Top SQL reports didn't show it because the SQL wasn't having problems on execution, it was during parsing. The rows updated are in 2 different data blocks.
Oracle oradism or the directly intimate shared monster ! Extended stats is a good feature I am using for the first time and I have found success with my testing. Connor and Chris don't just spend all day on AskTOM.
( Log Out / There is others parameters that control staleness of the an IMCU (In-Memory Compression Unity) like : Oracle in-memory white paper state that “The stale entries will be retrieved either from the transaction journal or from the base table (buffer cache).”, I think that i must dig deeper to check when the transaction journal is used because in my case data is read from the buffer cache every time they are stalled. :-) Here it is. ACTLINK_GROUP_IDS has 2 columns and both have normal index. please correct me if my understanding is wrong. TABLE USERS 10616832 13631488 0 COMPLETED NONE AUTO NO DUPLICATE NO MEMCOMPRESS 0 1,28395062, After that i will disable population, repopulation and trickle repopulation to avoid cleaning of stale entry from the in-memory column store by setting this parameter : (there is other way to do this like playing with undocumented parameter to change the thresholds ” _inmemory_repopulate_threshold_rows_percent” ” _inmemory_repopulate_threshold_blocks_percent” etc), Open three sessions : (session 3 is for stats collections using snapper tool thanks to Tanel Poder) I understand that physical I/O is the most expensive component and … Come on, you cant guess the query from the plan?
(the stats collected won’t change) When a block is requested by a query, Oracle looks for it in the Buffer Cache and if found, it results in a Logical read and if it does not find the Block in there it results in a physical read (disk I/O).
SEGMENT_TYPE TABLESPACE_NAME INMEMORY_SIZE BYTES BYTES_NOT_POPULATED POPULATE_ INMEMORY INMEMORY_DISTRI INMEMORY_DUPL INMEMORY_COMPRESS CON_ID COMP_RATIO I have "select count(*) from tab" on instance A and instance B. —————— —————————— ————- ———- ——————- ——— ——– ————— ————- —————– ———- ———- You can also catch regular content via Connor's blog and Chris's blog. (May be it’s only used to speed repopulation) UPDATE 10/04/2015 : For more info check my new blog post https://mahmoudhatem.wordpress.com/2015/04/08/oracle-in-memory-transaction-journal-or-buffer-cache/, Also Oracle in-memory white paper state “The original entries in the IMCU are not immediately replaced in order to provide read consistency and maintain data compression.
Flush the buffer cache and then fill it with random data to avoid prefetching of data.
Thank you so much. Believe me we did search, we did check top SQLs, we did check events and waits before calling Oracle support. When you set the amount of memory that SQL Server will use, you're controlling the size of the available buffer cache. Resolution. Ref: http://jonathanlewis.wordpress.com/2014/08/27/in-memory-consistency. I'm a bit fuzzy on the internals of the fast full index scan, but I think I see what you're saying. For me, it is like watching a traffic accident: I don't want to look, but I can't look away either. In AWR report under "Segments by Logical Reads" section, there is a total logical reads, I assume it is in unit of block. Note the new result cache information provided in the plan output:-----| Id|Operation | Name |Rows |Bytes |Cost (%CPU)|Time | Interestingly, it did't affect all the queries.
Setting it to its previous default value of false fixed those issue. Oracle DbNest : Filtered syscalls by seccomp profiles.
Although I was aware of this but wouldn't have tried it out if you hadn't suggested. I learned one more thing. In this case, the ORDER_HISTORY table contains very static data that will not change often if at all. It actually hurts my head to consider. create table read_consis inmemory no memcompress as select * from dba_objects; hatem@ORCL> select * from v$inmemory_area; alter system set inmemory_max_populate_servers=0; select object_name from read_consis where object_name=’TEST_INMEMORY3′; _inmemory_pct_inv_blocks_invalidate_imcu 100. Scan count 1, logical reads 4461565, physical reads 14682, read-ahead reads 4196628, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. select name,value from v$parameter where isdefault='FALSE'; Yes, that did the trick, but I have frequently found that FIRST_ROWS hinting produces the same plan as the RULE hint!
Any transaction executing against this object in the IM column store that started before the DML occurred, needs to see the original version of the entries” but in my test case although the transaction started before the DML we are not using the stale row (May be i am wrong but this what my test shows), The outcome is other question without answers !!
you said: logical reads = cache buffer reads, and I agree, but this doesn't seem true in AWR report. Seems that the _b_tree_bitmap_plans problem is documented in metalink note 225466.1, and it identifies one of the symptoms as being "Execution plan shows BITMAP CONVERSION". And of course, keep up to date with AskTOM via the official twitter account. When we're talking about reduction in LIO being beneficial, that's when we achieve it through improving the efficiency of the SQL (doing less work), right? Each consistent get is a latch, latches = contention.
