I just finished creating a new partitioned table to replace an old, non-partitioned table (renamed for safekeeping). I copied the newest data from the old table into the new table at the time I created it, but I still have roughly half the data left to copy over. The problem is, it's a live web service getting hammered nonstop, and every time I try to copy a chunk over via INSERT..SELECT, it insists on doing it as an atomic transaction (which consumes all the server's resources, slows everything to a crawl, and probably pushes the server dangerously close to running out of physical resources).
Just to be clear: OldTable is MyISAM. NewTable is InnoDB and partitioned by range on its primary key 'a'. Both tables have identical field names. The fields themselves aren't identical, but where they differ, the fields in NewTable are bigger.
The query that's causing problems looks like:
INSERT INTO NewTable (a,b,c,d,e,f,g)
SELECT a,b,c,d,e,f,g
FROM OldTable
WHERE a > 300000000 AND a <= 400000000
order by a
What I'd like for it to do: either commit after each insert, or just dispense with transactional integrity entirely and allow dirty reads to happen if they happen.
Locking NewTable (beyond possibly the one single row being inserted) is unacceptable. Locking OldTable is fine, because nothing else is using it anymore, anyway (besides the SQL to copy it to the new table, of course).
Also, is there a way to tell MySQL to do it at the lowest possible priority, and only work on the task in its (relative) free time?
In addition to reducing the number of rows being inserted at a time, try increasing the value of bulk_insert_buffer_size system variable to something more appropriate for your case? The default value is 8MB.
Related
I need to copy the content of one table to another. So I started using:
INSERT new_table SELECT * FROM old_table
However, I am getting the following error now:
1297, "Got temporary error 233 'Out of operation records in transaction coordinator (increase MaxNoOfConcurrentOperations)' from NDBCLUSTER"
I think I have an understanding why this occurs: My table is huge, and MySQL tries to take a snapshot in time (lock everything and make one large transaction out of it).
However, my data is fairly static and there is no other concurrent session that would modify the data. How can I tell MySQL to copy one row at a time, or in smaller chunks, without locking the whole thing?
Edit note: I already know that I can just read the whole table row-by-row into memory/file/dump and write back. I am interested to know if there is an easy way (maybe setting isolation level?). Note that the engine is InnoDB.
Data Migration is one of the few instances where a CURSOR can make sense, as you say, to ensure that the number of locks stays sane.
Use a cursor in conjunction with TRANSACTION, where you commit after every row, or after N rows (e.g. use a counter with modulo)
select the data from innodb into an outfile and load infile into
cluster
To select information related to a list of hundreds of IDs... rather than make a huge select statement, I create temp table, insert the ids into it, join it with a table to select the rows matching the IDs, then delete the temp table. So this is essentially a read operation, with no permanent changes made to any persistent database tables.
I do this in a transaction, to ensure the temp table is deleted when I'm finished. My question is... what happens when I commit such a transaction vs. let it roll it back?
Performance-wise... does the DB engine have to do more work to roll back the transaction vs committing it? Is there even a difference since the only modifications are done to a temp table?
Related question here, but doesn't answer my specific case involving temp tables: Should I commit or rollback a read transaction?
EDIT (Clarification of Question):
Not looking for advice up to point of commit/rollback. Transaction is absolutely necessary. Assume no errors occur. Assume I have created a temp table, assume I know real "work" writing to tempdb has occurred, assume I perform read-only (select) operations in the transaction, and assume I issue a delete statement on the temp table. After all that... which is cheaper, commit or rollback, and why? What OTHER work might the db engine do at THAT POINT for a commit vs a rollback, based on this specific scenario involving temp-tables and otherwise read-only operations?
If we are talking about local temporary table (i.e. the name is prefixed with a single #), the moment you close your connection, SQL Server will kill the table. Thus, assuming your data layer is well designed to keep connections open as short a time as possible, I would not worry about wrapping the creation of temp tables in a transaction.
I suppose there could be a slight performance difference of wrapping the table in a transaction but I would bet it is so small as to be inconsequential compared to the cost of keeping a transaction open longer due to the time to create and populate the temp table.
A simpler way to insure that the temp table is deleted is to create it using the # sign.
