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Posted to reviews@spark.apache.org by yanboliang <gi...@git.apache.org> on 2016/04/30 12:46:49 UTC
[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/12813
[SPARK-15030] [ML] [SparkR] Support formula in spark.kmeans in SparkR
## What changes were proposed in this pull request?
* Support formula in ```spark.kmeans``` in SparkR.
* Fix some outdated docs for SparkR.
## How was this patch tested?
Unit tests.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/yanboliang/spark spark-15030
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/12813.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 #12813
----
commit 2080090e7a2ec55eb0c2a9f9be79db76f8a98189
Author: Yanbo Liang <yb...@gmail.com>
Date: 2016-04-30T09:46:22Z
Support formula in spark.kmeans in SparkR
commit 12dfae14670e3c526530c4aa70810d2e45195b73
Author: Yanbo Liang <yb...@gmail.com>
Date: 2016-04-30T10:06:03Z
fix some docs
commit f1ba442350378296d07855a71e2299bd9fecde11
Author: Yanbo Liang <yb...@gmail.com>
Date: 2016-04-30T10:43:33Z
update some docs
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/12813#issuecomment-215964440
**[Test build #57445 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/57445/consoleFull)** for PR 12813 at commit [`79d1be4`](https://github.com/apache/spark/commit/79d1be46a518010247a722a51868f7d71bb56557).
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/12813#issuecomment-215956645
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/12813#issuecomment-215966562
**[Test build #57446 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/57446/consoleFull)** for PR 12813 at commit [`5bdce92`](https://github.com/apache/spark/commit/5bdce92bb427d5a665fba9eb20b6c6ec9bb3428b).
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/12813#issuecomment-215956643
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by yanboliang <gi...@git.apache.org>.
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/12813#discussion_r61669864
--- Diff: R/pkg/R/mllib.R ---
@@ -271,22 +274,25 @@ setMethod("summary", signature(object = "NaiveBayesModel"),
#' Fit a k-means model, similarly to R's kmeans().
#'
#' @param data SparkDataFrame for training
-#' @param k Number of centers
-#' @param maxIter Maximum iteration number
-#' @param initializationMode Algorithm choosen to fit the model
+#' @param formula A symbolic description of the model to be fitted. Currently only a few formula
+#' operators are supported, including '~', '.', ':', '+', and '-'.
+#' Note that the response variable of formula is empty in spark.kmeans.
+#' @param centers Number of centers
+#' @param iter.max Maximum iteration number
+#' @param algorithm The initialization algorithm choosen to fit the model
#' @return A fitted k-means model
#' @rdname spark.kmeans
#' @export
#' @examples
#' \dontrun{
-#' model <- spark.kmeans(data, k = 2, initializationMode="random")
+#' model <- spark.kmeans(data, ~ ., centers = 2, algorithm="random")
#' }
-setMethod("spark.kmeans", signature(data = "SparkDataFrame"),
- function(data, k, maxIter = 10, initializationMode = c("random", "k-means||")) {
- columnNames <- as.array(colnames(data))
- initializationMode <- match.arg(initializationMode)
- jobj <- callJStatic("org.apache.spark.ml.r.KMeansWrapper", "fit", data@sdf,
- k, maxIter, initializationMode, columnNames)
+setMethod("spark.kmeans", signature(data = "SparkDataFrame", formula = "formula"),
+ function(data, formula, centers, iter.max = 10, algorithm = c("random", "k-means||")) {
--- End diff --
In ```spark.glm```, we use
```
function(data, formula, family = gaussian, epsilon = 1e-06, maxit = 25)
```
Should we also fix them in this PR?
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/12813#issuecomment-215963096
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Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/12813#issuecomment-215970154
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/12813#issuecomment-215963089
**[Test build #57442 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/57442/consoleFull)** for PR 12813 at commit [`f1ba442`](https://github.com/apache/spark/commit/f1ba442350378296d07855a71e2299bd9fecde11).
* This patch **fails Spark unit tests**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/12813#issuecomment-215961834
**[Test build #57442 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/57442/consoleFull)** for PR 12813 at commit [`f1ba442`](https://github.com/apache/spark/commit/f1ba442350378296d07855a71e2299bd9fecde11).
