All,
I have to redesign an existing logging system being used in web application. The existing system reads an Excel sheet for records, processes(data validation) it, records the error messages for each entry in the Excel sheet into the database as soon as an error is found and displays the result in the end for all the records. So,
If I have 2 records in the excelsheet, R1 and R2, both fail with 3 validation error each, an insert query is fired 6 times for each validation message and the user sees all the 6 messages in the end of the validation process.
This method worked for smaller set of entries. But for 20,000 records, this obviously has become a bottleneck.
As per my initial redesign approach, following are the options I need suggestion on from everyone at SO:
1> Create a custom logger class with all the required information for logging and for each record in error, store the record ID as key and the Logger class object as value in a HashMap. When all the records are processed completely, perform database inserts for all the records in the HashMap in one shot.
2> Fire SQL inserts periodically i.e. for X records in total, process Y <= X records each time, perform insert operation once. and processing remaining records again.
We really do not have a set criteria at this point except for definitely improving the performance.
Can everyone please provide your feedback as to what would be an efficient logging system design and if there are better approaches than what I mentioned above ?
I would guess your problems are due to the fact you are doing row based operations, rather than set based ?
A set based operation would be the quickest way to load the data. If that is not possible I would go with the insert x records at a time as it is more scalable , inserting them all at once would require ever increasing amounts of memory (but would probably be quicker).
good discussion here on ask tom: http://asktom.oracle.com/pls/asktom/f?p=100:11:0::::P11_QUESTION_ID:1583402705463
Instead of memorizing every error in a HashMap, you could try (provided the DBMS supports it) to batch all those insert statements together and fire it at the end. Somewhat like this:
PreparedStatement ps = connection.prepareStatement("INSERT INTO table (...) values (?, ?, ...)");
for(...) {
ps.setString(1, ...);
...
ps.addBatch();
}
int[] results = ps.executeBatch();
Related
I am going to generate simple CSV file report in Java using Hibernate and MySQL.
I am using Native SQL (because query is too complex which is not possible with HQL or Criteria query and also this doesn't matter here) part of Hibernate to fetch the data and simply writing it using any of CSVWriter api (this doesn't matter here.)
As far all is well, but the problem starts now.
Requirements:
The report size can be with 5000K to 15000K records with 25 fields.
It can be run on real time.
There is one report column (let's say finalValue) for which I want sorting and it can be extract like this, (sum(b.quantity*c.unit_gross_price) - COALESCE(sum(pai.value),0)).
Problem:
MySQL Indexing can not be used for finalValue column (mentioned above) as it is complex combination of aggregate functions. So if execute the query (with or without limit) with sorting, it is taking 40sec, otherwise 0.075sec.
The Solutions:
These are the some solutions, that I can think but each have some limitations.
Sorting using java.util.TreeSet : It will throw the OutOfMemoryError, which is obvious as heap space will be exceed if I will put 15000K heavy objects.
Using limit in MySQL query and write file for each iteration : It will take much time as every query will take same time around 50sec as without sorting limit can't be use.
So the main problem here is to overcome two parameters : Memory and Time. I need to balance both of them.
Any ideas, suggestions?
NOTE: I am not given here any snaps of code that doesn't mean question details is not enough. Code doe's not require here.
I think you can use a streaming ResultSet here. As documeted on this page under the ResultSet section.
Here are the main points from the documentation.
By default, ResultSets are completely retrieved and stored in memory. In most cases this is the most efficient way to operate and, due to the design of the MySQL network protocol, is easier to implement. If you are working with ResultSets that have a large number of rows or large values and cannot allocate heap space in your JVM for the memory required, you can tell the driver to stream the results back one row at a time.
