İ am trying to understand the mysql architecture and I came acrosa two notions.
The first one is query cache, which I understood that it stores the queries that were run at least once, and if the query processor sees the query cached there, it no longer goes to the parser and takes the results directly to the cache.
But then, there is also the buffer pool, part of the Storage Engine buffer manager, which kinda does the same thing from my understanding.
So my question would be, if there is a cache in the logical layer, why do we need one in the physical layer also? İ am thinking that if a query is found in the query cache it will never be searched in the buffer pool, and if the query is not found in cache, then it will never be also retreived from the buffer pool. Am I missing something?
For query cache, you got it spot on. Its based on the raw text of the query mapping to the exact query results. It has major scaling problems which is why MySQL-8.0 removed it.
innodb buffer pool, is a storage of the low level data and index pages of the database. It ensures that all the recently used data is off disk and able to be queried without resorting to the much slower (by comparison to ram) storage.
So buffer pools serve all queries on the same data, while query caches only serve a particular query (at a large scaleability cost).
Adding some context to #danblack's answer, query cache stores the query and actual data associated with the query. But in buffer pool which we call as innodb_buffer_pool stores the physical (01,10) or low-level data or say pages. Whenever query executes it checks in the buffer pool and if required data is not present then it will proceed towards the disk (i.e. your secondary storage) and puts data in the buffer pool.
With query cache, there is a disadvantage of invalidating query cache if query cache size being set quite high without analyzing the situations. By "invalidating query cache" I mean marking the data or entry in query cache as invalid because the underlying table has been changed by DML statements. I have personally experienced many times for example under "show processlist" when replication is stuck for long at this particular state i.e. invalidation query cache and once it invalidates all the entries, things start catching up.
"Why do we need one in the physical layer?"
It is because having data in query cache can seriously impact the performance IF underlying table changes quite often which can affect the overall database performance. So if your table is not changing frequently query cache is useful. But now the concept of query cache has been removed in MySQL 8 (which is not a part of the discussion).
Bufferpool is only used to store pages coming from the secondary store.
CPU can not fetch data from secondary storage so the Database management system makes a pool in RAM and then CPU keeps access data from this buffer pool from RAM.
and DBMS uses a replacement algorithm to replace pages from this buffer pool.
Cache of data is something else.
There are other data structs and techniques for data cache.
Related
How can i exclude a complete schema from buffering or cacheing?
Each Query for this schema shouldt never buffered in query cache or innoDB Buffer.
Since you tagged your question innodb, I assume you want to exclude buffering pages for a particular schema in the InnoDB Buffer Pool.
There are no options to control the schema or tables that get stored in the buffer pool. In fact, any page read by a query must be stored in the buffer pool, at least while you're querying it.
InnoDB will automatically load pages into the buffer pool when you query them. InnoDB will also automatically evict pages if the space is needed for some other page by a subsequent query. The pages are managed by an LRU (least recently used) algorithm, which makes it more likely for an infrequently-used page to be evicted.
But InnoDB goes one step further. In the old days, there was a risk that a big table-scan would evict all the pages, even if your table-scan was a once-per-day query (like those run by mysqldump). So InnoDB tries to make the buffer pool scan-resistant by tracking pages that are newcomers to the buffer pool, or those which have "seniority" because they have been read many times. The senior pages are less likely to be evicted by newcomers.
All the above should help to explain why you probably don't need to control which schemas can use the buffer pool. InnoDB makes a good effort to make sure the pages you need are in RAM, and those you don't need aren't.
For the disabling of query cache for the specific schema - generally it's not possible, however, you can turn off query cache for your connection using
SET SESSION query_cache_type = OFF;
It will completely turn off query cache for the current session.
Or you can include SQL_NO_CACHE to your select queries.
As for the InnoDB buffer pool - I don't think it's possible as there are no schema specific configuration values for it.
SELECT P_CODE, P_PRICE
FROM PRODUCT
WHERE P_PRICE >= (SELECT AVG(P_PRICE) FROM PRODUCT);
Will this query (under mysql) result in two full table scans (from disk) or will the optimizer understand that it's faster too (if there is enough RAM to hold the result set) only do one full table scan? The table has no indexes.
Is it possible to read (somehow) this information from output of the EXPLAIN command in mysql?
The question is flawed based on a misunderstanding of what a table scan actually is:
A table scan iterates over all rows in the table (irrespective of how it obtains those rows).
It also differs slightly from an index scan in that it works with the "full row". Whereas an index scan has less overall data to process, because it works with a subset of columns.
