OBIEE Introduction By QuontraSolutions
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we offer online IT training with placements, project assistance in different platforms with real time industry consultants to provide quality training for all it professionals, corporate clients and students etc. OBIEE online training by quontrasolutions. we are providing excellent OBIEE training by real-time IT industry experts. Our training methodology is very unique our course content covers all the in-depth critical scenarios. We have completed more than 200+ OBIEE training batches through online training program. Our OBIEE classes covers all the real time scenarios, and its completely on hands-on for each and every session. Course content: • basics of data warehousing concepts • OBIEE concepts and overview • Oracle Business Intelligence (OBIEE) • Using Administration Tool and Creating Repository • Using Answers and Creating Interactive Dashboards • advanced OBIEE concepts Please Visit us for the Demo Classes, we have regular batches and weekend batches. Other Courses we offered: MICROSOFT: ADO .NET, ASP .NET, C# .NET, MSBI, SharePoint, Vb .NET PROGRAMMING: Core Java, Advanced Java, J2EE, Hibernates, Strutus, Java Scripting, Perl Scripting, Shell Scripting, springs, Ruby on Rails Mobile Apps: Android, IOS Training, Cloud Computing, Networking, Unix Admin, Sun Solaris, Testing Tools: Manual Testing, QTP, Selenium Sales force CRM: SalesForce Developer, SalesForce Administrator BUSINESS ANALYST, HADOOP DATABASE: SQL/PL-SQL Digital Marketing: Digital Marketing Indept, Search Engine Optimization, Search Engine Marketing, Social Media Optimization, Email Marketing If you are interested in taking any of the training please contact us: QUONTRA SOLUTIONS 204-226 Imperial Drive, Rayners Lane, Harrow- HA2 7HH. Email: info@quontrasolutions.co.uk Web: http://www.quontrasolutions.co.uk Phone : +44(0) 20 3734 1498 / 99
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OBIEE Introduction By QuontraSolutions
- 1. Performance Testing and OBIEE By Quontra Solutions
- 2. Oracle BI specialist at Morrisons plc Big IT development programme at its early stages implementing OBIEE, OBIA, ORDM, all on Oracle 11g & HP-UX
- 3. A Performance Tuning Methodology OBIEE techie stuff Learn from my mistakes!
- 4. Response times Report ETL batch OLTP transaction System impact Resource usage Scalability
- 5. Check that your system performs Are the users going to be happy? Baseline How fast is fast? ▪ How slow is slow? Validate system design Do it right, first time Capacity planning
- 6. It’s never too late “You’ll never catch all your problems in pre-production testing. That’s why you need a reliable and efficient method for solving the problems that leak through your pre-production testing processes.”
- 7. Because it makes you better at your job “At the very least, your performance test plan will make you a more competent diagnostician (and clearer thinker) when it comes time to fix the performance problems that will inevitably occur during production operation.”
- 8. Quantifying response times System impact User expectations Problem diagnosis Design validation
- 9. Define Measure Analyse Review Implement Timebox! Evaluate design / config options Do it right Don’t “fudge it” Do more testing Redefine test Do more testing
- 10. Define – what are you going to test • Aim of the test • Scope • Assumptions • Specifics • Data, environment, etc Build – how are you going to test it OBIEE specific Define Measure Analyse Review Implement •E.g. : •Check that the system performs •Baseline performance •Prove system capacity •Validate system design
- 11. Define Measure Analyse Review Implement MoFrew coemr cpoomnpeonntse n= tms =o reea csoiemr ptole mx a=n magoere = v maroiareb lperse =c ilsaer g=e mr moraer gefinfi coife nertror
- 12. Database Presentation Services BI Server Report / Dashboard Logical SQL Physical SQL statement(s) Data set(s) Data set Rendered report Excludes App/Web server & presentation services plug-in Define Measure Analyse Review Implement
- 13. Database Presentation Services nqcmd BI Server SQL Client Physical SQL LSQL Physical SQL User & Stopwatch Load Testing tool (eg. LoadRunner, OATS) Define Measure Analyse Review Implement
- 14. Define Measure Analyse Review Implement Usage Tracking or NQQuery.log Test script BI Server Data nqcmd Logical SQL Logical SQL Logical SQL
- 15. Master test script Define Measure Analyse Review Implement Test script BI Server Data nqcmd Logical SQL Test script nqcmd Test script nqcmd Test script nqcmd
- 16. Simulates user interaction – HTTP traffic Powerful, but can be difficult to set up Ajax complicates things Do you really need to use it? Tools Fiddler2 FireBug Reference: My Oracle Support – Doc ID 496417.1 http://rnm1978.wordpress.com/category/loadrunner Define Measure Analyse Review Implement
- 17. Be very clear what the aim of your test is You probably need to define multiple tests Different points on the OBIEE stack to interface Pick the most appropriate one Write everything down! Define Measure Analyse Review Implement
- 18. Define Measure Analyse Review Implement
- 19. Define Measure Analyse Review Implement Database Presentation Services BI Server Apache log Web Server App Server Presentation Services plug-in OAS log Analytics log sawserver.log NQServer.log NQQuery.log systems management Enterprise Manager BI Management Pack Usage Tracking PerfMon (windows only) jConsole etc Presentation services Enterprise Manager ASH, AWR, SQL Monitor Server metrics e.g. : IO, CPU, Memory PerfMon (Windows) Oracle OS Watcher (unix) Enterprise Manager (Oracle)
- 20. Define Measure Analyse Review Implement
