604b193dd4 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaEstimatorTransformerParamExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaEstimatorTransformerParamExample.java
@@ -100,7 +100,8 @@ public class JavaEstimatorTransformerParamExample {
     // Note that model2.transform() outputs a 'myProbability' column instead of the usual
     // 'probability' column since we renamed the lr.probabilityCol parameter previously.
     Dataset<Row> results = model2.transform(test);
-    for (Row r : results.select("features", "label", "myProbability", "prediction").collectRows()) {
+    Dataset<Row> rows = results.select("features", "label", "myProbability", "prediction");
+    for (Row r: rows.collectAsList()) {
       System.out.println("(" + r.get(0) + ", " + r.get(1) + ") -> prob=" + r.get(2)
         + ", prediction=" + r.get(3));
     }
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaModelSelectionViaCrossValidationExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaModelSelectionViaCrossValidationExample.java
index e394605db7..c4122d1247 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaModelSelectionViaCrossValidationExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaModelSelectionViaCrossValidationExample.java
@@ -111,7 +111,7 @@ public class JavaModelSelectionViaCrossValidationExample {
 
     // Make predictions on test documents. cvModel uses the best model found (lrModel).
     Dataset<Row> predictions = cvModel.transform(test);
-    for (Row r : predictions.select("id", "text", "probability", "prediction").collectRows()) {
+    for (Row r : predictions.select("id", "text", "probability", "prediction").collectAsList()) {
       System.out.println("(" + r.get(0) + ", " + r.get(1) + ") --> prob=" + r.get(2)
         + ", prediction=" + r.get(3));
     }
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaNGramExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaNGramExample.java
index 0305f737ca..608bd80285 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaNGramExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaNGramExample.java
@@ -60,7 +60,7 @@ public class JavaNGramExample {
 
     Dataset<Row> ngramDataFrame = ngramTransformer.transform(wordDataFrame);
 
-    for (Row r : ngramDataFrame.select("ngrams", "label").takeRows(3)) {
+    for (Row r : ngramDataFrame.select("ngrams", "label").takeAsList(3)) {
       java.util.List<String> ngrams = r.getList(0);
       for (String ngram : ngrams) System.out.print(ngram + " --- ");
       System.out.println();
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaPipelineExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaPipelineExample.java
index 6ae418d564..305420f208 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaPipelineExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaPipelineExample.java
@@ -80,7 +80,7 @@ public class JavaPipelineExample {
 
     // Make predictions on test documents.
     Dataset<Row> predictions = model.transform(test);
-    for (Row r : predictions.select("id", "text", "probability", "prediction").collectRows()) {
+    for (Row r : predictions.select("id", "text", "probability", "prediction").collectAsList()) {
       System.out.println("(" + r.get(0) + ", " + r.get(1) + ") --> prob=" + r.get(2)
         + ", prediction=" + r.get(3));
     }
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaPolynomialExpansionExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaPolynomialExpansionExample.java
index 5a4064c604..48fc3c8acb 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaPolynomialExpansionExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaPolynomialExpansionExample.java
@@ -23,6 +23,7 @@ import org.apache.spark.sql.SQLContext;
 
 // $example on$
 import java.util.Arrays;
+import java.util.List;
 
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.ml.feature.PolynomialExpansion;
@@ -61,8 +62,8 @@ public class JavaPolynomialExpansionExample {
     Dataset<Row> df = jsql.createDataFrame(data, schema);
     Dataset<Row> polyDF = polyExpansion.transform(df);
 
-    Row[] row = polyDF.select("polyFeatures").takeRows(3);
-    for (Row r : row) {
+    List<Row> rows = polyDF.select("polyFeatures").takeAsList(3);
+    for (Row r : rows) {
       System.out.println(r.get(0));
     }
     // $example off$
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaSimpleParamsExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaSimpleParamsExample.java
index 52bb4ec050..cb911ef5ef 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaSimpleParamsExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaSimpleParamsExample.java
@@ -103,7 +103,8 @@ public class JavaSimpleParamsExample {
     // Note that model2.transform() outputs a 'myProbability' column instead of the usual
     // 'probability' column since we renamed the lr.probabilityCol parameter previously.
     Dataset<Row> results = model2.transform(test);
-    for (Row r: results.select("features", "label", "myProbability", "prediction").collectRows()) {
+    Dataset<Row> rows = results.select("features", "label", "myProbability", "prediction");
+    for (Row r: rows.collectAsList()) {
       System.out.println("(" + r.get(0) + ", " + r.get(1) + ") -> prob=" + r.get(2)
           + ", prediction=" + r.get(3));
     }
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaSimpleTextClassificationPipeline.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaSimpleTextClassificationPipeline.java
index 9bd543c44f..a18a60f448 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaSimpleTextClassificationPipeline.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaSimpleTextClassificationPipeline.java
@@ -84,7 +84,7 @@ public class JavaSimpleTextClassificationPipeline {
 
     // Make predictions on test documents.
     Dataset<Row> predictions = model.transform(test);
-    for (Row r: predictions.select("id", "text", "probability", "prediction").collectRows()) {
+    for (Row r: predictions.select("id", "text", "probability", "prediction").collectAsList()) {
       System.out.println("(" + r.get(0) + ", " + r.get(1) + ") --> prob=" + r.get(2)
           + ", prediction=" + r.get(3));
     }
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaTfIdfExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaTfIdfExample.java
index fd1ce424bf..37a3d0d84d 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaTfIdfExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaTfIdfExample.java
@@ -66,7 +66,7 @@ public class JavaTfIdfExample {
     IDF idf = new IDF().setInputCol("rawFeatures").setOutputCol("features");
     IDFModel idfModel = idf.fit(featurizedData);
     Dataset<Row> rescaledData = idfModel.transform(featurizedData);
-    for (Row r : rescaledData.select("features", "label").takeRows(3)) {
+    for (Row r : rescaledData.select("features", "label").takeAsList(3)) {
       Vector features = r.getAs(0);
       Double label = r.getDouble(1);
       System.out.println(features);
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaTokenizerExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaTokenizerExample.java
index a2f8c436e3..9225fe2262 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaTokenizerExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaTokenizerExample.java
@@ -59,7 +59,7 @@ public class JavaTokenizerExample {
     Tokenizer tokenizer = new Tokenizer().setInputCol("sentence").setOutputCol("words");
 
     Dataset<Row> wordsDataFrame = tokenizer.transform(sentenceDataFrame);
-    for (Row r : wordsDataFrame.select("words", "label").takeRows(3)) {
+    for (Row r : wordsDataFrame.select("words", "label").takeAsList(3)) {
       java.util.List<String> words = r.getList(0);
       for (String word : words) System.out.print(word + " ");
       System.out.println();
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaWord2VecExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaWord2VecExample.java
index 2dce8c2168..c5bb1eaaa3 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaWord2VecExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaWord2VecExample.java
@@ -59,7 +59,7 @@ public class JavaWord2VecExample {
       .setMinCount(0);
     Word2VecModel model = word2Vec.fit(documentDF);
     Dataset<Row> result = model.transform(documentDF);
-    for (Row r : result.select("result").takeRows(3)) {
+    for (Row r : result.select("result").takeAsList(3)) {
       System.out.println(r);
     }
     // $example off$