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by mengxr <gi...@git.apache.org>.
Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/12813#issuecomment-215973911
LGTM. Merged into master. Thanks!
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by yanboliang <gi...@git.apache.org>.
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/12813#discussion_r61669670
--- Diff: R/pkg/R/mllib.R ---
@@ -271,22 +274,25 @@ setMethod("summary", signature(object = "NaiveBayesModel"),
#' Fit a k-means model, similarly to R's kmeans().
#'
#' @param data SparkDataFrame for training
-#' @param k Number of centers
-#' @param maxIter Maximum iteration number
-#' @param initializationMode Algorithm choosen to fit the model
+#' @param formula A symbolic description of the model to be fitted. Currently only a few formula
+#' operators are supported, including '~', '.', ':', '+', and '-'.
+#' Note that the response variable of formula is empty in spark.kmeans.
+#' @param centers Number of centers
+#' @param iter.max Maximum iteration number
+#' @param algorithm The initialization algorithm choosen to fit the model
#' @return A fitted k-means model
#' @rdname spark.kmeans
#' @export
#' @examples
#' \dontrun{
-#' model <- spark.kmeans(data, k = 2, initializationMode="random")
+#' model <- spark.kmeans(data, ~ ., centers = 2, algorithm="random")
#' }
-setMethod("spark.kmeans", signature(data = "SparkDataFrame"),
- function(data, k, maxIter = 10, initializationMode = c("random", "k-means||")) {
- columnNames <- as.array(colnames(data))
- initializationMode <- match.arg(initializationMode)
- jobj <- callJStatic("org.apache.spark.ml.r.KMeansWrapper", "fit", data@sdf,
- k, maxIter, initializationMode, columnNames)
+setMethod("spark.kmeans", signature(data = "SparkDataFrame", formula = "formula"),
+ function(data, formula, centers, iter.max = 10, algorithm = c("random", "k-means||")) {
--- End diff --
I vote for ```max.iter/init.mode```, and will update it.
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by mengxr <gi...@git.apache.org>.
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/12813#discussion_r61669606
--- Diff: R/pkg/R/mllib.R ---
@@ -271,22 +274,25 @@ setMethod("summary", signature(object = "NaiveBayesModel"),
#' Fit a k-means model, similarly to R's kmeans().
#'
#' @param data SparkDataFrame for training
-#' @param k Number of centers
-#' @param maxIter Maximum iteration number
-#' @param initializationMode Algorithm choosen to fit the model
+#' @param formula A symbolic description of the model to be fitted. Currently only a few formula
+#' operators are supported, including '~', '.', ':', '+', and '-'.
+#' Note that the response variable of formula is empty in spark.kmeans.
+#' @param centers Number of centers
+#' @param iter.max Maximum iteration number
+#' @param algorithm The initialization algorithm choosen to fit the model
#' @return A fitted k-means model
#' @rdname spark.kmeans
#' @export
#' @examples
#' \dontrun{
-#' model <- spark.kmeans(data, k = 2, initializationMode="random")
+#' model <- spark.kmeans(data, ~ ., centers = 2, algorithm="random")
#' }
-setMethod("spark.kmeans", signature(data = "SparkDataFrame"),
- function(data, k, maxIter = 10, initializationMode = c("random", "k-means||")) {
- columnNames <- as.array(colnames(data))
- initializationMode <- match.arg(initializationMode)
- jobj <- callJStatic("org.apache.spark.ml.r.KMeansWrapper", "fit", data@sdf,
- k, maxIter, initializationMode, columnNames)
+setMethod("spark.kmeans", signature(data = "SparkDataFrame", formula = "formula"),
+ function(data, formula, centers, iter.max = 10, algorithm = c("random", "k-means||")) {
--- End diff --
Since `spark.kmeans` already indicates that this method is different from R's `kmeans`, we made the param names consistent with MLlib params. Especially the change from `algorithm` to `initMode` makes more sense. We should discuss whether we want to use `maxIter`/`initMode` or `max.iter`/`init.mode` as params.
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by mengxr <gi...@git.apache.org>.
