Mohit Dave created SPARK-31338:
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             Summary: Spark SQL JDBC Data Source partitioned read : Spark SQL 
does not honor for NOT NULL table definition of partition key.
                 Key: SPARK-31338
                 URL: https://issues.apache.org/jira/browse/SPARK-31338
             Project: Spark
          Issue Type: Bug
          Components: Spark Core
    Affects Versions: 2.4.5
            Reporter: Mohit Dave


*Our Use-case Details:*

While reading from a jdbc source using spark sql, we are using below read 
format :

jdbc(url: String, table: String, columnName: String, lowerBound: Long, 
upperBound: Long, numPartitions: Int, connectionProperties: Properties).

 

Table defination : 
postgres=> \d lineitem_sf1000
           Table "public.lineitem_sf1000"     Column      |         Type        
  | Modifiers
-----------------+-----------------------+-----------
 l_orderkey      | bigint                | not *null* l_partkey       | bigint  
              | not null l_suppkey       | bigint                | not null 
l_linenumber    | bigint                | not null l_quantity      | 
numeric(10,2)         | not null l_extendedprice | numeric(10,2)         | not 
null l_discount      | numeric(10,2)         | not null l_tax           | 
numeric(10,2)         | not null l_returnflag    | character varying(1)  | not 
null l_linestatus    | character varying(1)  | not null l_shipdate      | 
character varying(29) | not null l_commitdate    | character varying(29) | not 
null l_receiptdate   | character varying(29) | not null l_shipinstruct  | 
character varying(25) | not null l_shipmode      | character varying(10) | not 
null l_comment       | character varying(44) | not nullIndexes:    
"l_order_sf1000_idx" btree (l_orderkey) 
 

Partition column : l_orderkey 

numpartion : 16

 

*Problem details :* 

 
{code:java}
SELECT 
"l_orderkey","l_shipinstruct","l_quantity","l_partkey","l_discount","l_commitdate","l_receiptdate","l_comment","l_shipmode","l_linestatus","l_suppkey","l_shipdate","l_tax","l_extendedprice","l_linenumber","l_returnflag"
 FROM (SELECT 
l_orderkey,l_partkey,l_suppkey,l_linenumber,l_quantity,l_extendedprice,l_discount,l_tax,l_returnflag,l_linestatus,l_shipdate,l_commitdate,l_receiptdate,l_shipinstruct,l_shipmode,l_comment
 FROM public.lineitem_sf1000) query_alias WHERE l_orderkey >= 1500000001 AND 
l_orderkey < 1875000001 {code}
15 queries are generated with the above BETWEEN clauses. The last query looks 
like this below:
{code:java}
SELECT 
"l_orderkey","l_shipinstruct","l_quantity","l_partkey","l_discount","l_commitdate","l_receiptdate","l_comment","l_shipmode","l_linestatus","l_suppkey","l_shipdate","l_tax","l_extendedprice","l_linenumber","l_returnflag"
 FROM (SELECT 
l_orderkey,l_partkey,l_suppkey,l_linenumber,l_quantity,l_extendedprice,l_discount,l_tax,l_returnflag,l_linestatus,l_shipdate,l_commitdate,l_receiptdate,l_shipinstruct,l_shipmode,l_comment
 FROM public.lineitem_sf1000) query_alias WHERE l_orderkey < 375000001 or 
l_orderkey is null {code}
I*n the last query, we are trying to get the remaining records, along with any 
data in the table for the partition key having NULL values.*

This hurts performance badly. While the first 15 SQLs took approximately 10 
minutes to execute, the last SQL with the NULL check takes 45 minutes because 
it has to evaluate a second scan(OR clause) of the table for NULL values for 
the partition key.

*Note that I have defined the partition key of the table to be NOT NULL, at the 
database. Therefore, the SQL for the last partition need not have this NULL 
check, Spark SQl should be able to avoid such condition and this Jira is 
intended to fix this behavior.*
{code}
 {code}
 

 



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