- 21. Lots of different ways to measure Build measurement into your test plan Automate where possible ▪ Easier ▪ Less error Define Measure Analyse Review Implement
- 22. Define Measure Analyse Review Implement
- 23. Define Measure Analyse Review Implement
- 27. Define Measure Analyse Review Implement
- 28. Response time 1 1 9 3 2 10 2 1 2 3 1 1 1 2 2 2 3 3 9 10 Average (mean) 3.4 50th percentile (Median) 2 90th percentile 9.1 Define Measure Analyse Review Implement
- 29. Define Measure Analyse Review Implement Dashboard Requests Logical SQL • ORA_HASH(QUERY_TEXT) Physical SQL • SQL IDs Execution plan • Execution plan hash id
- 30. S_NQ_ACCT START_TS ROW_COUNT TOTAL_TIME_SEC NUM_DB_QUERY QUERY_TEXT QUERY_SRC_CD SAW_SRC_PATH SAW_DASHBOARD OBIEE_REPLAY_STATEMENTS qt_ora_hash query_text saw_path dashboard OBIEE_REPLAY_STATS testid testenv qt_ora_hash start_ts response_time row_count db_query_cnt Define Measure Analyse Review Implement
- 31. Define Measure Analyse Review Implement Evaluate design / config options Do it right Don’t “fudge it” Timebox!
- 32. Define Measure Analyse Review Implement Redefine test Continue testing Implement
- 33. Define Measure Analyse Review Implement
- 34. Define Measure Analyse Review Implement
- 35. You won’t get your testing right first time There’s no shame in that Don’t cook the books ▪ Better to redefine your test than invalidate its results Stick to the methodology Don’t move the goalposts Very tempting to pick off the “low-hanging fruit” ▪ If you do, make sure you don’t get indigestion… Timebox Test your implementation!
- 36. Define Measure Analyse Review Implement Evaluate design / config options Do it right Don’t “fudge it” Do more testing Redefine test Do more testing
Notes de l'éditeur
- It’s not too late to put in place a solid performance test methodology around an existing system. If you set up your performance tests now you will have a set of baselines and a full picture of how your system behaves normally Then when it breaks or someone complains you’re already set to deal with it If you don’t, then when you do have problems you have to start from scratch, finding your way through the process. Which is better – at your leisure, or with the proverbial gun of unhappy users held to your head? Performance testing isn’t optional. It’s mandatory. It’s just up to you when you do it. Even if you’re running Exadata or similar and a so confident that you don’t have performance problems and never will – how are you going to capacity plan? Do you know how your system currently behaves in terms of CPU , IO, etc? How many more users can you run? Which is easier, simulate and calculate up front, or wait until it starts creaking?
- Performance Testing requires an extremely thorough understanding of the system. If you do it properly there is no doubt you will come out of it better equipped to support and develop the system further
- Any questions so far?
- This is the methodology we’ve developed It’s a high level view – subsequent slides will give detail
- Any questions?
- Once you’ve defined your test you need to execute it – and measure the results Here’s the ways you should consider measuring the different parts of the stack
- Once you’ve decided how much of the stack you’re going to test, you need to set about designing the test and how you’re going to capture your metrics Performance tests are all about collecting metrics that allow you to make statistically valid and quantifiable conclusions about your system. The primary metric of interest is time. What’s the end-to-end response time, from request to answer, and where’s the time in between spent? If a user complains that a report take five minutes to run but the DBA says they don’t see the query hit the database for the first two, and then it executes in 30 seconds, what’s happened to the other two and a half minutes? Other metrics of interest are the environmental statistics like CPU, memory, and IO, and diagnostic statistics such as the execution plan on the database and lower-level information like buffer gets etc. So – from the top down: [click] Web server, eg. Apache log – first log of the user request coming in App server, eg. OAS Presentation Serivces plugin, Analytics – (this is where you see the error logs when you get 500 Internal Server Error from analytics) [click] sawserver.log - by default this doesn’t record that much, but by changing the logconfig.xml file you can enable extremely detailed logging. This is useful for diagnosing lots of problems, but also if you’re looking to do an accurate profile of where the time in an Answers request is spent. You can see when it receives the user request, when it sends on the logical SQL to the bI Server, and when it receives the data back See http://rnm1978.wordpress.com/category/log/ for details [click] BI Server – spoilt for choice here. For a production environment I strongly recommend enabling Usage Tracking. For performance work you should also be using NQQuery.log where the variable levels of logging show you logical and physical SQL, BI Server execution plans, response times for each database query run, etc. [click] As well as these two features there is the systemsmanagement functionality which exposes some very detailed counters through windows PerfMon or the BI Management Pack for OEM. You can also use the jmx protocol to access the data through clients like Jconsole or jManage [click] For the database all the standard monitoring practices apply, depending on what your database is. For Oracle you should be using OEM, ASH, SQL Monitor, etc. [click] And finally, for getting a complete picture of the stack’s performance -- Speak to your users! Maybe not as empirically valid as the other components, but just as important.
