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Posted to reviews@spark.apache.org by rxin <gi...@git.apache.org> on 2015/02/03 10:09:37 UTC
[GitHub] spark pull request: [SQL] DataFrame API update
GitHub user rxin opened a pull request:
https://github.com/apache/spark/pull/4332
[SQL] DataFrame API update
1. Added Java-friendly version of the expression operators (i.e. gt, geq)
2. Added JavaDoc for most operators
3. Simplified expression operators by having only one version of the function (that accepts Any). Previously we had two methods for each expression operator, one accepting Any and another accepting Column.
4. agg function now accepts varargs of (String, String).
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/rxin/spark df-update
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/4332.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 #4332
----
commit 576d07a2a6dddef77693e5f1caca1df30fd8f2e4
Author: Reynold Xin <rx...@databricks.com>
Date: 2015-02-03T07:48:37Z
random commit.
Conflicts:
sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
commit ab0aa69d2df6ba40359953e32883505ddc309e4f
Author: Reynold Xin <rx...@databricks.com>
Date: 2015-02-03T09:04:30Z
Added Java friendly expression methods.
Added JavaDoc.
For each expression operator, have only one version of the function (that accepts Any). Previously we had two methods for each expression operator, one accepting Any and another accepting Column.
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[GitHub] spark pull request: [SQL] DataFrame API update
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/4332#issuecomment-72617077
[Test build #26644 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/26644/consoleFull) for PR 4332 at commit [`ab0aa69`](https://github.com/apache/spark/commit/ab0aa69d2df6ba40359953e32883505ddc309e4f).
* This patch merges cleanly.
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[GitHub] spark pull request: [SQL] DataFrame API update
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/4332#issuecomment-72626858
Test PASSed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/26644/
Test PASSed.
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[GitHub] spark pull request: [SQL] DataFrame API update
Posted by asfgit <gi...@git.apache.org>.
Github user asfgit closed the pull request at:
https://github.com/apache/spark/pull/4332
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[GitHub] spark pull request: [SQL] DataFrame API update
Posted by davies <gi...@git.apache.org>.
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/4332#discussion_r23991126
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/Dsl.scala ---
@@ -100,27 +91,82 @@ object Dsl {
Column(literalExpr)
}
+ //////////////////////////////////////////////////////////////////////////////////////////////
+ //////////////////////////////////////////////////////////////////////////////////////////////
+
+ /** Aggregate function: returns the sum of all values in the expression. */
def sum(e: Column): Column = Sum(e.expr)
+
+ /** Aggregate function: returns the sum of distinct values in the expression. */
def sumDistinct(e: Column): Column = SumDistinct(e.expr)
+
+ /** Aggregate function: returns the number of items in a group. */
def count(e: Column): Column = Count(e.expr)
+ /** Aggregate function: returns the number of distinct items in a group. */
@scala.annotation.varargs
def countDistinct(expr: Column, exprs: Column*): Column =
CountDistinct((expr +: exprs).map(_.expr))
+ /** Aggregate function: returns the approximate number of distinct items in a group. */
def approxCountDistinct(e: Column): Column = ApproxCountDistinct(e.expr)
- def approxCountDistinct(e: Column, rsd: Double): Column =
- ApproxCountDistinct(e.expr, rsd)
+ /** Aggregate function: returns the approximate number of distinct items in a group. */
+ def approxCountDistinct(e: Column, rsd: Double): Column = ApproxCountDistinct(e.expr, rsd)
+
+ /** Aggregate function: returns the average of the values in a group. */
def avg(e: Column): Column = Average(e.expr)
+
+ /** Aggregate function: returns the first value in a group. */
def first(e: Column): Column = First(e.expr)
+
+ /** Aggregate function: returns the last value in a group. */
def last(e: Column): Column = Last(e.expr)
+
+ /** Aggregate function: returns the minimum value of the expression in a group. */
def min(e: Column): Column = Min(e.expr)
+
+ /** Aggregate function: returns the maximum value of the expression in a group. */
def max(e: Column): Column = Max(e.expr)
+ //////////////////////////////////////////////////////////////////////////////////////////////
+ //////////////////////////////////////////////////////////////////////////////////////////////
+
+ /**
+ * Unary minus, i.e. negate the expression.
+ * {{{
+ * // Select the amount column and negates all values.
+ * // Scala:
+ * df.select( -df("amount") )
+ *
+ * // Java:
+ * df.select( negate(df.col("amount")) );
+ * }}}
+ */
+ def negate(e: Column): Column = -e
--- End diff --
negative or neg?
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[GitHub] spark pull request: [SQL] DataFrame API update
Posted by rxin <gi...@git.apache.org>.
Github user rxin commented on the pull request:
https://github.com/apache/spark/pull/4332#issuecomment-72617197
cc @davies Number 3 is a big change - but it does simplify the API documentation quite a bit.
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[GitHub] spark pull request: [SQL] DataFrame API update
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/4332#issuecomment-72626851
[Test build #26644 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/26644/consoleFull) for PR 4332 at commit [`ab0aa69`](https://github.com/apache/spark/commit/ab0aa69d2df6ba40359953e32883505ddc309e4f).
* This patch **passes all tests**.
* This patch merges cleanly.
* This patch adds no public classes.
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