How to Optimize Jobs on the Data Integration Service for Performance and Stability
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1 How to Optimize Jobs on the Data Integration Service for Performance and Stability Informatica LLC. No part of this document may be reproduced or transmitted in any form, by any means (electronic, photocopying, recording or otherwise) without prior consent of Informatica LLC. All other company and product names may be trade names or trademarks of their respective owners and/or copyrighted materials of such owners.
2 Abstract You can optimize the Data Integration Service for performance or stability depending on job type, such as mappings, profiles, or web services, whether the Data Integration Service runs on a grid, and based on the of the nodes. To optimize the Data Integration Service, you can configure the service to run DTM instances in the Data Integration Service process, in a separate DTM process on the local node, or in a separate DTM process on a remote node. Supported Versions Informatica Big Data Management 10.0 Informatica Data Quality 10.0 Informatica Data Services 10.0 Table of Contents Overview Launch Job Options Configuration Determine Where the DTM Instance Can Run DTM Process Pool Management Rules and Guidelines when Jobs Run in Separate Processes Optimize the Logical Data Transformation Manager Overview You can configure the Data Integration Service to run DTM instances in the Data Integration Service process, in a separate DTM process on the local node, or in a separate DTM process on a remote node. A DTM process is an operating system process that the Data Integration Service starts to run DTM instances. Multiple DTM instances can run within the Data Integration Service process or within the same DTM process. Informatica provides recommendations on where the Data Integration Service should run DTM instances based on the following factors: The types of jobs you want to run such as mappings, profiles, or web services Whether the Data Integration Service runs on a single node or on a grid Based on the of the nodes When you configure the recommended option based these factors, you optimize Data Integration Service performance to increase speed or processing or you ensure the stability of the service. For example, you want to run a data quality mapping on a grid where each node has both the service and compute. To increase stability, you can configure the Data Integration Service to run the DTM instances in a separate processes on the local node. 2
3 Launch Job Options Configuration The Launch Job Options property on the Data Integration Service determines where the service starts DTM instances. On the Services and Nodes view of the Manage tab, select a Data Integration Service from the Domain Navigator. Configure the Launch Job Options property in the Execution options in the Properties view. Restart the service for any changes to take effect. The following image shows where you configure the Launch Job Options property on the Data Integration Service: Choose one of the following options for the Launch Job Options property: In the service process. The DTM instances run in the Data Integration Service process. In separate local processes. The DTM instances run in separate DTM processes on the local node. In separate remote processes. The DTM instances run in separate DTM processes on the remote node. 3
4 Determine Where the DTM Instance Can Run Based on the types of jobs you want to run, whether the Data Integration Service runs on a single node or on a grid, and based on the of the nodes, select whether the jobs run in process or out of process. The following table describes jobs types, the configuration of the Data Integration Service, the recommended Launch Job Options value to select, and the advantages of using the recommendation configuration: Job Type Data Integration Service Configuration Launch Job Options Value Advantages - SQL data service - Web service - Single node where each node has both the service and compute In the service process Performance increases when the Data Integration Service runs the jobs in the service process. - Mapping - Profile - Workflow - Single node where each node has both the service and compute In separate local processes Stability increases because an unexpected interruption to one job does not affect all other jobs. - Mapping - Profile - Workflow where nodes have a different combination of In separate remote processes Stability increases because an unexpected interruption to one job does not affect all other jobs. Also, you can better use the resources available on each node in the grid. When a node has the compute role only, the node does not have to run the service process. The machine uses all available processing power to run mappings. Note: Ad hoc jobs, with the exception of profiles, can run in the Data Integration Service process or in separate DTM processes on the local node. Ad hoc jobs include mappings run from the Developer tool or previews, scorecards, or drill downs on profile results run from the Developer tool or Analyst tool. If you configure a Data Integration Service grid to run jobs in separate remote processes, the service runs ad hoc jobs in separate local processes. DTM Process Pool Management When the Data Integration Service runs jobs in separate local or remote processes, the Data Integration Service maintains a pool of reusable DTM processes. The DTM process pool includes DTM processes that are running jobs and DTM processes that are idle. Each running DTM process in the pool is reserved for use by one of the following groups of related jobs: Jobs from the same deployed application Preview jobs Profiling jobs Mapping jobs run from the Developer tool 4
5 For example, if you run two jobs from the same deployed application, two DTM instances are created in the same DTM process. If you run a preview job, the DTM instance is created in a different DTM process. When a DTM process finishes running a job, the process closes the DTM instance. When the DTM process finishes running all jobs, the DTM process is released to the pool as an idle DTM process. An idle DTM process is available to run any type of job. Rules and Guidelines when Jobs Run in Separate Processes Consider the following rules and guidelines when you configure the Data Integration Service to run jobs in separate local or remote processes: You cannot use the Maximum Memory Size property for the Data Integration Service to limit the amount of memory that the service allocates to run jobs. If you set the maximum memory size, the Data Integration Service ignores it. If the Data Integration Service runs on UNIX, the host file on each node with the compute role and on each node with both the service and compute must contain a localhost entry. If the host file does not contain a localhost entry, jobs that run in separate processes fail. Windows does not require a localhost entry in the host file. If you configure connection pooling, each DTM process maintains its own connection pool library. All DTM instances running in the DTM process can use the connection pool library. The number of connection pool libraries depends on the number of running DTM processes. Optimize the Logical Data Transformation Manager You can configure custom properties for the Data Integration Service to optimize the Logical Data Transformation Manager (LDTM). Optimize the LDTM to reduce mapping run time and increase the amount of time the LDTM spends optimizing the mapping. Configure custom properties in the Properties view of the Data Integration Service Properties. To access the Data Integration Service properties, click the service in the Domain Navigator. The Properties view appears. You can change the properties while the service is running, but you must restart the service for the properties to take effect. Configure the following custom properties to optimize the LDTM: Custom Property Name ExecutionContextOptions.Optimizer.MaxMappingPorts ExecutionContextOptions.Optimizer.TimeoutMilliseconds Description The maximum number of ports that a mapping can contain before the Data Integration Service disables optimization. Increase the value for the Data Integration Service to perform optimization on a mapping with a large number of ports. Default is Maximum amount of time in seconds that the Data Integration Service can spend optimizing a mapping. Increase the value to extend the amount of time that the Data Integration Service performs optimization on the mapping. Default is 60. Author Informatica Documentation Team 5
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