In one of my previous blog post i demonstrated that the amount of work needed for IN-MEMORY population/[trickle] re-population in oracle 12.1.0.2.6 is more than we may expect : IN-MEMORY population/[trickle] re-population : How much work ? You may be surprised !
Let’s do a very quick check on how this is now handled in oracle 12.2.0.1/OEL 6/UEK4
This is a reference list grouping some IN-MEMORY post i published.I’ll be updating it whenever I add a new one.
In my last blog post on IN-MEMORY when investigating the amount of work done on behalf of IN-MEMORY population/[trickle] re-population i have done some observation concerning auto I/O slot resize.So here is more detail in a very short post(Sadly no time for a deeper investigation 😦 ).
We all know that IN-Memory is a great new feature, but how much work is done on behalf to maintain the in-memory column store ? You may be surprised !
In this post i will trace the work done by the In-memory background worker processes W0nn during population and trickle re-population .I will be using systemtap and some scripts developed by Luca Canali.So let’s begin !
When investigating how the optimizer calculate the cost of In-memory operation i hit some anomaly. Let’s begin with a big overview of how the cost of in-memory operation is calculated (For more info please check http://www.vldb.org/pvldb/vol8/p1770-das.pdf ). The cost of in-memory operation is based on this new keys statistics which are maintained in real time (as stated by the previous doc and demonstrated by Riyaj Shamsudeen https://t.co/tp0Q1sNZrB for example function “ktmpjUpdInMemExtStat” update In-memory extent statistics in the same session ) :
Oracle in-memory white paper stated that “When a DML statement changes a row in an object that is populated into the IM column store, the corresponding entries for that row is marked stale in the IMCU and a copy of the new version of the row is added to the in-memory transaction journal.”
“When a query with a newer SCN is executed against the object, it will read all of the entries for the columns in the IMCU except the stale entries. The stale entries will be retrieved either from the transaction journal or from the base table (buffer cache).”
UPDATE 30/03/2017 : It’s seem to be a documentation bug the new doc state : “The stale entries will be retrieved from the base table (i.e. row store).”
Lets try some example and observe :
Attribute clustering is a new feature of oracle 12c for more info check http://docs.oracle.com/database/121/DWHSG/attcluster.htm#DWHSG9338.
I will focus here only on how attribute clustering can improve in-memory query.For a description of in-memory pruning please check my previous post.
Here is a quick example to demonstate how Attribute clustering can improve in-memory query pruning and compression ratio. Here is the simple steps :
“The more stale entries in an IMCU,the slower the scan of IMCU will become” (Oracle in-memory white papers)
In fact the stale row will be read from the transaction journal (if it’s there) or from the buffer cache.
The question is how much stale entries do we have ? How to reduce them if required ?
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For other parts : Part1 , Part2
Let’s see a quick example of in-memory pruning using storage index :
In-memory white paper : “A further reduction in the amount of data accessed is possible due to the In-Memory Storage Indexes that are automatically created and maintained on each of the columns in the IM column store. Storage Indexes allow data pruning to occur based on the filter predicates supplied in a SQL statement.An In -Memory Storage Index keeps track of minimum and maximum values for each column in an IMCU.When a query specifies a WHERE clause predicate, the In-Memory Storage Index on the referenced column is examined to determine if any entries with the specified column value exist in each IMCU by comparing the specified value(s) to the minimum and maximum values maintained in the Storage Index. If the column value is outside the minimum and maximum range for an IMCU, the scan of that IMCU is avoided”
Quick example :
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This is the second blog post about the new in-memory feature of oracle database 12c.For the preceding post Part 1
UPDATE 10/11/2014 : Flushing the buffer cache before testing to check for physical reads
In this post i will try to demonstrate how read consistency is maintained in the in-memory column store and determine how much work is done on behalf. Please read the white paper about in-memory before (you can find a link in the bottom of the page).
Let’s begin by creating our testing table and loading it on the in-memory column store :
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