Oracle International Corporation

Madhuri Kandepi

Srikanth Bellamkonda

Andrew Witkowski

Yi Pan

Manish Pratap Singh

Shuo Chen

Yash Shah

Skew handling techniques are provided in parallel execution for even load balancing and scaling. In a compile-time solution, a dynamic sampling query is issued to detect partition skew. The compile-time solution determines the number of skewed partitions and uses a hybrid distribution scheme where skewed partitions use a random distribution and non-skewed partitions use the original server mapping. In a runtime solution, producer server processes create partition mapping vectors that contain partition mapping information. Each producer server process sends its partition mapping vector to the query coordinator (QC). The QC receives the partition mapping vectors from the producer server processes, merges the vectors, and determines a skew result based on the merged mapping vectors and sends the skew result to the producer server processes. The producer server process can alter distribution of skewed partitions based on the skew result.

Handling data skew for parallel execution with server mapping plans

An approach for implementing function semantic based partition-wise SQL execution and partition pruning in a data processing system is provided. The system receives a query directed to a range-partitioned table and determines if operation key(s) of the query include(s) function(s) over the table partitioning key(s). If so, the system obtains a set of values corresponding to each partition by evaluating the function(s) on a low bound and/or a high bound table partitioning key value corresponding to the partition. The system may then compare the sets of values corresponding to different partitions and determine whether to aggregate results obtained by executing the query over the partitions based on the comparison. The system may also determine whether to prune any partitions from processing based on a set of correlations between the set of values for each partition and predicate(s) of the query including function(s) over the table partitioning key(s).

Function semantic based partition-wise SQL execution and partition pruning

According to embodiments, a multi-node database management system allows consumer processes ('consumers') implementing a portion of a distributed data-combination operation to independently send a STOP notification to corresponding producer processes ('producers'). Upon a given consumer determining that the consumer requires no further information from corresponding producers, the consumer sends a STOP notification to the producers. When a given consumer sends out a STOP notification, the producers drop any data destined for the given consumer and also stops preparing data for and sending rows to the given consumer. Furthermore, once the producers receive STOP notifications from all of the consumers corresponding to the producers, the producers stop the current sub plan execution immediately without requiring completion of the sub plan. Thus, embodiments significantly improve the query execution performance by avoiding scanning and distributing data that is not needed for execution of the distributed operation.

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Cupertino, CA, United States of America

Madhuri Kandepi