[jira] [Updated] (SPARK-8420) Inconsistent behavior with Dataframe Timestamp between 1.3.1 and 1.4.0
[
https://issues.apache.org/jira/browse/SPARK-8420?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Michael Armbrust updated SPARK-8420:
Labels: (was: releasenotes)
Inconsistent behavior with Dataframe Timestamp between 1.3.1 and 1.4.0
--
Key: SPARK-8420
URL: https://issues.apache.org/jira/browse/SPARK-8420
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 1.4.0
Reporter: Justin Yip
Assignee: Michael Armbrust
Priority: Blocker
Fix For: 1.4.1, 1.5.0
I am trying out 1.4.0 and notice there are some differences in behavior with
Timestamp between 1.3.1 and 1.4.0.
In 1.3.1, I can compare a Timestamp with string.
{code}
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2, Timestamp.valueOf(2014-01-01
00:00:00
...
scala df.filter($_2 = 2014-06-01).show
...
_1 _2
2 2014-01-01 00:00:...
{code}
However, in 1.4.0, the filter is always false:
{code}
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2, Timestamp.valueOf(2014-01-01
00:00:00
df: org.apache.spark.sql.DataFrame = [_1: int, _2: timestamp]
scala df.filter($_2 = 2014-06-01).show
+--+--+
|_1|_2|
+--+--+
+--+--+
{code}
Not sure if that is intended, but I cannot find any doc mentioning these
inconsistencies.
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[jira] [Updated] (SPARK-8420) Inconsistent behavior with Dataframe Timestamp between 1.3.1 and 1.4.0
[
https://issues.apache.org/jira/browse/SPARK-8420?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Michael Armbrust updated SPARK-8420:
Shepherd: Yin Huai
Inconsistent behavior with Dataframe Timestamp between 1.3.1 and 1.4.0
--
Key: SPARK-8420
URL: https://issues.apache.org/jira/browse/SPARK-8420
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 1.4.0
Reporter: Justin Yip
Assignee: Michael Armbrust
Priority: Blocker
Labels: releasenotes
I am trying out 1.4.0 and notice there are some differences in behavior with
Timestamp between 1.3.1 and 1.4.0.
In 1.3.1, I can compare a Timestamp with string.
{code}
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2, Timestamp.valueOf(2014-01-01
00:00:00
...
scala df.filter($_2 = 2014-06-01).show
...
_1 _2
2 2014-01-01 00:00:...
{code}
However, in 1.4.0, the filter is always false:
{code}
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2, Timestamp.valueOf(2014-01-01
00:00:00
df: org.apache.spark.sql.DataFrame = [_1: int, _2: timestamp]
scala df.filter($_2 = 2014-06-01).show
+--+--+
|_1|_2|
+--+--+
+--+--+
{code}
Not sure if that is intended, but I cannot find any doc mentioning these
inconsistencies.
--
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[jira] [Updated] (SPARK-8420) Inconsistent behavior with Dataframe Timestamp between 1.3.1 and 1.4.0
[
https://issues.apache.org/jira/browse/SPARK-8420?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Yin Huai updated SPARK-8420:
Fix Version/s: 1.5.0
Inconsistent behavior with Dataframe Timestamp between 1.3.1 and 1.4.0
--
Key: SPARK-8420
URL: https://issues.apache.org/jira/browse/SPARK-8420
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 1.4.0
Reporter: Justin Yip
Assignee: Michael Armbrust
Priority: Blocker
Labels: releasenotes
Fix For: 1.5.0
I am trying out 1.4.0 and notice there are some differences in behavior with
Timestamp between 1.3.1 and 1.4.0.
In 1.3.1, I can compare a Timestamp with string.
{code}
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2, Timestamp.valueOf(2014-01-01
00:00:00
...
scala df.filter($_2 = 2014-06-01).show
...
_1 _2
2 2014-01-01 00:00:...
{code}
However, in 1.4.0, the filter is always false:
{code}
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2, Timestamp.valueOf(2014-01-01
00:00:00
df: org.apache.spark.sql.DataFrame = [_1: int, _2: timestamp]
scala df.filter($_2 = 2014-06-01).show
+--+--+
|_1|_2|
+--+--+
+--+--+
{code}
Not sure if that is intended, but I cannot find any doc mentioning these
inconsistencies.