The bug is documented on Metalink.
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. Intuitively I would suppose that during the FFIS there is a CPU cost in examining every indexed value in every leaf block to see if it matches the query predicate, whereas the index range scan is more selective in which blocks' entries have to be "examined". This has got to be a rookie question but I'm going to ask it anyway. Regarding logical reads, I've been toying with a query to try to measure the logical read complexity for the queries used at production database (mainly OLTP but also has to support big queries for big reports): When I try to update a record a table, it is going to have a row level lock. Change ), You are commenting using your Facebook account. This was seemingly caused by a bug in the code path, not a change in the execution path.
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. A logical read without a subsequent physical read is a "cache hit," basically. Change ), You are commenting using your Twitter account.
The views expressed on this blog are my own and do not necessarily reflect the views of Oracle Corporation.
physical read IO requests: Number of read requests for application activity (mainly buffer cache and direct load operation) which read one or more database blocks per request. If you have a query that is executed often and reads data that rarely changes, this feature can increase performance significantly.
Unless this is a different bug of course. >> ... what you can draw from that [reduced LIO's due to larger block size] performance wise is that it would technically scale better with more users ... <<, the table structure for ATTRIBUTE_VAL_HEADERS, >>When I was running some (single user) tests on this sort of thing I noted that a. I've taken a guess about what may have been happening, and built a simple example that may be relevant. What are your thoughts on this Tom? Let’s interpret this stats : We have 91612 rows,3 of them are staled and read form the cache into 2 different block(CR blocks created).We have 6 additional physical reads 2 data blocks (of our updated rows),1 undo blocks,1 undo header and some prefetched block (This is only an assumption, i should have used tracing 10046 and 10298 events to check for the correct type of block reads but i didn’t ). I concentrate 100% on reducing LIO's", And yes, I did play around with the optimizer_index_* parameters, all 3 combos of this parameter (10/90, 50/50 and 90/10 did not change the CBO plan), "it can work both ways, depends on sizes of things (buffer cache, how much of the stuff was cached before you started, can it all be cached) as well". Expertise through exercise!
They are bang-on, actually.
logical read bytes from cache , 24576, physical reads , 1, physical reads cache , 1, physical read IO requests , 1, physical read bytes , 8192, ... We have 91612 rows,3 of them are staled and read form the cache into 2 different block(CR blocks created).We have 6 additional physical reads 2 … Can you please confirm. Thanks Tom for explaing about the Full Scans , could you please suggest a better way for the below ? ——————————————————————————————————————————– ——————————————————————– We had the same issue when we moved from 8174 to 9203. Change ), POUG17 : Memory-access-tracing
I have 2 dbms_xplan outputs pasted below, one I consider BAD and second GOOD because of the response times and reads.
( Log Out / The parallel query (direct path read) took only 3 IO's to complete. In the case of a full table scan, the blocks would be placed on the least recently accessed end of the buffer instead of the most recently accessed end, causing them to be flushed out sooner. In your example Nested Loops has more buffer gets than, say, Hash Join. The difference in time taken is very small.
This was because Oracle read the data from the result cache instead of pouring through millions of rows of data. So it seems odd that "using any and all available tests, nothing showed the problem" -- if that was the case then the execution plans would have showed it. Not everything should be in heap organized tables. ( Log Out /
As some here may know, I have been following that thread (very minor contributions on occasion, others are certainly providing more of the technical side) for days now. Well you executed the query 1772 times with about 128 LIOs each time, that doesn't *seem* like many per execution to me, but I'm having to assume that this is a real production system with significantly sized objects since you dont tell us anything about the structure of the objects at all. In the second query the consistent gets are quite high.
If so, it will retrieve those results instead of reading all the blocks and creating the results again. But saying that, we might be loosing on performance of other queries [where it might have a positive impact, I am sure if they changed the default value then there must be some positive intention ;-)].
To utilize result cache at the query level, we can add a hint: Below are three successive executions of this query: Elapsed: 00:00:14.85 consistent gets: 31907 physical reads: 31897 Elapsed: 00:00:00.06 consistent gets: 0 physical reads: 0 Elapsed: 00:00:00.04 consistent gets: 0 physical reads: 0 The first execution of the query populated the result cache, but notice how the 2nd and 3rd execution of the query took no time at all and no logical or physical reads. The statistics are upto date.
It absolutely astounds me how quickly the contradictions come.
POUG18 : The power of linux advanced tracer Let’s begin by creating our testing table and loading it on the in-memory column store : OWNER SEGMENT_NAME Being a frequent reader of your site, that is the first thing I check!
I am trying to research consistent read clone in 10g, is there a way to track this from in-memory v$ views ?