Abstract: A computer detects initialization of a first messaging session. The computer receives one or more message commands relating to one or more messages. The computer monitors message progress of the first messaging session. The computer detects errors in the message progress. The computer starts one or more additional messaging session(s). The computer monitors message progress of the first messaging session and the one or more additional messaging session(s). The computer detects contraction of messaging sessions is appropriate. The computer closes one or more messaging sessions.

Abstract: A method for testing an extract, transform, load job (ETL job) is provided. The method may include receiving an uploaded ETL job. The method may also include executing a functionality test of the uploaded ETL job using a test bucket. The method may further include determining the executed functionality test produces a failure result. The method may also include creating at least one test sub-job corresponding to at least one stage within on the uploaded ETL job. The method may further include generating a plurality of test data for each of the at least one created test sub-job. The method may also include executing the at least one created test sub-job using the plurality of generated test data. The method may further include creating a report based on a plurality of results associated with the at least one executed test sub-job.

Abstract: Compiling test cases. The method may include uploading at least one extract, transform, load job (ETL job) and a plurality of test cases. The method may also include identifying a plurality of design features associated with the at least one uploaded ETL job. The method may further include identifying at least one feature change within the plurality of identified design features. The method may also include determining a plurality of related test cases within the plurality of uploaded test cases corresponding to the at least one identified feature change. The method may further include creating a test bucket based on a grouping of the determined plurality of related test cases. The method may also include adding at least one of a plurality of corresponding ETL jobs and a plurality of corresponding ETL job stages associated with the at least one identified feature change to the created test bucket.

Abstract: A method for testing an extract, transform, load job (ETL job) is provided. The method may include receiving an uploaded ETL job. The method may also include executing a functionality test of the uploaded ETL job using a test bucket. The method may further include determining the executed functionality test produces a failure result. The method may also include creating at least one test sub-job corresponding to at least one stage within on the uploaded ETL job. The method may further include generating a plurality of test data for each of the at least one created test sub-job. The method may also include executing the at least one created test sub-job using the plurality of generated test data. The method may further include creating a report based on a plurality of results associated with the at least one executed test sub-job.

Abstract: A computer detects initialization of a first messaging session. The computer receives one or more message commands relating to one or more messages. The computer monitors message progress of the first messaging session. The computer detects errors in the message progress. The computer starts one or more additional messaging session(s). The computer monitors message progress of the first messaging session and the one or more additional messaging session(s). The computer detects contraction of messaging sessions is appropriate. The computer closes one or more messaging sessions.

Abstract: Compiling test cases. The method may include uploading at least one extract, transform, load job (ETL job) and a plurality of test cases. The method may also include identifying a plurality of design features associated with the at least one uploaded ETL job. The method may further include identifying at least one feature change within the plurality of identified design features. The method may also include determining a plurality of related test cases within the plurality of uploaded test cases corresponding to the at least one identified feature change. The method may further include creating a test bucket based on a grouping of the determined plurality of related test cases. The method may also include adding at least one of a plurality of corresponding ETL jobs and a plurality of corresponding ETL job stages associated with the at least one identified feature change to the created test bucket.

Abstract: A method for testing an extract, transform, load job (ETL job) is provided. The method may include receiving an uploaded ETL job. The method may also include executing a functionality test of the uploaded ETL job using a test bucket. The method may further include determining the executed functionality test produces a failure result. The method may also include creating at least one test sub-job corresponding to at least one stage within on the uploaded ETL job. The method may further include generating a plurality of test data for each of the at least one created test sub-job. The method may also include executing the at least one created test sub-job using the plurality of generated test data. The method may further include creating a report based on a plurality of results associated with the at least one executed test sub-job.

Abstract: Handling extract-transform-load (ETL) job mismatches as “exceptions.” Exception handling may include the following steps: (i) determining a mismatch while running an extract-transform-load job with the mismatch being a mismatch of at least one of the following types: design time information mismatch, and/or operational metadata mismatch; and (ii) responsive to determining the mismatch, handling the mismatch as an exception.

Abstract: A method for testing an extract, transform, load job (ETL job) is provided. The method may include receiving an uploaded ETL job. The method may also include executing a functionality test of the uploaded ETL job using a test bucket. The method may further include determining the executed functionality test produces a failure result. The method may also include creating at least one test sub-job corresponding to at least one stage within on the uploaded ETL job. The method may further include generating a plurality of test data for each of the at least one created test sub-job. The method may also include executing the at least one created test sub-job using the plurality of generated test data. The method may further include creating a report based on a plurality of results associated with the at least one executed test sub-job.

Abstract: Compiling test cases. The method may include uploading at least one extract, transform, load job (ETL job) and a plurality of test cases. The method may also include identifying a plurality of design features associated with the at least one uploaded ETL job. The method may further include identifying at least one feature change within the plurality of identified design features. The method may also include determining a plurality of related test cases within the plurality of uploaded test cases corresponding to the at least one identified feature change. The method may further include creating a test bucket based on a grouping of the determined plurality of related test cases. The method may also include adding at least one of a plurality of corresponding ETL jobs and a plurality of corresponding ETL job stages associated with the at least one identified feature change to the created test bucket.

