r23 - 2015-05-26 - 18:09:05 - StephanieBagotYou are here: TWiki >  Deployment Web > DeploymentTroubleshooting > PerformanceTroubleshooting > WhyDoMyETLsTakeSoLongToRun > LongRunningETLError

Long-running ETLs with error(s)

Authors: GeraldMitchell, StephanieBagot
Build basis: CLM 4.x, 5.x; and supported versions of Insight, RRDI, Requisite Pro, ClearQuest

This situation is to help determine both cause and resolution where ETL (Extract, Transform, Load) processes take significantly longed than expected to run and there is an error present.

Why do my ETLs take so long to run?

This situation is to help discover the possibilities in correcting ETLs in the situation where the ETLs seem to be taking what is considered a longer time than expected to run. This specific topic will cover instances when an error does occur.

Keep in mind that many errors and failures are not fatal: the jobs may run or trigger a different result as a consequence of the failure.

If no error has been found or occurred, navigate to the Long Running ETL without an Error page.

Initial Assessment

After you have completed the Initial Troubleshooting, and the Initial Assessment ETL specific questions, you have identified an error which you have determined to be the root cause of the long running ETL. While typically an error would stop the ETLs from continuing, in some cases, the ETLs will attempt to continue after the error until completion, thus resulting in the ETL running for much longer than expected.

Possible causes and solutions

There is too much data collected by the job

  • Delivery of data into the data warehouse is slow when projects contain more data than can be delivered by the ETL within the time limit imposed by HTTP. The HTTP connection used by the JDBC driver for delivering data can even be interrupted due to HTTP timeout. This can be seen when the JDBC driver records a "java.io.IOException: Premature EOF" exception and some of the ETL builds fail. This may be intermittent due to network conditions, CLM usage, and other environment and system states, as well as the data contents. It is possible to reduce the data delivered by customizing the ETL process to deliver raw data directly to a temporary table and then to separately transform that data into the target table. This requires the creation of a temporary table with the correct privileges, configuring the application server, customizing the ETL process, and executing the ETL job. See the technote 1455870 for an example of Insight and Requisite Pro, though the general principal applies to all applications and data warehousing. The HTTP connection is governed by a timeout default that can be adjusted for the sender and receiver in the HTTP and application server such that no HTTP timeout occurs and there is not JDBC driver interruption.
  • The communication timeout issues may also be related to the LPTA timeout especially if the CLM servers on in an enterprise topology or using proxies. This is most obvious in the application server standard out logs where an error such as
    SECJ0371W: Validation of the LTPA token failed because the token expired
    can be seen. The LPTA may be tweaked in the web and application server settings. For example, in WebSphere Application Server 7.0 or higher has a LTPA Timeout setting that can be accessed the console's Global security > Administrative authentication > LTPA panel. The LTPA Timeout value for forwarded credentials between servers field can be adjusted to 240 or higher to yield better results for RQM. See Technote 1454016 for more information.
  • If there are ETL error logs relating to connection resets or other networking impediments and the database logs show system resource errors, the database may need tuned or start to hit system limitations. As an example, when CLM Reporting Jobs are executed for a very large repository data set (more than 500000 records) on a 32-bit environment, the jobs may fail after a few hours due to limited system resources such as seen in Technote 1503427.

Too many other jobs are running and causing errors or failures

  • There are jobs being run which are not necessary. Jobs that are duplicated or run too often can slow performance. It is best to only run jobs right before they are needed to get the latest information. It is also best to run with deltas when possible.
    • Example: The ANALYZE_TABLE command is already run by the ETL jobs, so it is redundant to have it run twice. The ANALYZE_TABLE command can be disabled through a new parameter in the Data Warehouse connection page named: Automatically update the database statistics. Source: Technote 1590790

Something in the data is causing failure

  • It could be that some numbers were hitting a value threshold and the error threshold has been disabled. If the error limit has not been hit, the job will not fail but the logging will have been impacted and the performance might degrade. With no error threshold, the errors would continue to occur indefinitely. Depending on the impact of the numbers to their usage, these errors may cause a performance degradation.
    • Example: High value numbers (greater than 99,999,999) or numbers with a precision greater than in the repository used to cause issues with the data warehouse. See technote 1551425. If the repository contains high numbers, they can be ignored during the ETL process and not loaded into the data warehouse. This means those numeric values will not be available for the metrics reporting. Disable the error threshold for the ETL jobs. The ETL logs need to be checked thoroughly and periodically to make sure no other types of non-fatal errors are ignored. To enable the error threshold for the Requirements ETL jobs: as a JazzAdmins user access the JTS admin URL, choose "Jazz Team Server - Server Administration" and then the "Advanced Properties" section. Change the "Requirements Job Threshold" property value to from -1 (disabled) to a reasonable number and restart the server.

