HowToInstallObiee11GClientOnWindows7This is the fourth and final part of a series of blogs showing how to perform a standard single serverinstance installation of OBIEE 12c. Oracle BI 11g OBIEE installation on windows Oracle database 11g installation on windows RCU installation on windows. N0lp_ZQi1U/T_smFpf_JGI/AAAAAAAABl8/7WpKyQK9Jlk/s1600/6.jpg' alt='How To Install Obiee 11G Client On Windows 7' title='How To Install Obiee 11G Client On Windows 7' />IT Training. Amazon Cloud AWS Developer Training. AWSDEV Developing on AWS Solutions Architect Training. AWSA Architecting on AWS AWSAC Architecting on. Introduction. OBIEE provides Usage Tracking as part of the core product functionality. It writes directly to a database table every Logical Query that hits the BI. This Blog is personal and independent. It does not reflect the position or policy of Oracle. It is my external memory, that helps me remember solutions I. Complete Technical Acronyms, Glossary Definitions for PC, SAN, NAS, QA, Testing, HDTV, Wireless, Linux, Embedded, Networks, Video, Digital, pharma, Unix, Video. JjpxzRlsv00/0.jpg' alt='How To Install Obiee 11G Client On Windows 7' title='How To Install Obiee 11G Client On Windows 7' />USAGE TRACKING OBIEE. The OBIEE BI Server cache can be one of the most effective ways of improving response times of OBIEE dashboards. By using data already in the cache it reduces load on the database, the network, and the BI Server. Should you be using it I always describe it as the icing on the cake its not a fix for a badly designed OBIEE system, but it does make a lot of sense to use once youre happy that the foundations for the system are in place. If the foundations are not not in placeThen youre just papering over the cracks and at some point its probably going to come back to bite you. As Mark Rittman put it nearly seven years ago, its usually the last desperate throw of the dice. The phrase technical debt Yeh, that. But, BI Server caching used after performance review and optimisation rather than instead of then its a Good Thing. So youve decided to use the BI Server cache, and merrily trotted over to Enterprise Manager to enable it, restarted the BI Server, and now your work is done, right Not quite. Because the BI Server cache will start to store data from all the queries that you run, and use it to satisfy subsequent queries. Not only will it match on a direct hit for the same query, it will use a subset of an existing cache entry where appropriate, and can even aggregate up from whats in the cache to satisfy a query at a higher level. Clever stuff. But, what happens when you load new data into your data warehouse Well, the BI Server continues to serve requests out of the cache, because why shouldnt it And herein lies the problem with just turn caching on. Uiwebview Local Html Javascript File. You have to have a cache management strategy. A cache management strategy sounds grand doesnt it But it boils down to two things Accuracy Flush any data from the cache that is now stale. Speed Prime the cache so that as many queries get a hit on it, first time. Maintaining an Accurate Cache. Katt Williams Pimp Chronicles Full. Every query that is run through the BI Server, whether from a Dashboard, Answers, or more funky routes such as custom ODBC clients or JDBC, will end up in cache. Its possible to seed primewarmup the cache explicitly, and this is discussed later. The only time you wont see data in the cache is if a you have BI Server caching disabled, or b youve disabled the Cacheable option for a physical table that is involved in providing the data for the query being run. You can see metadata for the current contents of the cache in the Administration Tool when connected online to the BI Server, through the Manage Cache menu option. This gives you lots of useful information particularly when you come to optimising cache usage including the size of each entry, when it was created, when it was last used, and so on. Purging Options. So weve a spread of queries run that hit various dimension and fact tables and created lots of cache entries. Now weve loaded data into our underlying database, so we need to make sure that the next time a user runs an OBIEE query that uses the new data they can see it. Otherwise we commit the cardinal sin of any analytical system and show the user incorrect data which is a Bad Thing. It may be fast, but its WRONG. We can purge the whole cache, but thats a pretty brutal approach. The cache is persisted to disk and can hold lots of data stretching back months to blitz all of that just because one table has some new data is overkill. A more targetted approach is to purge by physical database, physical table, or even logical query. When would you use these Purge entire cache the nuclear option, but also the simplest. If your data model is small and a large proportion of the underlying physical tables may have changed data, then go for this. Purge by Physical Database less brutal that clearing the whole cache, if you have various data sources that are loaded at different points in the batch schedule then targetting a particular physical database makes sense. Purge by Physical Table if many tables within your database have remained unchanged, whilst a large proportion of particlar tables have changed or its a small table then this is a sensible option to run for each affected table. Purge by Query If you add a few thousand rows to a billion row fact table, purging all references to that table from the cache would be a waste. Imagine you have a table with sales by day. You load new sales figures daily, so purging the cache by query for recent data is obviously necessary, but data from previous weeks and months may well remain untouched so it makes sense to leave queries against those in the cache. The specifics of this choice are down to you and your ETL process and business rules inherent in the data maybe there shouldnt be old data loaded, but what happens if there is See above re. This option is the most complex to maintain because you risk leaving behind in the cache data that may be stale but doesnt match the precise set of queries that you purge against. Which one is correct depends onyour data load and how many tables youve changedyour level of reliance on the cache can you afford low cache hit ratio until it warms up againtime to reseed new content. If you are heavily dependant on the cache and have large amounts of data in it, you are probably going to need to invest time in a precise and potentially complex cache purge strategy. Conversely if you use caching as the icing on the cake andor its quick to seed new content then the simplest option is to purge the entire cache. Simple is good OBIEE has enough moving parts without adding to its complexity unnecessarily. Note that OBIEE itself will perform cache purges in some situations including if a dynamic repository variable used by a Business Model e. Logical Column gets a new value through a scheduled initialisation block. Performing the Purge. There are several ways in which we can purge the cache. First Ill discuss the ones that I would not recommend except for manual testing Administration Tool Manage Cache Purge. Doing this every time your ETL runs is not a sensible idea unless you enjoy watching paint dry or need to manually purge it as part of a deployment of a new RPD etc. In the Physical table, setting Cache persistence time. Why not Because this time period starts from when the data was loaded into the cache, notwhen the data was loaded into your database. An easy mistake to make would be to think that with a daily ETL run, setting the Cache persistence time to 1 day might be a good idea. Its not, because if your ETL runs at 0. Even if you use cache seeding, youre still relinquishing control of the data accuracy in your cache. What happens if the ETL batch overruns or underruns The only scenario in which I would use this option is if I was querying directly against a transactional system and wanted to minimise the number of hits OBIEE made against it the trade off being users would deliberately be seeing stale data but sometimes this is an acceptable compromise, so long as its made clear in the presentation of the data. So the two viable options for cache purging are BI Server Cache Purge Procedures. Event Polling Table. BI Server Cache Purge Procedures. These are often called ODBC Procedures but technically ODBC is just one of several ways that the commands can be sent to the BI Server to invoke.