CREATE TABLE #mytable (
rowID int,
rowName char(30) )
The # tells SQL Server that this table is a local temporary table. This table is only visible to this session of SQL Server. When the session is closed, the table will be automatically dropped. You can treat this table just like any other table with a few exceptions. The only real major one is that you can't have foreign key constraints on a temporary table. The others are covered in Books Online.
Temporary tables are created in tempdb.
If you do this, you won't have to wrap it in a transaction.
EDIT: To clarify the records originally come from a flat-file database and is not in the MySQL database.
In one of our existing C programs which purpose is to take data from the flat-file and insert them (based on criteria) into the MySQL table:
Open connection to MySQL DB
for record in all_record_of_my_flat_file:
if record contain a certain field:
if record is NOT in sql_table A: // see #1
insert record information into sql_table A and B // see #2
Close connection to MySQL DB
select field from sql_table A where field=XXX
2 inserts
I believe that management did not feel it is worth it to add the functionality so that when the field in the flat file is created, it would be inserted into the database. This is specific to one customer (that I know of). I too, felt it odd that we use tool such as this to "sync" the data. I was given the duty of using and maintaining this script so I haven't heard too much about the entire process. The intent is to primarily handle additional records so this is not the first time it is used.
This is typically done every X months to sync everything up or so I'm told. I've also been told that this process takes roughly a couple of days. There is (currently) at most 2.5million records (though not necessarily all 2.5m will be inserted and most likely much less). One of the table contains 10 fields and the other 5 fields. There isn't much to be done about iterating through the records since that part can't be changed at the moment. What I would like to do is speed up the part where I query MySQL.
I'm not sure if I have left out any important details -- please let me know! I'm also no SQL expert so feel free to point out the obvious.
I thought about:
Putting all the inserts into a transaction (at the moment I'm not sure how important it is for the transaction to be all-or-none or if this affects performance)
Using Insert X Where Not Exists Y
LOAD DATA INFILE (but that would require I create a (possibly) large temp file)
I read that (hopefully someone can confirm) I should drop indexes so they aren't re-calculated.
mysql Ver 14.7 Distrib 4.1.22, for sun-solaris2.10 (sparc) using readline 4.3
Why not upgrade your MySQL server to 5.0 (or 5.1), and then use a trigger so it's always up to date (no need for the monthly script)?
DELIMITER //
CREATE TRIGGER insert_into_a AFTER INSERT ON source_table
FOR EACH ROW
BEGIN
IF NEW.foo > 1 THEN
SELECT id AS #testvar FROM a WHERE a.id = NEW.id;
IF #testvar != NEW.id THEN
INSERT INTO a (col1, col2) VALUES (NEW.col1, NEW.col2);
INSERT INTO b (col1, col2) VALUES (NEW.col1, NEW.col2);
END IF
END IF
END //
DELIMITER ;
Then, you could even setup update and delete triggers so that the tables are always in sync (if the source table col1 is updated, it'll automatically propagate to a and b)...
Here's my thoughts on your utility script...
1) Is just a good practice anyway, I'd do it no matter what.
2) May save you a considerable amount of execution time. If you can solve a problem in straight SQL without using iteration in a C-Program, this can save a fair amount of time. You'll have to profile it first to ensure it really does in a test environment.
3) LOAD DATA INFILE is a tactic to use when inserting a massive amount of data. If you have a lot of records to insert (I'd write a query to do an analysis to figure out how many records you'll have to insert into table B), then it might behoove you to load them this way.
Dropping the indexes before the insert can be helpful to reduce running time, but you'll want to make sure you put them back when you're done.
Although... why aren't all the records in table B in the first place? You haven't mentioned how processing works, but I would think it would be advantageous to ensure (in your app) that the records got there without your service script's intervention. Of course, you understand your situation better than I do, so ignore this paragraph if it's off-base. I know from experience that there are lots of reasons why utility cleanup scripts need to exist.
EDIT: After reading your revised post, your problem domain has changed: you have a bunch of records in a (searchable?) flat file that you need to load into the database based on certain criteria. I think the trick to doing this as quickly as possible is to determine where the C application is actually the slowest and spends the most time spinning its proverbial wheels:
If it's reading off the disk, you're stuck, you can't do anything about that, unless you get a faster disk.