Abstract: Compiling test cases. The method may include uploading at least one extract, transform, load job (ETL job) and a plurality of test cases. The method may also include identifying a plurality of design features associated with the at least one uploaded ETL job. The method may further include identifying at least one feature change within the plurality of identified design features. The method may also include determining a plurality of related test cases within the plurality of uploaded test cases corresponding to the at least one identified feature change. The method may further include creating a test bucket based on a grouping of the determined plurality of related test cases. The method may also include adding at least one of a plurality of corresponding ETL jobs and a plurality of corresponding ETL job stages associated with the at least one identified feature change to the created test bucket.

Abstract: Insertion, in a data warehouse process, of a buffer operator between an upstream data operator and a downstream data operator. The processor processes a data record for the upstream data operator to pass to the downstream data operator. In response to determining that the downstream data operator is not ready to accept the data record from the upstream data operator, a buffer operator is inserted between the upstream data operator and the downstream data operator. The data record processed by the upstream data operator is passed to the buffer operator for storing into a buffer allocated for use by the buffer operator. The data record stored into the buffer is passed to the downstream data operator when the downstream data operator is ready to accept data. In another aspect, when the allocated buffer utilization decreases to a threshold value, the buffer operator is removed and the buffers are released.

Abstract: A method for testing an extract, transform, load job (ETL job) is provided. The method may include receiving an uploaded ETL job. The method may also include executing a functionality test of the uploaded ETL job using a test bucket. The method may further include determining the executed functionality test produces a failure result. The method may also include creating at least one test sub-job corresponding to at least one stage within on the uploaded ETL job. The method may further include generating a plurality of test data for each of the at least one created test sub-job. The method may also include executing the at least one created test sub-job using the plurality of generated test data. The method may further include creating a report based on a plurality of results associated with the at least one executed test sub-job.

Abstract: Compiling test cases. The method may include uploading at least one extract, transform, load job (ETL job) and a plurality of test cases. The method may also include identifying a plurality of design features associated with the at least one uploaded ETL job. The method may further include identifying at least one feature change within the plurality of identified design features. The method may also include determining a plurality of related test cases within the plurality of uploaded test cases corresponding to the at least one identified feature change. The method may further include creating a test bucket based on a grouping of the determined plurality of related test cases. The method may also include adding at least one of a plurality of corresponding ETL jobs and a plurality of corresponding ETL job stages associated with the at least one identified feature change to the created test bucket.

Abstract: Compiling test cases. The method may include uploading at least one extract, transform, load job (ETL job) and a plurality of test cases. The method may also include identifying a plurality of design features associated with the at least one uploaded ETL job. The method may further include identifying at least one feature change within the plurality of identified design features. The method may also include determining a plurality of related test cases within the plurality of uploaded test cases corresponding to the at least one identified feature change. The method may further include creating a test bucket based on a grouping of the determined plurality of related test cases. The method may also include adding at least one of a plurality of corresponding ETL jobs and a plurality of corresponding ETL job stages associated with the at least one identified feature change to the created test bucket.

Abstract: A method for testing an extract, transform, load job (ETL job) is provided. The method may include receiving an uploaded ETL job. The method may also include executing a functionality test of the uploaded ETL job using a test bucket. The method may further include determining the executed functionality test produces a failure result. The method may also include creating at least one test sub-job corresponding to at least one stage within on the uploaded ETL job. The method may further include generating a plurality of test data for each of the at least one created test sub-job. The method may also include executing the at least one created test sub-job using the plurality of generated test data. The method may further include creating a report based on a plurality of results associated with the at least one executed test sub-job.

Abstract: Handling extract-transform-load (ETL) job mismatches as “exceptions.” Exception handling may include the following steps: (i) determining a mismatch while running an extract-transform-load job with the mismatch being a mismatch of at least one of the following types: design time information mismatch, and/or operational metadata mismatch; and (ii) responsive to determining the mismatch, handling the mismatch as an exception.

Abstract: Handling extract-transform-load (ETL) job mismatches as “exceptions.” Exception handling may include the following steps: (i) determining a mismatch while running an extract-transform-load job with the mismatch being a mismatch of at least one of the following types: design time information mismatch, and/or operational metadata mismatch; and (ii) responsive to determining the mismatch, handling the mismatch as an exception.

Abstract: In an approach to identifying duplicates in data, one or more computer processors receive a request from a user to identify duplicates in a data set. The one or more computer processors retrieve the data set utilizing data discovery. The one or more computer processors perform data profiling on the data set. The one or more computer processors determine one or more domain types of the data set, based, at least in part, on the performed data profiling. The one or more computer processors perform data standardization on the data set, based, at least in part, on the one or more determined domain types. Responsive to performing data standardization, the one or more computer processors perform probabilistic matching on the data set. The one or more computer processors to identify two or more duplicates in the data set, based, at least in part, on the probabilistic matching.

Abstract: Methods for resolving a number of in-memory issues associated with parallel query execution of a database operation on a database utilizing a graphics processing unit (GPU) are presented including: tying a table choice to a number of accesses per second made to a table; and synchronizing threads in a same shared GPU multiprocessor to avoid compromising concurrency, and where the parallel query execution of the database operation is performed solely by the GPU. In some embodiments, methods further include storing data from the GPU to a disk to solve volatility; and enabling a user, at any time, to query the amount of memory being used by the table created by the user to monitor memory consumption.