[GitHub] spark pull request: [SPARK-8681] fixed wrong ordering of columns i...
Github user asfgit closed the pull request at: https://github.com/apache/spark/pull/7060 --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-8681] fixed wrong ordering of columns i...
Github user rxin commented on the pull request: https://github.com/apache/spark/pull/7060#issuecomment-116827359 Thanks. Merging in master & branch-1.4. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-8681] fixed wrong ordering of columns i...
Github user brkyvz commented on a diff in the pull request:
https://github.com/apache/spark/pull/7060#discussion_r33499886
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/DataFrameStatSuite.scala ---
@@ -65,22 +67,22 @@ class DataFrameStatSuite extends SparkFunSuite {
}
test("crosstab") {
-val df = Seq((0, 0), (2, 1), (1, 0), (2, 0), (0, 0), (2, 0)).toDF("a",
"b")
+val rng = new Random()
+val data = Seq.tabulate(25)(i => (rng.nextInt(5), rng.nextInt(10)))
+val df = data.toDF("a", "b")
val crosstab = df.stat.crosstab("a", "b")
val columnNames = crosstab.schema.fieldNames
assert(columnNames(0) === "a_b")
-assert(columnNames(1) === "0")
-assert(columnNames(2) === "1")
-val rows: Array[Row] = crosstab.collect().sortBy(_.getString(0))
-assert(rows(0).get(0).toString === "0")
-assert(rows(0).getLong(1) === 2L)
-assert(rows(0).get(2) === 0L)
-assert(rows(1).get(0).toString === "1")
-assert(rows(1).getLong(1) === 1L)
-assert(rows(1).get(2) === 0L)
-assert(rows(2).get(0).toString === "2")
-assert(rows(2).getLong(1) === 2L)
-assert(rows(2).getLong(2) === 1L)
+// reduce by key
+val expected = data.map(t => (t, 1)).groupBy(_._1).mapValues(_.length)
+val rows = crosstab.collect()
+rows.foreach { row =>
+ val i = row.getString(0).toInt
+ for (col <- 1 to 9) {
+val j = columnNames(col).toInt
+assert(row.getLong(col) === expected.getOrElse((i, j), 0).toLong)
--- End diff --
That would need a lot of work, because we don't know the ordering of the
rows and the columns
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[GitHub] spark pull request: [SPARK-8681] fixed wrong ordering of columns i...
Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/7060#discussion_r33497360
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/DataFrameStatSuite.scala ---
@@ -65,22 +67,22 @@ class DataFrameStatSuite extends SparkFunSuite {
}
test("crosstab") {
-val df = Seq((0, 0), (2, 1), (1, 0), (2, 0), (0, 0), (2, 0)).toDF("a",
"b")
+val rng = new Random()
+val data = Seq.tabulate(25)(i => (rng.nextInt(5), rng.nextInt(10)))
+val df = data.toDF("a", "b")
val crosstab = df.stat.crosstab("a", "b")
val columnNames = crosstab.schema.fieldNames
assert(columnNames(0) === "a_b")
-assert(columnNames(1) === "0")
-assert(columnNames(2) === "1")
-val rows: Array[Row] = crosstab.collect().sortBy(_.getString(0))
-assert(rows(0).get(0).toString === "0")
-assert(rows(0).getLong(1) === 2L)
-assert(rows(0).get(2) === 0L)
-assert(rows(1).get(0).toString === "1")
-assert(rows(1).getLong(1) === 1L)
-assert(rows(1).get(2) === 0L)
-assert(rows(2).get(0).toString === "2")
-assert(rows(2).getLong(1) === 2L)
-assert(rows(2).getLong(2) === 1L)
+// reduce by key
+val expected = data.map(t => (t, 1)).groupBy(_._1).mapValues(_.length)
+val rows = crosstab.collect()
+rows.foreach { row =>
+ val i = row.getString(0).toInt
+ for (col <- 1 to 9) {
+val j = columnNames(col).toInt
+assert(row.getLong(col) === expected.getOrElse((i, j), 0).toLong)
--- End diff --
Could we use `checkAnswer` here instead?
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[GitHub] spark pull request: [SPARK-8681] fixed wrong ordering of columns i...
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[GitHub] spark pull request: [SPARK-8681] fixed wrong ordering of columns i...
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[GitHub] spark pull request: [SPARK-8681] fixed wrong ordering of columns i...
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[GitHub] spark pull request: [SPARK-8681] fixed wrong ordering of columns i...
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[GitHub] spark pull request: [SPARK-8681] fixed wrong ordering of columns i...
Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/7060#discussion_r33440758
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala
---
@@ -119,14 +119,14 @@ private[sql] object StatFunctions extends Logging {
rows.foreach { (row: Row) =>
// row.get(0) is column 1
// row.get(1) is column 2
-// row.get(3) is the frequency
+// row.get(2) is the frequency
countsRow.setLong(distinctCol2.get(row.get(1)).get + 1,
row.getLong(2))
}
// the value of col1 is the first value, the rest are the counts
countsRow.setString(0, col1Item.toString)
countsRow
}.toSeq
-val headerNames = distinctCol2.map(r => StructField(r._1.toString,
LongType)).toSeq
+val headerNames = distinctCol2.toSeq.sortBy(_._2).map(r =>
StructField(r._1.toString, LongType))
--- End diff --
i'd also add explicit type for distinctCol2, and explain what the tuples are
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[GitHub] spark pull request: [SPARK-8681] fixed wrong ordering of columns i...
Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/7060#discussion_r33440738
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala
---
@@ -119,14 +119,14 @@ private[sql] object StatFunctions extends Logging {
rows.foreach { (row: Row) =>
// row.get(0) is column 1
// row.get(1) is column 2
-// row.get(3) is the frequency
+// row.get(2) is the frequency
countsRow.setLong(distinctCol2.get(row.get(1)).get + 1,
row.getLong(2))
}
// the value of col1 is the first value, the rest are the counts
countsRow.setString(0, col1Item.toString)
countsRow
}.toSeq
-val headerNames = distinctCol2.map(r => StructField(r._1.toString,
LongType)).toSeq
+val headerNames = distinctCol2.toSeq.sortBy(_._2).map(r =>
StructField(r._1.toString, LongType))
--- End diff --
maybe add inline comment explaining what _2 is?
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[GitHub] spark pull request: [SPARK-8681] fixed wrong ordering of columns i...
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[GitHub] spark pull request: [SPARK-8681] fixed wrong ordering of columns i...
GitHub user brkyvz opened a pull request: https://github.com/apache/spark/pull/7060 [SPARK-8681] fixed wrong ordering of columns in crosstab I specifically randomized the test. What crosstab does is equivalent to a countByKey, therefore if this test fails again for any reason, we will know that we hit a corner case or something. cc @rxin @marmbrus You can merge this pull request into a Git repository by running: $ git pull https://github.com/brkyvz/spark crosstab-fixes Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/7060.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #7060 commit d96da7e955574b12587e10d69d6008115ebc6352 Author: Burak Yavuz Date: 2015-06-27T20:35:02Z fixed wrong ordering of columns in crosstab --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