If it's doing the SQL query-insert operation, you could try optimizing that, but your'e doing a compare between two databases (the flat-file and the MySQL one)
A quick thought: by doing a LOAD DATA INFILE bulk insert to populate a temporary table very quickly (perhaps even an in-memory table if MySQL allows that), and then doing the INSERT IF NOT EXISTS might be faster than what you're currently doing.
In short, do profiling, and figure out where the slowdown is. Aside from that, talk with an experienced DBA for tips on how to do this well.
I discussed with another colleague and here is some of the improvements we came up with:
For:
SELECT X FROM TABLE_A WHERE Y=Z;
Change to (currently waiting verification on whether X is and always unique):
SELECT X FROM TABLE_A WHERE X=Z LIMIT 1;
This was an easy change and we saw some slight improvements. I can't really quantify it well but I did:
SELECT X FROM TABLE_A ORDER BY RAND() LIMIT 1
and compared the first two query. For a few test there was about 0.1 seconds improvement. Perhaps it cached something but the LIMIT 1 should help somewhat.
Then another (yet to be implemented) improvement(?):
for record number X in entire record range:
if (no CACHE)
CACHE = retrieve Y records (sequentially) from the database
if (X exceeds the highest record number in cache)
CACHE = retrieve the next set of Y records (sequentially) from the database
search for record number X in CACHE
...etc
I'm not sure what to set Y to, are there any methods for determining what's a good sized number to try with? The table has 200k entries. I will edit in some results when I finish implementation.
A co-worker just made me aware of a very strange MySQL behavior.
Assuming you have a table with an auto_increment field and another field that is set to unique (e.g. a username-field). When trying to insert a row with a username thats already in the table the insert fails, as expected. Yet the auto_increment value is increased as can be seen when you insert a valid new entry after several failed attempts.
For example, when our last entry looks like this...
ID: 10
Username: myname
...and we try five new entries with the same username value on our next insert we will have created a new row like so:
ID: 16
Username: mynewname
While this is not a big problem in itself it seems like a very silly attack vector to kill a table by flooding it with failed insert requests, as the MySQL Reference Manual states:
"The behavior of the auto-increment mechanism is not defined if [...] the value becomes bigger than the maximum integer that can be stored in the specified integer type."
Is this expected behavior?
InnoDB is a transactional engine.
This means that in the following scenario:
Session A inserts record 1
Session B inserts record 2
Session A rolls back
, there is either a possibility of a gap or session B would lock until the session A committed or rolled back.
InnoDB designers (as most of the other transactional engine designers) chose to allow gaps.
From the documentation:
When accessing the auto-increment counter, InnoDB uses a special table-level AUTO-INC lock that it keeps to the end of the current SQL statement, not to the end of the transaction. The special lock release strategy was introduced to improve concurrency for inserts into a table containing an AUTO_INCREMENT column
…
InnoDB uses the in-memory auto-increment counter as long as the server runs. When the server is stopped and restarted, InnoDB reinitializes the counter for each table for the first INSERT to the table, as described earlier.
If you are afraid of the id column wrapping around, make it BIGINT (8-byte long).
Without knowing the exact internals, I would say yes, the auto-increment SHOULD allow for skipped values do to failure inserts. Lets say you are doing a banking transaction, or other where the entire transaction and multiple records go as an all-or-nothing. If you try your insert, get an ID, then stamp all subsequent details with that transaction ID and insert the detail records, you need to ensure your qualified uniqueness. If you have multiple people slamming the database, they too will need to ensure they get their own transaction ID as to not conflict with yours when their transaction gets committed. If something fails on the first transaction, no harm done, and no dangling elements downstream.
Old post,
but this may help people,
You may have to set innodb_autoinc_lock_mode to 0 or 2.
System variables that take a numeric value can be specified as --var_name=value on the command line or as var_name=value in option files.