To enable this functionality, create a Statement instance in the following manner:
stmt = conn.createStatement(java.sql.ResultSet.TYPE_FORWARD_ONLY,
java.sql.ResultSet.CONCUR_READ_ONLY);
stmt.setFetchSize(Integer.MIN_VALUE);
The combination of a forward-only, read-only result set, with a fetch size of Integer.MIN_VALUE serves as a signal to the driver to stream result sets row-by-row. After this, any result sets created with the statement will be retrieved row-by-row.
There are some caveats with this approach. You must read all of the rows in the result set (or close it) before you can issue any other queries on the connection, or an exception will be thrown.
The earliest the locks these statements hold can be released (whether they be MyISAM table-level locks or row-level locks in some other storage engine such as InnoDB) is when the statement completes.
If using streaming results, process them as quickly as possible if you want to maintain concurrent access to the tables referenced by the statement producing the result set.
So, with a streaming result-set, write your order by query, and then start writing the results into your CSV file.
This still probably doesn't solve the sorting issue, but I think if you can't pre-generate that value and put an index on it, the sorting is going to take some time.
However, there might be some server config variables that you can use to optimize the sorting performance.
From the MySQL Order-By optimization page
I think you can set the read_rnd_buffer_size value, which, according to the docs, can:
Setting the variable to a large value can improve ORDER BY performance by a lot
Another one is sort_buffer_size, for which, the docs say the follwing:
If you see many Sort_merge_passes per second in SHOW GLOBAL STATUS output, you can consider increasing the sort_buffer_size value to speed up ORDER BY or GROUP BY operations that cannot be improved with query optimization or improved indexing.
Another variable that can probably help is the innodb_buffer_pool_size. Which allows innodb to keep as much table data in memory as possible and avoid some disk-seeks.
However, all of these variables require some tuning. Some trial-and-error and probably some kind of benchmarking to get right.
There are some other suggestions on that MySQL Order-By optimization page as well.
Use a temporary table to store your select result with an index on finalValue. This will store and index your intermediate result.
CREATE TEMPORARY TABLE my_temp_table (INDEX my_index_name (finalValue))
SELECT ... -- your select
Note that complex expressions will require an alias in your SELECT to be used as a part of a CREATE TABLE SELECT. I assume that your SELECT has the alias finalValue (the column you mentioned).
Then select the temporary table ordered by the finalValue (the index will be used).
SELECT * FROM my_temp_table ORDER BY finalValue;
And finally drop the temporary table (or reuse it if you want, but remember that when client session terminates temporary data is automatically deleted).
Summary tables. (Let's see more details to be sure this is Data Warehouse type data.) Summary tables are augmented periodically with subtotals and counts. Then when the report is needed, the data is readily available almost directly from the summary table, rather than scanning lots of raw data and doing aggregates.
My blog on Summary Tables. Let's see your schema and report query; we can discuss this in more detail.
I want the DBMS to help me gain speed when doing a lot of inserts.
Today I do an INSERT Query in Java and catch the exception if the data already is in the database.
The exception I get is :
SQLite Exception : [19] DB[1] exec() columns recorddate, recordtime are not unique.
If I get an exception I do a SELECT Query with the primary keys (recorddate, recordtime) and compare the result with the data I am trying to insert in Java. If it is the same I continue with next insert, otherwise I evaluate the data and decide what to save and maybe do an UPDATE.
This process takes time and I would like to speed it up.
I have thought of INSERT IF NOT EXIST but this just ignore the insert if there is any data with the same primary keys, am I right? And I want to make sure it is exactly the same data before I ignore the insert.
I would appreciate any suggestions for how to make this faster.
I'm using Java to handle large amount of data to insert into a SQLite database (SQLite v. 3.7.10). As the connection between Java and SQLite I am using sqlite4java (http://code.google.com/p/sqlite4java/)
I do not think letting the dbms handling more of that logic would be faster, at least not with plain SQL, as far as I can think of there is no "create or update" there.
When handling lots of entries often latency is an important issue, especially with dbs accessed via network, so at least in that case you want want to use mass operations whereever possible. Even if provided, "create or update" instead of select and update or insert (if even) would only half the latency.