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/12813#discussion_r61669769
--- Diff: R/pkg/R/mllib.R ---
@@ -271,22 +274,25 @@ setMethod("summary", signature(object = "NaiveBayesModel"),
#' Fit a k-means model, similarly to R's kmeans().
#'
#' @param data SparkDataFrame for training
-#' @param k Number of centers
-#' @param maxIter Maximum iteration number
-#' @param initializationMode Algorithm choosen to fit the model
+#' @param formula A symbolic description of the model to be fitted. Currently only a few formula
+#' operators are supported, including '~', '.', ':', '+', and '-'.
+#' Note that the response variable of formula is empty in spark.kmeans.
+#' @param centers Number of centers
+#' @param iter.max Maximum iteration number
+#' @param algorithm The initialization algorithm choosen to fit the model
#' @return A fitted k-means model
#' @rdname spark.kmeans
#' @export
#' @examples
#' \dontrun{
-#' model <- spark.kmeans(data, k = 2, initializationMode="random")
+#' model <- spark.kmeans(data, ~ ., centers = 2, algorithm="random")
#' }
-setMethod("spark.kmeans", signature(data = "SparkDataFrame"),
- function(data, k, maxIter = 10, initializationMode = c("random", "k-means||")) {
- columnNames <- as.array(colnames(data))
- initializationMode <- match.arg(initializationMode)
- jobj <- callJStatic("org.apache.spark.ml.r.KMeansWrapper", "fit", data@sdf,
- k, maxIter, initializationMode, columnNames)
+setMethod("spark.kmeans", signature(data = "SparkDataFrame", formula = "formula"),
+ function(data, formula, centers, iter.max = 10, algorithm = c("random", "k-means||")) {
--- End diff --
We need to be consistent with other SparkR APIs. For example, we have `approxQuantile(x, col, probabilities, relativeError)` and `insertInto(x, tableName)`. Given those existing APIs, I think we should use `maxIter` and `initMode` here. But I didn't scan all existing methods.
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/12813#issuecomment-215971072
Merged build finished. Test PASSed.
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by yanboliang <gi...@git.apache.org>.
Github user yanboliang commented on the pull request:
https://github.com/apache/spark/pull/12813#issuecomment-215961694
Jenkins, test this please.
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/12813#issuecomment-215956628
**[Test build #57439 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/57439/consoleFull)** for PR 12813 at commit [`f1ba442`](https://github.com/apache/spark/commit/f1ba442350378296d07855a71e2299bd9fecde11).
* This patch **fails Spark unit tests**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by asfgit <gi...@git.apache.org>.
Github user asfgit closed the pull request at:
https://github.com/apache/spark/pull/12813
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/12813#issuecomment-215970127
**[Test build #57445 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/57445/consoleFull)** for PR 12813 at commit [`79d1be4`](https://github.com/apache/spark/commit/79d1be46a518010247a722a51868f7d71bb56557).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/12813#issuecomment-215954387
**[Test build #57439 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/57439/consoleFull)** for PR 12813 at commit [`f1ba442`](https://github.com/apache/spark/commit/f1ba442350378296d07855a71e2299bd9fecde11).
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/12813#issuecomment-215971047
**[Test build #57446 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/57446/consoleFull)** for PR 12813 at commit [`5bdce92`](https://github.com/apache/spark/commit/5bdce92bb427d5a665fba9eb20b6c6ec9bb3428b).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/12813#issuecomment-215970155
Test PASSed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/57445/
Test PASSed.
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by yanboliang <gi...@git.apache.org>.
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/12813#discussion_r61670513
--- Diff: mllib/src/test/java/org/apache/spark/mllib/stat/JavaStatisticsSuite.java ---
@@ -72,7 +72,7 @@ public void testCorr() {
Double corr1 = Statistics.corr(x, y);
Double corr2 = Statistics.corr(x, y, "pearson");
// Check default method
- assertEquals(corr1, corr2);
+ assertEquals(corr1, corr2, 1e-5);
--- End diff --
Fix the unstable test BTW.
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[GitHub] spark pull request: [SPARK-15030] [ML] [SparkR] Support formula in...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/12813#issuecomment-215963095
Merged build finished. Test FAILed.
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