Command-Line parameter format:
--innodb-autoinc-lock-mode=0
OR
Open your mysql.ini and add following line :
innodb_autoinc_lock_mode=0
I know that this is an old article but since I also couldn't find the right answer, I actually found a way to do this. You have to wrap your query within an if statement. Its usually insert query or insert and on duplicate querys that mess up the organized auto increment order so for regular inserts use:
$check_email_address = //select query here\\
if ( $check_email_address == false ) {
your query inside of here
}
and instead of INSERT AND ON DUPLICATE use a UPDATE SET WHERE QUERY in or outside an if statement doesn't matter and a REPLACE INTO QUERY also does seem to work
I have a C program that mines a huge data source (20GB of raw text) and generates loads of INSERTs to execute on simple blank table (4 integer columns with 1 primary key). Setup as a MEMORY table, the entire task completes in 8 hours. After finishing, about 150 million rows exist in the table. Eight hours is a completely-decent number for me. This is a one-time deal.
The problem comes when trying to convert the MEMORY table back into MyISAM so that (A) I'll have the memory freed up for other processes and (B) the data won't be killed when I restart the computer.
ALTER TABLE memtable ENGINE = MyISAM
I've let this ALTER TABLE query run for over two days now, and it's not done. I've now killed it.
If I create the table initially as MyISAM, the write speed seems terribly poor (especially due to the fact that the query requires the use of the ON DUPLICATE KEY UPDATE technique). I can't temporarily turn off the keys. The table would become over 1000 times larger if I were to and then I'd have to reprocess the keys and essentially run a GROUP BY on 150,000,000,000 rows. Umm, no.
One of the key constraints to realize: The INSERT query UPDATEs records if the primary key (a hash) exists in the table already.
At the very beginning of an attempt at strictly using MyISAM, I'm getting a rough speed of 1,250 rows per second. Once the index grows, I imagine this rate will tank even more.
I have 16GB of memory installed in the machine. What's the best way to generate a massive table that ultimately ends up as an on-disk, indexed MyISAM table?
Clarification: There are many, many UPDATEs going on from the query (INSERT ... ON DUPLICATE KEY UPDATE val=val+whatever). This isn't, by any means, a raw dump problem. My reasoning for trying a MEMORY table in the first place was for speeding-up all the index lookups and table-changes that occur for every INSERT.
If you intend to make it a MyISAM table, why are you creating it in memory in the first place? If it's only for speed, I think the conversion to a MyISAM table is going to negate any speed improvement you get by creating it in memory to start with.
You say inserting directly into an "on disk" table is too slow (though I'm not sure how you're deciding it is when your current method is taking days), you may be able to turn off or remove the uniqueness constraints and then use a DELETE query later to re-establish uniqueness, then re-enable/add the constraints. I have used this technique when importing into an INNODB table in the past, and found even with the later delete it was overall much faster.
Another option might be to create a CSV file instead of the INSERT statements, and either load it into the table using LOAD DATA INFILE (I believe that is faster then the inserts, but I can't find a reference at present) or by using it directly via the CSV storage engine, depending on your needs.
Sorry to keep throwing comments at you (last one, probably).
I just found this article which provides an example of a converting a large table from MyISAM to InnoDB, while this isn't what you are doing, he uses an intermediate Memory table and describes going from memory to InnoDB in an efficient way - Ordering the table in memory the way that InnoDB expects it to be ordered in the end. If you aren't tied to MyISAM it might be worth a look since you already have a "correct" memory table built.
I don't use mysql but use SQL server and this is the process I use to handle a file of similar size. First I dump the file into a staging table that has no constraints. Then I identify and delete the dups from the staging table. Then I search for existing records that might match and put the idfield into a column in the staging table. Then I update where the id field column is not null and insert where it is null. One of the reasons I do all the work of getting rid of the dups in the staging table is that it means less impact on the prod table when I run it and thus it is faster in the end. My whole process runs in less than an hour (and actually does much more than I describe as I also have to denormalize and clean the data) and affects production tables for less than 15 minutes of that time. I don't have to wrorry about adjusting any constraints or dropping indexes or any of that since I do most of my processing before I hit the prod table.
Consider if a simliar process might work better for you. Also could you use some sort of bulk import to get the raw data into the staging table (I pull the 22 gig file I have into staging in around 16 minutes) instead of working row-by-row?