Understanding Informatica Profiling and PWH Purge Issues
This video discusses profiling and purge issues in Informatica, covering architecture, execution, and configuration. It provides tips for improving performance and diagnosing problems.
00:00:00 This video discusses the profiling and purge issues in Informatica, including the overview, architecture, execution, and configuration of profiling. It explains the purpose of profiling data and the modules involved.
📚 Profiling helps us understand the strengths and weaknesses of our data in a data warehouse.
🏢 The profiling architecture consists of four modules: analyst service, developer tool, data integration service, and profile warehouse.
🔍 Execution of profile definitions involves reading from the source, executing the profile, and storing the results in the profile warehouse database.
00:02:52 This video discusses the issues with profiling and PWH purge, including the process of creating a profile warehouse and setting properties. It also mentions how to execute profiles and view the results.
🔍 Profiling in data integration service requires enabling the profiling model and creating a profile warehouse with metadata tables.
⚙️ Different database properties and advanced profiling properties can be configured to meet specific requirements, such as the maximum concurrent profile jobs.
📊 After executing a profile, the results can be observed in the profiling console or client, with options for drill down analysis.
00:05:43 This video provides an overview of profiling and PWH purge issues. It covers stats, column rules, row counts, non-distinct values, patterns, drill down options, and duplicate records.
📊 The overview page shows stats like the number of profile runs, columns in the table, and applied rules.
🔍 The profile execution provides details about non-distinct values, value frequency, patterns, null percentage, and data types.
🔎 Drill down option allows viewing specific column data, checking for duplicates, and analyzing record types.
00:08:36 This video discusses the issues with profiling and purging in the profile warehouse, and recommends avoiding direct truncation of tables.
⚙️ Performing drill down on stage mode connects to the source database, extracts results, and displays them.
💾 Stage data option can affect performance on profile warehouse operations, recommended for complex or mainframe sources.
🏛️ Maintaining profile warehouse is crucial to prevent data growth and degradation of performance.
🔒 Purging profile warehouse content is recommended using 'purge' command to maintain consistency and prevent failures.
00:11:28 A video discussing the issues and solutions for profiling and purging the profile warehouse. It recommends regular purging every 15-30 days and provides tips for improving performance.
🔍 Profiling and PWH purge is recommended to avoid inconsistency and ensure accurate results.
📆 The recommended frequency for performing the purge is every 15 to 30 days based on historical data needs.
💽 Database optimizations, such as adding an index and adjusting database properties, can significantly improve purge performance.
00:14:19 This video discusses issues related to purging in a database, including lack of activity, slow performance, and excessive growth. It also provides recommendations for maintaining the profile warehouse to facilitate purge activities.
🔍 The video discusses issues with purging data from a profile warehouse database, including slow performance and lack of activity during purging.
📚 To address these issues, the video recommends collecting logs and performing DB tracing to identify delayed and intensive queries. It also suggests maintaining regular purge activity to prevent excessive growth in the profile warehouse database.
💡 By implementing these recommendations, the purge process can be optimized and the profile warehouse can be effectively managed.
00:17:11 This video discusses issues with table profiling and PWH purge, including performance and hang problems. It suggests collecting more logging and verifying delete queries on the profile warehouse to diagnose the issue.
Identifying tables that are being written to frequently to optimize performance.
Investigating the hang scenario during profile fetching to determine the cause.
Using additional logging and DBA assistance to diagnose performance or hang issues.
Want to deep dive into this video?