--
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[jira] [Updated] (SPARK-8420) Inconsistent behavior with Dataframe Timestamp between 1.3.1 and 1.4.0
[
https://issues.apache.org/jira/browse/SPARK-8420?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Xiangrui Meng updated SPARK-8420:
-
Assignee: Yin Huai
Inconsistent behavior with Dataframe Timestamp between 1.3.1 and 1.4.0
--
Key: SPARK-8420
URL: https://issues.apache.org/jira/browse/SPARK-8420
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 1.4.0
Reporter: Justin Yip
Assignee: Yin Huai
Priority: Blocker
I am trying out 1.4.0 and notice there are some differences in behavior with
Timestamp between 1.3.1 and 1.4.0.
In 1.3.1, I can compare a Timestamp with string.
{code}
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2, Timestamp.valueOf(2014-01-01
00:00:00
...
scala df.filter($_2 = 2014-06-01).show
...
_1 _2
2 2014-01-01 00:00:...
{code}
However, in 1.4.0, the filter is always false:
{code}
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2, Timestamp.valueOf(2014-01-01
00:00:00
df: org.apache.spark.sql.DataFrame = [_1: int, _2: timestamp]
scala df.filter($_2 = 2014-06-01).show
+--+--+
|_1|_2|
+--+--+
+--+--+
{code}
Not sure if that is intended, but I cannot find any doc mentioning these
inconsistencies.
--
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(v6.3.4#6332)
-
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[jira] [Updated] (SPARK-8420) Inconsistent behavior with Dataframe Timestamp between 1.3.1 and 1.4.0
[
https://issues.apache.org/jira/browse/SPARK-8420?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Michael Armbrust updated SPARK-8420:
Labels: releasenotes (was: )
Inconsistent behavior with Dataframe Timestamp between 1.3.1 and 1.4.0
--
Key: SPARK-8420
URL: https://issues.apache.org/jira/browse/SPARK-8420
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 1.4.0
Reporter: Justin Yip
Assignee: Michael Armbrust
Priority: Blocker
Labels: releasenotes
I am trying out 1.4.0 and notice there are some differences in behavior with
Timestamp between 1.3.1 and 1.4.0.
In 1.3.1, I can compare a Timestamp with string.
{code}
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2, Timestamp.valueOf(2014-01-01
00:00:00
...
scala df.filter($_2 = 2014-06-01).show
...
_1 _2
2 2014-01-01 00:00:...
{code}
However, in 1.4.0, the filter is always false:
{code}
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2, Timestamp.valueOf(2014-01-01
00:00:00
df: org.apache.spark.sql.DataFrame = [_1: int, _2: timestamp]
scala df.filter($_2 = 2014-06-01).show
+--+--+
|_1|_2|
+--+--+
+--+--+
{code}
Not sure if that is intended, but I cannot find any doc mentioning these
inconsistencies.
--
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(v6.3.4#6332)
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[jira] [Updated] (SPARK-8420) Inconsistent behavior with Dataframe Timestamp between 1.3.1 and 1.4.0
[
https://issues.apache.org/jira/browse/SPARK-8420?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Yin Huai updated SPARK-8420:
Target Version/s: 1.4.1, 1.5.0 (was: 1.4.1)
Inconsistent behavior with Dataframe Timestamp between 1.3.1 and 1.4.0
--
Key: SPARK-8420
URL: https://issues.apache.org/jira/browse/SPARK-8420
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 1.4.0
Reporter: Justin Yip
Priority: Blocker
I am trying out 1.4.0 and notice there are some differences in behavior with
Timestamp between 1.3.1 and 1.4.0.
In 1.3.1, I can compare a Timestamp with string.
{code}
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2, Timestamp.valueOf(2014-01-01
00:00:00
...
scala df.filter($_2 = 2014-06-01).show
...
_1 _2
2 2014-01-01 00:00:...
{code}
However, in 1.4.0, the filter is always false:
{code}
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2, Timestamp.valueOf(2014-01-01
00:00:00
df: org.apache.spark.sql.DataFrame = [_1: int, _2: timestamp]
scala df.filter($_2 = 2014-06-01).show
+--+--+
|_1|_2|
+--+--+
+--+--+
{code}
Not sure if that is intended, but I cannot find any doc mentioning these
inconsistencies.
