![]() Having the index defined on the key will allow the job to run much faster as compared to non indexed keys. Index Database Table columns - When updating the data in a Table through Talend Job, it is recommended to index the database table columns on the same fields which is defined as Key in the Talend Database output component. Visit the article “ Difference between Dom4J and SAX parser in Talend”, for detailed difference between Dom4J and SAX parser.ġ0. Visit the article “ Handling Huge XML files in Talend”, for demonstration of performance optimization of SAX parser. But if your requirement is getting accomplished using SAX parser, you must prefer it over Dom4J. we can only basic XPATH expression and can not use expressions like Last, array selection of data etc. However SAX parser comes with few downsides e.g. Use SAX parser over Dom4J whenever required - When parsing Huge XML files try using the SAX parser in the Generation mode in the Advanced Settings of tFileInputXML component. For more details on ELT components click here.ĩ. So if the database tables are indexed properly and data is huge then ELT method can provide to be much better option in terms of performance of the Job. However, it will Talend will automatically create Insert/Select statements which will directly run on DB server. Benefit of using ELT component is that It will not unload the data from database tables into Job flow for performing the transformations. performing a join between the data in different table in same database. There are couple of scenarios where we can use ELT components e.g. Use Talend ELT Components when required- ETL components are very handy and helps to optimize performance of the job when we need to perform transformation on data within a single database. Visit the article “ Parallel Execution Sub Jobs in Talend Open Studio” for more details and demonstration of Parallel execution of Sub Jobs in Talend Open Studio.Ĩ. You can enable this option from Job view. However, this option is disabled by default. This option is also available in Talend Open Studio. ![]() Running SubJobs in Parallel by using the Multithreaded Executions.(only available in Talend Integration Suite) Using the tParallelize component of Talend.You can achieve the parallelization in following two ways: Talend will execute one of the sub job(randomly) and when one is finished then it start execution of the second subjob. If we have a Job which loads two different tables from two different files and there is no dependency between both loads then Talend will not automatically execute the Jobs in parallel. Extensively used Talend components like tfileinputdelimited, tparquetinput, tspakrow,tSetGlobalVar tMap, tReplicate, tJoin, tFileList, tSortRow, tBufferInput, tBufferOutput, tDenormalize, tNormalize, tParseRecordSet, tUniqueRow, tS3put, tS3get, tS3FileList, tRedshiftInput, tRedshiftOutput, tRedshiftRow, tsnowflakeinput, tsnowflakeoutput, tsnowfl. However, Talend doesn’t automatically execute the subjobs in Parallel. Parallelism -Most of the time we need to run few jobs/sub jobs in parallel to maximize the performance and reduce overall job execution time.
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