[GitHub] spark pull request #16020: [SPARK-18596][ML] add checking and caching to bis...
Github user hhbyyh closed the pull request at: https://github.com/apache/spark/pull/16020 --- 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 #16020: [SPARK-18596][ML] add checking and caching to bis...
Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/16020#discussion_r90599078
--- Diff: mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala
---
@@ -334,10 +334,10 @@ class KMeans @Since("1.5.0") (
val summary = new KMeansSummary(
model.transform(dataset), $(predictionCol), $(featuresCol), $(k))
model.setSummary(Some(summary))
-instr.logSuccess(model)
if (handlePersistence) {
instances.unpersist()
}
+instr.logSuccess(model)
--- End diff --
The `handlePersistence` check in `KMeans` at L309 should also be updated to
use `dataset.storageLevel`. Since we're touching KMeans here anyway we may as
well do it now.
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[GitHub] spark pull request #16020: [SPARK-18596][ML] add checking and caching to bis...
Github user hhbyyh commented on a diff in the pull request:
https://github.com/apache/spark/pull/16020#discussion_r89780207
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/clustering/BisectingKMeans.scala ---
@@ -255,10 +256,19 @@ class BisectingKMeans @Since("2.0.0") (
@Since("2.0.0")
override def fit(dataset: Dataset[_]): BisectingKMeansModel = {
+val handlePersistence = dataset.rdd.getStorageLevel ==
StorageLevel.NONE
--- End diff --
Thanks for checking on this. I feel like we should have a unit test for
this, but probably not here.
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[GitHub] spark pull request #16020: [SPARK-18596][ML] add checking and caching to bis...
Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/16020#discussion_r89740159
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/clustering/BisectingKMeans.scala ---
@@ -273,6 +283,7 @@ class BisectingKMeans @Since("2.0.0") (
val summary = new BisectingKMeansSummary(
model.transform(dataset), $(predictionCol), $(featuresCol), $(k))
model.setSummary(Some(summary))
+if (handlePersistence) rdd.unpersist()
--- End diff --
Prefer
```
if (handlePersistence) {
rdd.unpersist()
}
```
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[GitHub] spark pull request #16020: [SPARK-18596][ML] add checking and caching to bis...
Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/16020#discussion_r89740085
--- Diff: mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala
---
@@ -334,10 +334,8 @@ class KMeans @Since("1.5.0") (
val summary = new KMeansSummary(
model.transform(dataset), $(predictionCol), $(featuresCol), $(k))
model.setSummary(Some(summary))
+if (handlePersistence) instances.unpersist()
instr.logSuccess(model)
-if (handlePersistence) {
--- End diff --
prefer to keep this form according to style guide.
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[GitHub] spark pull request #16020: [SPARK-18596][ML] add checking and caching to bis...
Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/16020#discussion_r89740051
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/clustering/BisectingKMeans.scala ---
@@ -255,10 +256,19 @@ class BisectingKMeans @Since("2.0.0") (
@Since("2.0.0")
override def fit(dataset: Dataset[_]): BisectingKMeansModel = {
+val handlePersistence = dataset.rdd.getStorageLevel ==
StorageLevel.NONE
--- End diff --
By the way, I've been meaning to log a ticket for this issue, but have been
tied up.
This will actually never work. `dataset.rdd` will always have storage level
`NONE`. To see this:
```
scala> import org.apache.spark.storage.StorageLevel
import org.apache.spark.storage.StorageLevel
scala> val df = spark.range(10).toDF("num")
df: org.apache.spark.sql.DataFrame = [num: bigint]
scala> df.storageLevel == StorageLevel.NONE
res0: Boolean = true
scala> df.persist
res1: df.type = [num: bigint]
scala> df.storageLevel == StorageLevel.MEMORY_AND_DISK
res2: Boolean = true
scala> df.rdd.getStorageLevel == StorageLevel.MEMORY_AND_DISK
res3: Boolean = false
scala> df.rdd.getStorageLevel == StorageLevel.NONE
res4: Boolean = true
```
So in fact all the algorithms that are checking for storage level using
`dataset.rdd` are actually double-caching the data if the input DataFrame is
actually cached, because the RDD will not appear to be cached.
So we should migrate all the checks to use `dataset.storageLevel` which was
added in https://github.com/apache/spark/pull/13780
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[GitHub] spark pull request #16020: [SPARK-18596][ML] add checking and caching to bis...
GitHub user hhbyyh opened a pull request: https://github.com/apache/spark/pull/16020 [SPARK-18596][ML] add checking and caching to bisecting kmeans ## What changes were proposed in this pull request? jira: https://issues.apache.org/jira/browse/SPARK-18596 This is a follow up for https://issues.apache.org/jira/browse/SPARK-18356. Check if the DataFrame sent to BisectingKMeans is cached, if not, we need to cache the converted RDD to ensure performance for BisectingKMeans. ## How was this patch tested? existing unit tests. You can merge this pull request into a Git repository by running: $ git pull https://github.com/hhbyyh/spark bikcache Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/16020.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 #16020 commit a4c88ee89f175c0672eeebe004ef3ac87a7a464a Author: Yuhao Yang Date: 2016-11-27T05:34:18Z add checking and caching to bisecting kmeans --- 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
