[jira] [Created] (SPARK-32632) Bad partitioning in spark jdbc method with parameter lowerBound and upperBound

["Liu Dinghua (Jira)" <ji...@apache.org>]

Liu Dinghua created SPARK-32632:
-----------------------------------

             Summary: Bad partitioning in spark jdbc method with parameter lowerBound and upperBound
                 Key: SPARK-32632
                 URL: https://issues.apache.org/jira/browse/SPARK-32632
             Project: Spark
          Issue Type: Bug
          Components: SQL
    Affects Versions: 3.0.0
            Reporter: Liu Dinghua


When i use the jdbc methed
{code:java}
def jdbc( url: String, table: String, columnName: String, lowerBound: Long, upperBound: Long, numPartitions: Int, connectionProperties: Properties)
{code}
 
 I am confused by the partitions generated by this method   for the rows of first partition is not limited by the lowerBound and the ones of the last partition isn't limited by the upperBound. 
 
For example, I use the method  as follow:
 
{code:java}
val data = spark.read.jdbc(url, table, "id", 2, 5, 3,buildProperties()) .selectExpr("id","appkey","funnel_name")
data.show(100, false)  
{code}
 

The result partitions info is :

 20/08/05 16:58:59 INFO JDBCRelation: Number of partitions: 3, WHERE clauses of these partitions: `id` < 3 or `id` is null, `id` >= 3 AND `id` < 4, `id` >= 4

The returned data is:
||id|| appkey||funnel_name||
|0|yanshi|test001|
|1|yanshi|test002|
|2|yanshi|test003|
|3|xingkong|test_funnel|
|4|xingkong|test_funnel2|
|5|xingkong|test_funnel3|
|6|donews|test_funnel4|
|7|donews|test_funnel|
|8|donews|test_funnel2|
|9|dami|test_funnel3|
|13|dami|test_funnel4|
|15|xiaoai|test_funnel6|

 

Normally, the clause of the first partition is " 'id' >=2 and `id` < 3 " for the lowerBound is 2, and the clause of the last partition is " `id` >= 4", but the facts are not.

 

 
 



--
This message was sent by Atlassian Jira
(v8.3.4#803005)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org