--
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(v6.3.4#6332)
-
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[jira] [Updated] (SPARK-8420) Inconsistent behavior with Dataframe Timestamp between 1.3.1 and 1.4.0
[
https://issues.apache.org/jira/browse/SPARK-8420?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Michael Armbrust updated SPARK-8420:
Description:
I am trying out 1.4.0 and notice there are some differences in behavior with
Timestamp between 1.3.1 and 1.4.0.
In 1.3.1, I can compare a Timestamp with string.
{code}
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2, Timestamp.valueOf(2014-01-01
00:00:00
...
scala df.filter($_2 = 2014-06-01).show
...
_1 _2
2 2014-01-01 00:00:...
{code}
However, in 1.4.0, the filter is always false:
{code}
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2, Timestamp.valueOf(2014-01-01
00:00:00
df: org.apache.spark.sql.DataFrame = [_1: int, _2: timestamp]
scala df.filter($_2 = 2014-06-01).show
+--+--+
|_1|_2|
+--+--+
+--+--+
{code}
Not sure if that is intended, but I cannot find any doc mentioning these
inconsistencies.
was:
I am trying out 1.4.0 and notice there are some differences in behavior with
Timestamp between 1.3.1 and 1.4.0.
In 1.3.1, I can compare a Timestamp with string.
{code}
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2, Timestamp.valueOf(2014-01-01
00:00:00
...
scala df.filter($_2 = 2014-06-01).show
...
_1 _2
2 2014-01-01 00:00:...
{code}
However, in 1.4.0, the filter is always false:
{code}
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2, Timestamp.valueOf(2014-01-01
00:00:00
df: org.apache.spark.sql.DataFrame = [_1: int, _2: timestamp]
scala df.filter($_2 = 2014-06-01).show
+--+--+
|_1|_2|
+--+--+
+--+--+
{code}
Not sure if that is intended, but I cannot find any doc mentioning these
inconsistencies.
Priority: Blocker (was: Minor)
Target Version/s: 1.4.0
Inconsistent behavior with Dataframe Timestamp between 1.3.1 and 1.4.0
--
Key: SPARK-8420
URL: https://issues.apache.org/jira/browse/SPARK-8420
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 1.4.0
Reporter: Justin Yip
Priority: Blocker
I am trying out 1.4.0 and notice there are some differences in behavior with
Timestamp between 1.3.1 and 1.4.0.
In 1.3.1, I can compare a Timestamp with string.
{code}
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2, Timestamp.valueOf(2014-01-01
00:00:00
...
scala df.filter($_2 = 2014-06-01).show
...
_1 _2
2 2014-01-01 00:00:...
{code}
However, in 1.4.0, the filter is always false:
{code}
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2, Timestamp.valueOf(2014-01-01
00:00:00
df: org.apache.spark.sql.DataFrame = [_1: int, _2: timestamp]
scala df.filter($_2 = 2014-06-01).show
+--+--+
|_1|_2|
+--+--+
+--+--+
{code}
Not sure if that is intended, but I cannot find any doc mentioning these
inconsistencies.
--
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(v6.3.4#6332)
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[jira] [Updated] (SPARK-8420) Inconsistent behavior with Dataframe Timestamp between 1.3.1 and 1.4.0
[
https://issues.apache.org/jira/browse/SPARK-8420?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Michael Armbrust updated SPARK-8420:
Target Version/s: 1.4.1 (was: 1.4.0)
Inconsistent behavior with Dataframe Timestamp between 1.3.1 and 1.4.0
--
Key: SPARK-8420
URL: https://issues.apache.org/jira/browse/SPARK-8420
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 1.4.0
Reporter: Justin Yip
Priority: Blocker
I am trying out 1.4.0 and notice there are some differences in behavior with
Timestamp between 1.3.1 and 1.4.0.
In 1.3.1, I can compare a Timestamp with string.
{code}
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2, Timestamp.valueOf(2014-01-01
00:00:00
...
scala df.filter($_2 = 2014-06-01).show
...
_1 _2
2 2014-01-01 00:00:...
{code}
However, in 1.4.0, the filter is always false:
{code}
scala val df = sqlContext.createDataFrame(Seq((1,
Timestamp.valueOf(2015-01-01 00:00:00)), (2, Timestamp.valueOf(2014-01-01
00:00:00
df: org.apache.spark.sql.DataFrame = [_1: int, _2: timestamp]
scala df.filter($_2 = 2014-06-01).show
+--+--+
|_1|_2|
+--+--+
+--+--+
{code}
Not sure if that is intended, but I cannot find any doc mentioning these
inconsistencies.
--
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