[
https://issues.apache.org/jira/browse/SPARK-38140?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Wenchen Fan resolved SPARK-38140.
---------------------------------
Fix Version/s: 3.3.0
Resolution: Fixed
Issue resolved by pull request 35440
[https://github.com/apache/spark/pull/35440]
> Desc column stats (min, max) for timestamp type is not consistent with the
> value due to time zone difference
> ------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-38140
> URL: https://issues.apache.org/jira/browse/SPARK-38140
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.1.2, 3.2.1
> Reporter: Zhenhua Wang
> Assignee: Zhenhua Wang
> Priority: Minor
> Fix For: 3.3.0
>
>
> Currently timestamp column's stats (min/max) are stored in UTC in metastore,
> and when desc its min/max column stats, they are also shown in UTC.
> As a result, for users not in UTC, the column stats (shown to users) are not
> consistent with the actual value, which causes confusion.
> For example:
> {noformat}
> spark-sql> create table tab_ts_master (ts timestamp) using parquet;
> spark-sql> insert into tab_ts_master values make_timestamp(2022, 1, 1, 0, 0,
> 1.123456), make_timestamp(2022, 1, 3, 0, 0, 2.987654);
> spark-sql> select * from tab_ts_master;
> 2022-01-01 00:00:01.123456
> 2022-01-03 00:00:02.987654
> spark-sql> set spark.sql.session.timeZone;
> spark.sql.session.timeZone Asia/Shanghai
> spark-sql> analyze table tab_ts_master compute statistics for all columns;
> spark-sql> desc formatted tab_ts_master ts;
> col_name ts
> data_type timestamp
> comment NULL
> min 2021-12-31 16:00:01.123456
> max 2022-01-02 16:00:02.987654
> num_nulls 0
> distinct_count 2
> avg_col_len 8
> max_col_len 8
> histogram NULL
> {noformat}
--
This message was sent by Atlassian Jira
(v8.20.1#820001)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