But the question is actually asking about difference between physical and logical IO.
(from disk) or will the optimizer understand that it's faster too (if there is enough RAM to hold the result set)
Yes the query will do 2 table scans. That cannot be avoided:
the server has to process the full set of prices twice.
and it has to finish processing for AVG(PRICE) before it can start processing for the WHERE filter.
However, a "logical" table scan does not necessarily require reading the data from disk twice. If all the data is in memory, the server can perform the table scan in memory. So although the second stage of processing must still perform a table scan, it can be more efficient by avoiding secondary disk access.
Take a look at this question to see how to distinguish logical and physical IO on mysql:
For a MySQL query, how do you determine physical and logical I/O?
I'll add that in theory a server could choose to keep only the Price column in memory on the first pass. In which case it wouldn't need be perform a "full table scan" on the second pass.
However this is unlikely in practice as there's a benefit to keep all the data in memory for other future queries ... whatever columns they may wish to process.
Re your comment:
my assumption, when looking at the query, is than an optimizer should/would be able to determine that "this query reads the same data twice, after the first read i will put it into memory(if there is space) and use the in-memory data for the next part of the query, instead of asking the disk for it twice"
Well, at least in MySQL's InnoDB engine, something sort of like this happens. InnoDB can't really read pages directly from disk. It load every requested page into RAM before doing data operations on it. The RAM is a preallocated area called the InnoDB buffer pool. This stores byte-for-byte copies of the pages from the on-disk tablespace, plus some metadata about them.
After reading a page, the buffer pool has no immediate need to evict it from RAM, unless other pages are requested and there's no space left in the buffer pool for them. So subsequent requests for the same pages may find the pages already residing in RAM. The more this happens, the better your performance overall.
You might have more data pages in your product table than can fit in your buffer pool. During a table-scan, InnoDB will evict pages as needed to load the remaining set of pages for the table. If you have a table that is many times larger than your buffer pool, you can imagine that this results in quite a bit of "churn" as pages come in and out. If you can afford it, allocating more RAM to the buffer pool is an good way to improve performance.
All these facts about the buffer pool don't change the fact that your query will perform two table-scans. It is true that it will be faster to read the pages from the buffer pool than reading pages from disk. You can experiment:
Shutdown your MySQL Server and start it back up again. The buffer pool should be empty at this point (unless you are using the feature to save the buffer pool on shutdown).
Run your query. It might take many seconds, because each page requested has to be read from disk before it can be used.
Run the same query again. It's faster! I've seen cases where this difference makes the performance about 4x faster in tests. I understand that RAM is typically thousands of times faster than disk, but I/O speed is not the only code running. Also it depends on what other requests are occupying the disk bandwidth, and other factors.
The difference between disk speed and RAM speed is (more or less) an arithmetic factor. No matter how large your dataset, the speed difference gives the same advantage.
Indexes are much more important, because they turn a linear search O(n) into a B-tree search O(log2n). As your dataset gets larger, the advantage of this becomes more dramatic. This is why there is so much emphasis on analyzing complexity of algorithms in computer science.
Please explain how you could do this with only one table scan. It is not obvious.
The use of the AVG() function would typically result in two full scans. If you have an index, then one or both scans might use the index.
I am attempting to make a query run on a large database in acceptable time. I'm looking at optimizing the query itself (e.g. Clarification of join order for creation of temporary tables), which took me from not being able to complete the query at all (with a 20 hr cap) to completing it but with time that's still not acceptable.
In experimenting, I found the following strange behavior that I'd like to understand: I want to do the query over a time range of 2 years. If I try to run it like that directly, then it still will not complete within the 10 min I'm allowing for the test. If I reduce it to the first 6 months of the range, it will complete pretty quickly. If I then incrementally re-run the query by adding a couple of months to the range (i.e. run it for 8 months, then 10 months, up to the full 2 yrs), each successive attempt will complete and I can bootstrap my way up to being able to get the full two years that I want.
I suspected that this might be possible due to caching of results by the MySQL server, but that does not seem to match the documentation:
If an identical statement is received later, the server retrieves the results from the query cache rather than parsing and executing the statement again.
http://dev.mysql.com/doc/refman/5.7/en/query-cache.html
The key word there seems to be "identical," and the apparent requirement that the queries be identical was reenforced by other reading that I did. (The docs even indicate that the comparison on the query is literal to the point that logically equivalent queries written with "SELECT" vs. "select" would not match.) In my case, each subsequent query contains the full range of the previous query, but no two of them are identical.