Something with a job is causing failure

  • The user id the job is using is not allowed
    • Correct user id permissions
      • The user ids need permissions in all applications for which the ETL will touch, including the JTS.
      • Assure that the user ids are assigned the correct licenses.
      • Make sure to assign the data collection user with both the "JazzAdmins" repository permission and the "Data Collector" license.
    • Check for the user id to have the permission appropriate to the project areas used in each connected application.
      • Make sure that the user id does not have special characters in the id, such as - (dash).
      • The user ids spelling and password need to be validated.
      • For example, using a corporate policy for some directory services require that the password expires every 90 days, and that automated ids be named a specific structure related to its purpose. If the directory service administrator audit revealed an irregularity, it is possible the id has been removed, frozen or locked out.
      • Remove the LDAP for the User ID (see Technote 1609143) For the Common ETL job there are sometimes errors that are intermittent that will cause a failure and possibly be missed. When the data collection jobs are run, all jobs succeed except for the Common jobs. Common ETL jobs fail with an error: CRRRE1404E: The user or password is invalid The problem could be due to JTS losing connection to the LDAP server at that time, so that change and configuration management (CCM) is not able to authenticate the LDAP user ID used to run the ETL tasks. If a proxy server is in place, it could be due to a failing connection between CCM and JTS through the proxy server. An internal functional ID can be used to run the ETL Data Collection jobs instead of a real LDAP ID. This will result in not using the LDAP server and save the time in connection and any validations related to the LDAP.
        1. Navigate to jts/admin > Server > Consumers. Create and register a new consumers key. Set the etl_user as the function user.
        2. Navigate to jts/admin > Reports > Datawarehouse Connection. Enter the consumer key and secret for the connection properties. Change the XDC Authentication Type from "Form" to "JTS".
        3. Navigate to jts/admin > Reports > Data Collection Jobs. Enter the newly created Consumer Key and secret. Note that as seen in technote 1591743. changing the authentication type from LDAP to the internal authentication for the Data Collection User results in the Data Collection Jobs possibly having issues; manually reconfigure the Data Collection User in each application.
  • RTC Loop jobs may have unreported failures Technote 1515487 In IBM Rational Insight, running published ETLs against RTC with multiple databases reports job succeeded and the Loop jobs will report success, but the ETL job logs may contain errors errors if a failure occurs with parts of the job.
  • Data collection job variables need to be reviewed and corrected
    • Disabled jobs need to result in a passed
    • Failure to have disabled jobs result in a pass will result in a full load and wipe out the current data, resulting in a long standing full load operation every run, instead of a delta.
    • Example: a XDC for Requisite Pro disables a build node result variable. The disable does not return in a valid response. This resulted in a failure and so caused a full ETL load to occur, for every run. The full run instead of the delta run takes magnitudes more time and also blocks other ETLs dependent on that data to run.
  • Data collection jobs need to be run in a specific order
    • Data collections for older applications (such as Requisite Pro or ClearQuest) are recommended to run before the newer CLM applications (JTS, RQM)
  • ETLs on specific data shouldn't be attempted at the same time.
    • The ETL is data dependent and so should be treated as a queue. Only one ETL should be scheduled at a time.
  • Run a full data collection job to gather all new data from your repository. NOTE: This may take significantly longer than the typical data collection job run (which is only incremental).

Check the integrations with other projects

Sometimes data and jobs that are integrated with other applications can have conflicts with timing, become queued in deadlock, or have other issues. Assure that all of the jobs and data are necessary for the functionality desired and that any custom ETL work has been vetted for timing and logic against the other ETLs.

Insight ETL Hangs

There is a known issue with Insight ETLs hanging on Oracle databases. For more information, see Technote 1638341: ETL hangs when delivering data to an Oracle data warehouse.

Related topics:

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Additional contributors: None

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