- Useful when prob is suspected on DB, only place that individual physical SQL query response times are kept Database query times & row counts
- EM is good For pure testing – need to capture data : SQL Tuning Sets Good for capturing behaviour of a set of SQL over time – longest running, most IO, etc Less good for focussing on individual queries because stats are aggregated SQL Monitor – export from EM (next slide) +++++++++++++++++++++++++++++++++++ SQL Server DMVs, SQL Profiler, PerfMon counters, etc Other RDBMS – pass
- Got to mention this – from EM you can export a standalone HTML file that renders like this brilliant
- Lots of different ways to measure decide what metrics are relevant to your testing Load testing – system metrics v. Important Perf testing indiv report – maybe just response time Plan your measurements as part of the test Trigger collection scripts automagically Include manual collection in test instructions
- Analysis step is : Collate data store in sensible way - Raw data - label your tests better to use a non-meaningful label analyse it - visualisation - analysis will depend on aim of test - eg loadtesting – identify bottlenecks
- [click] raw data, [click] compared to a previous baseline – illustrate varience [click] host metrics - IO graph [click] response time, over time
- Testing – understand more about system as you go – prob want to redefine test – that’s part of the process! Performance Testing is an iterative process. I can’t stress this enough. You will not get it right the first time you do it Whatever you do, you’ll probably miss something or invalidate your tests. Remember that an iterative approach is entirely valid, don’t feel you “got it wrong” and have to fudge the results to cover your mistake. Better to abandon a test and learn from the mistake than produce a “perfect” test that’s complete rubbish. Stick to method Benefit of also enforces justification for changes, avoid “we’ve always done it that way” don’t move the goalposts. You might find some horrible queries as you dig into them you notice some obvious “quick wins” If you rush the fix in without completing your first round of testing, you risk invalidating it BE METHODICAL!!!! Timebox the execute/measure/analyse iterations -don’t get lost in diminishing returns It’s a good idea to timebox your work, and have regular review points Test your implementation! parallel config, not tested properly after implement in test env, nearly got to prod without realising Don’t get so bogged down in the detail that you miss the wood for the trees You can end up focussing on perfecting one element of the system at the expense of all the others.
- This presentation has shown you how to run big workloads against your OBIEE system But, resist the temptation to dash off and see what happens when you run a thousand users against your system at once. It’ll be fun, but ultimately a waste of time. You have to define what you’re going to do. You need to define what the ultimate aim is. Are you proving a system performs to specific user requirements? In which case your test definition is almost written for you, you just have to fill in the gaps If you’re building a performance test for best-practice and all the good reasons I spoke about before then you need to think carefully about what you’ll test. What’s a representative sample of the system’s workload? For example: - Analyse existing usage, pick the most frequently run reports SPEAK TO YOUR USERS! Which reports do they care about? Be wary of only analysing the reports that users complain about though – you want to be colleting lots and lots of good metrics. What happens when you fix the slow reports – the old “fast” reports will now appear slow in comparison, so you want to have some baselines for them too I can’t stress this strongly enough. Cary Millsap writes excellently on the whole subject of performance. I can’t recommend highly enough his paper “Thinking Clearly About Performance”, as well as many of the articles on his blog. http://carymillsap.blogspot.com/2010/02/thinking-clearly-about-performance.html There are books and books written on how you should approach performance testing and tuning, people like Mr Millsap have built their whole careers around it. It’s way outside the scope of this, but I believe it’s essential to understand the approach to follow, otherwise all your testing can be in vain. It’s not the same as dashing off an OBIEE report that you can bin and recreate next week. Imagine designing your DW schema without good modelling knowledge – or think of ones that you’ve worked with where the person who created it didn’t understand what they were doing. The wasted time and misleading results can be potentially disastrous if you don’t get it right up front. Take my word for it – time invested up front reading and understanding will repay itself ten-fold. Preaching over.
- Questions & Discussion