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FAQ: What is the Maximum Native Batch Execution pool size in the DIS execution properties?
Answer
​The maximum number of deployed jobs that can run concurrently in the native environment. The Data Integration Service moves native mapping jobs from the queue to the native job pool when enough resources are available. The default is 10.

The value of this flag is the maximum number of Native mapping jobs (excluding DXT preview jobs, REST, SQL, WS endpoint jobs) that may be in the RUNNING state (including ldtm compilation and ldtm execution) at any one time.

Jobs get into this pool by getting pulled from the queue. Jobs are pulled from the queue when space is available in this pool.

When the Data Integration Service runs on a grid, the maximum number of deployed and on-demand jobs that can run concurrently across the grid are calculated as follows:

        Maximum native batch pool size * Number of running service processes

For example, if a DIS is running on 3 nodes in GRID, with native batch pool size set to 15, at any given point in time, DIS can run 15*3= 45 Native jobs concurrently.

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When you increase the pool size values, the Data Integration Service uses more hardware resources such as CPU, memory, and system I/O. Set these values based on the resources available on the nodes in the grid. Hence, you should increase this value considering the hardware resources available on the Informatica nodes.
The maximum native batch pool size can be set up to a value up to 2* (No of CPU cores -1).

For example: If there is a 4 core CPU node on which DIS is running, Maximum native batch pool size can be set to 6. (Max)  

At any given point in time, DIS can execute 10 deployed mappings and all remaining deployed mappings will go in the queued state.

If the DIS is running on a GRID (of 2 nodes) in the above scenario, DIS can execute (2*6) 12 deployed mappings concurrently.
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More Information
When the number of concurrent jobs exceeds the native and Hadoop execution pool size, the Data Integration Service stops taking jobs from the queue until the number of concurrently running jobs falls below the threshold you configured.


Applies To
Product: Data Engineering Integration(Big Data Management); Data Engineering Quality(Big Data Quality); Data Quality
Problem Type: Configuration
User Type: Administrator
Project Phase: Configure
Product Version:
Database:
Operating System:
Other Software:

Reference

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Last Modified Date:8/11/2020 1:03 AMID:625988
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