Bank of America Corporation

Dirk E Anderson

Haresh Kurani

Vimal Vijayasekaran

Vijayakumar Gurusamy Raju

Aspects described herein relate to methods and systems for comparing data stored in disparate parallel systems using hash sums. A database having a parallel system architecture may comprise a plurality of nodes each storing a plurality of records. A central node may initiate parallel calculation of a set of node hash sums for each individual node. Calculating a node hash sum for an individual node may comprise calculating, by the individual node, a set of hash values for each individual record of the plurality of records stored by the individual node and combining each hash value of the set of hash values to generate the node hash sum for the individual node. The central processor may combine each node hash sum to generate a database hash sum. The central processor may store the generated database hash sum and/or utilize it in comparisons with database hash sums for other databases.

Comparing data stores using hash sums on disparate parallel systems

According to an embodiment, an apparatus including a memory and a processor is provided. The memory may store a plurality of conversion rules. The processor may receive a first script and determine a first type associated with the first script, a plurality of variables included in the first script, and a first layout associated with the first script. The processor may determine that at least one conversion rule of the plurality of conversion rules should be applied. The processor may determine a second type, a second variable, and a second layout. The processor may generate a second script associated with the second type and the second layout, the second script comprising the second variable, the second script executable against a database comprising a plurality of database processors.

Script converter

Apparatus and methods for determination of unacceptable skew for query in a massively parallel processing system. The apparatus and methods may use data associated with processing the query that has been stored in computer logs. The processing data may be used to determine the actual level of skew for the query. The apparatus and methods may calculate an acceptable level of skew. If the actual skew exceeds the acceptable skew, the query may be considered unacceptably skewed and may be flagged for tuning.

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St. Augustine, FL, United States of America

Dirk E Anderson