Additionally, the tables are updated overnight. So at the end of the day yesterday we had the full, 2-yr query running in 19 sec when, presumably, it was cached since we had by that point obtained the full result at least once. Today we cannot make the query run anymore, which would seem to be consistent with the cache having been invalidated when the table was updated last night.
So the questions: Is there some special case that allows the server to cache in this case? If yes, where is that documented? If not, any suggestion on what else would lead to this behavior?
Yes, there is a cache that optimizes (general) access to the harddrive. It is actually a very important part of every storage based database system, because reading data from (or writing e.g. temporary data to) the harddrive is usually the most relevant bottleneck for most queries.
For InnoDB, this is called the InnoDB Buffer Pool:
InnoDB maintains a storage area called the buffer pool for caching data and indexes in memory. Knowing how the InnoDB buffer pool works, and taking advantage of it to keep frequently accessed data in memory, is an important aspect of MySQL tuning. For information about how the InnoDB buffer pool works, see InnoDB Buffer Pool LRU Algorithm.
You can configure the various aspects of the InnoDB buffer pool to improve performance.
Ideally, you set the size of the buffer pool to as large a value as practical, leaving enough memory for other processes on the server to run without excessive paging. The larger the buffer pool, the more InnoDB acts like an in-memory database, reading data from disk once and then accessing the data from memory during subsequent reads. See Section 15.6.3.2, “Configuring InnoDB Buffer Pool Size”.
There can be (and have been) written books about the buffer pool, how it works and how to optimize it, so I will stop there and just leave you with this keyword and refer you to the documentation.
Basically, your subsequent reads add data to the cache that can be reused until it has been replaced by other data (which in your case has happened the next day). Since (for MySQL) this can be any read of the involved tables and doesn't have to be your maybe complicated query, it might make the "prefetching" easier for you.
Although the following comes with a disclaimer because it obviously can have a negative impact on your server if you change your configuration: the default MySQL configuration is very (very) conservative, and e.g. the innodb_buffer_pool_size system setting is way too low for most servers younger than 15 years, so maybe have a look at your configuration (or let your system administrator check it).
We did some experimentation, including checking the effect from the system noted in the answer by #Solarflare. In our case, we concluded that the apparent caching was real, but it had nothing to do with MySQL at all. It was instead caused by the Linux disk cache. We were able to verify this in our case by manually flushing that cache after and before getting a result and comparing times.
This is what I understand it as:
Buffer Pool in Innodb: This stores the index and data from Sql table and caches it for future queries so it doesn't need to bother Mysql all the time.
Memcached: this is used to store the data received from Innodb and caches it so it doesn't need to keep asking Innodb each time.
Aren't they both doing the same thing I.e caching the response in Ram so it is faster and reduces I/o and sql parsing? Then why add another layer of memcached on top of Innodb Buffer pool?
The Buffer pool is managed by InnoDB. Everything needed to do queries must be in the buffer pool so data already in there gets evicted if needed when new data is read from disk to be used in the current query.
Joins between tables is still done and can be costly, even if the tables are in the buffer pool.
Memcached on the other hand is a key-value store. No relational operations can be performed on data stored there, just inserts and retrievals. It is also distributed making it possible to build huge clusters.
Typically the results of long running or heavy queries are stored in memcached for a period of time, taking load of the database.
I'm running:
MySQL v5.0.67
InnoDB engine
innodb_buffer_pool_size = 70MB
Question: What command can I run to ensure that my entire 50 MB database is stored entirely in RAM?
I am curious about why you want to store the entire table in memory. My guess is that you are not. The most important thing for me is if your queries are running well and if you are tied up on disk access. It is also possible that the OS has cached disk blocks that you need if there is memory available. In this case, even though MySQL might not have it in memory, the OS will. If your queries are not running well, and you can do it, I highly recommend adding more memory if you want it all in RAM. If you have slowdowns it is more likely that you are running into contention.
show table status
will show you some of the information.
If you get the server IO/buffer/cache statistics from
show server status
and then run a query that requires each row to be accessed (say sum the non empty values from each row using a column that is not indexed) and check to see if any IO has occurred.
I doubt you are caching the entire thing in memory though with only 70MB. You have to take out a lot of cache, temp, and index buffers from that total.
If you run SELECT COUNT(*) FROM yourtable USE INDEX (PRIMARY) then InnoDB will put every page of the PRIMARY index into buffer pool (assuming there is enough room in it). If the table has secondary indexes and if you want to load them into the buffer pool, too, then craft a similar query that would read from a secondary index and do the job.