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Github user felixcheung commented on the issue:
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github seems to like to hide stuff.
FYI, this comment
https://github.com/apache/spark/pull/14775#discussion_r76526025
and this
Github user eyalfa commented on the issue:
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@cloud-fan, @hvanhovell ,
I'd really appreciate your comments on this as it really is close to
completion. please let me know if you prefer a new pull request (easier to
review without the merge
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--- Diff: R/pkg/DESCRIPTION ---
@@ -11,7 +11,7 @@ Authors@R: c(person("Shivaram", "Venkataraman", role =
c("aut", "cre"),
email
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--- Diff: R/pkg/R/backend.R ---
@@ -25,9 +25,23 @@ isInstanceOf <- function(jobj, className) {
callJMethod(cls, "isInstance", jobj)
}
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--- Diff: R/pkg/DESCRIPTION ---
@@ -11,7 +11,7 @@ Authors@R: c(person("Shivaram", "Venkataraman", role =
c("aut", "cre"),
email =
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--- Diff: R/pkg/R/jobj.R ---
@@ -82,7 +82,20 @@ getClassName.jobj <- function(x) {
callJMethod(cls, "getName")
}
-cleanup.jobj <-
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--- Diff: R/pkg/DESCRIPTION ---
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c("aut", "cre"),
email
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--- Diff: R/pkg/R/backend.R ---
@@ -37,12 +51,42 @@ callJMethod <- function(objId, methodName, ...) {
invokeJava(isStatic = FALSE, objId$id,
Github user gatorsmile commented on the issue:
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One minor comment about the current PR and the future PRs in statistics.
When we adding new statistics-specific properties, we should exclude them in
the DDL command, like `SHOW CREATE TABLE`.
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Github user gatorsmile commented on the issue:
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uh,,, after reviewing the work in CBO, I found one more bug. We should not
copy the Hive-generated statistics info stored in table properties.
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retest this please
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Found another related JIRA:
https://issues.apache.org/jira/browse/HIVE-12730. This is only available in
Hive 2.1. They are trying to resolve the issues we hit:
> We would like to
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Github user HyukjinKwon commented on the issue:
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Do you mind if I ask https://github.com/apache/spark/pull/10572 is also
closable?
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Is that https://github.com/apache/spark/pull/12095?
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@davies do you have the commit that fixes this in 2.0 ?
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@lins05 I think the LDA model data size usually will be much smaller than
training data, so that here it seems no need to change to treeAggregate ( for
DistributedLDAModel ) . thanks!
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[WIP][SPARK-17138][ML][MLib] Add Python API for multinomial logistic
regression
## What changes were proposed in this pull request?
Add Python API for multinomial logistic
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@felixcheung Good point about having a wrapper -- That will make it easier
to update the methods going forward. I added a new file `jvm.R` with the
wrapper functions.
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--- Diff: R/pkg/R/jobj.R ---
@@ -82,7 +82,20 @@ getClassName.jobj <- function(x) {
callJMethod(cls, "getName")
}
-cleanup.jobj <-
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--- Diff: R/pkg/inst/tests/testthat/test_jvm_api.R ---
@@ -0,0 +1,41 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
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-cleanup.jobj <-
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@@ -37,12 +51,42 @@ callJMethod <- function(objId, methodName, ...) {
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--- Diff: R/pkg/R/backend.R ---
@@ -37,12 +51,42 @@ callJMethod <- function(objId, methodName, ...) {
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@@ -37,12 +51,42 @@ callJMethod <- function(objId, methodName, ...) {
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@@ -37,12 +51,42 @@ callJMethod <- function(objId, methodName, ...) {
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--- Diff: R/pkg/R/backend.R ---
@@ -25,9 +25,23 @@ isInstanceOf <- function(jobj, className) {
callJMethod(cls, "isInstance", jobj)
}
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cc @yanboliang
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[SPARK-17281][ML][MLLib] Add treeAggregateDepth parameter for
AFTSurvivalRegression
## What changes were proposed in this pull request?
Add treeAggregateDepth parameter for
Github user gatorsmile commented on the issue:
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Very recently, Hive 2.0.0 fixed a serious bug. See the JIRA:
https://issues.apache.org/jira/browse/HIVE-12661
We can get a wrong result when the statistics are out of dated (i.e.,
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@cloud-fan let me do more investigation and will reply your question later.
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--- Diff:
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@@ -1294,20 +1296,29 @@ class SparkSqlAstBuilder(conf: SQLConf)
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--- Diff:
core/src/main/scala/org/apache/spark/deploy/history/HistoryServer.scala ---
@@ -225,14 +274,26 @@ class HistoryServer(
}
}
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