[
https://issues.apache.org/jira/browse/SPARK-4077?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14190531#comment-14190531
]
Yin Huai commented on SPARK-4077:
---------------------------------
[~gvramana] Thank you for looking at it. Seems for text source, Hive use
LazyTimestamp to deserialize the value and set it to TimestampWriteable. So,
this issue only affects text sources, right?
[The
code|https://github.com/apache/hive/blob/trunk/serde/src/java/org/apache/hadoop/hive/serde2/io/TimestampWritable.java#L130]
mentioned by [~gvramana] is shown as follows.
{code:java}
public void set(Timestamp t) {
if (t == null) {
timestamp.setTime(0);
timestamp.setNanos(0);
return;
}
this.timestamp = t;
bytesEmpty = true;
timestampEmpty = false;
}
{code}
btw, why the result of runSqlHive(ask hive to run the query) is not affected?
> A broken string timestamp value can Spark SQL return wrong values for valid
> string timestamp values
> ---------------------------------------------------------------------------------------------------
>
> Key: SPARK-4077
> URL: https://issues.apache.org/jira/browse/SPARK-4077
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.1.0
> Reporter: Yin Huai
> Assignee: Venkata Ramana G
>
> The following case returns wrong results.
> The text file is
> {code}
> 2014-12-11 00:00:00,1
> 2014-12-11astring00:00:00,2
> {code}
> The DDL statement and the query are shown below...
> {code}
> sql("""
> create external table date_test(my_date timestamp, id int)
> row format delimited
> fields terminated by ','
> lines terminated by '\n'
> LOCATION 'dateTest'
> """)
> sql("select * from date_test").collect.foreach(println)
> {code}
> The result is
> {code}
> [1969-12-31 19:00:00.0,1]
> [null,2]
> {code}
> If I change the data to
> {code}
> 2014-12-11 00:00:00,1
> 2014-12-11 00:00:00,2
> {code}
> The result is fine.
> For the data with broken string timestamp value, I tried runSqlHive. The
> result is fine.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