I realize that is not what you asked for, but I would try to optimize in a different way, processing chunks of data, select all of them into a map then partition the input in creates, updates and ignores. That way ignores are almost for free, and further lookups are guaranteed to be done in memory. Unlikely that the dbms can be significantly faster.
If unsure if that is the right approach for you, profiling of overhead times should help.
Wrap all of your inserts and updates into a transaction. In SQL this will be written as follows.
BEGIN;
INSERT OR REPLACE INTO Table(Col1,Col2) VALUES(Val1,Val2);
COMMIT;
There are two things to note here: the database paging and commits will not be written to disk until COMMIT is called, speeding up your queries significantly; the second thing is the INSERT OR REPLACE syntax, which does precisely what you want for UNIQUE or PRIMARY KEY fields.
Most database wrappers have a special syntax for managing transactions. You can certainly execute a query, BEGIN, followed by your inserts and updates, and finish by executing COMMIT. Read the database wrapper documentation.
One more thing you can do is switch to Write-Ahead Logging. Run the following command, only once, on the database.
PRAGMA journal_mode = wal;
Without further information, I would:
BEGIN;
UPDATE table SET othervalues=... WHERE recorddate=... AND recordtime=...;
INSERT OR IGNORE INTO table(recorddate, recordtime, ...) VALUES(...);
COMMIT;
UPDATE will update all existing rows, ignoring non existent because of WHERE clause.
INSERT will then add new rows, ignoring existing because of IGNORE.
I have a multi-threaded client/server system with thousands of clients continuously sending data to the server that is stored in a specific table. This data is only important for a few days, so it's deleted afterwards.
The server is written in J2SE, database is MySQL and my table uses InnoDB engine. It contains some millions of entries (and is indexed properly for the usage).
One scheduled thread is running once a day to delete old entries. This thread could take a large amount of time for deleting, because the number of rows to delete could be very large (some millions of rows).
On my specific system deletion of 2.5 million rows would take about 3 minutes.
The inserting threads (and reading threads) get a timeout error telling me
Lock wait timeout exceeded; try restarting transaction
How can I simply get that state from my Java code? I would prefer handling the situation on my own instead of waiting. But the more important point is, how to prevent that situation?
Could I use
conn.setIsolationLevel( Connection.TRANSACTION_READ_UNCOMMITTED )
for the reading threads, so they will get their information regardless if it is most currently accurate (which is absolutely OK for this usecase)?
What can I do to my inserting threads to prevent blocking? They purely insert data into the table (primary key is the tuple userid, servertimemillis).
Should I change my deletion thread? It is purely deleting data for the tuple userid, greater than specialtimestamp.
Edit:
When reading the MySQL documentation, I wonder if I cannot simply define the connection for inserting and deleting rows with
conn.setIsolationLevel( Connection.TRANSACTION_READ_COMMITTED )
and achieve what I need. It says that UPDATE- and DELETE statements, that use a unique index with a unique search pattern only lock the matching index entry, but not the gap before and with that, rows can still be inserted into that gap. It would be great to get your experience on that, since I can't simply try it on production - and it is a big effort to simulate it on test environment.
Try in your deletion thread to first load the IDs of the records to be deleted and then delete one at a time, committing after each delete.
If you run the thread that does the huge delete once a day and it takes 3 minutes, you can split it to smaller transactions that delete a small number of records, and still manage to get it done fast enough.
A better solution :
First of all. Any solution you try must be tested prior to deployment in production. Especially a solution suggested by some random person on some random web site.
Now, here's the solution I suggest (making some assumptions regarding your table structure and indices, since you didn't specify them):
Alter your table. It's not recommended to have a primary key of multiple columns in InnoDB, especially in large tables (since the primary key is included automatically in any other indices). See the answer to this question for more reasons. You should add some unique RecordID column as primary key (I'd recommend a long identifier, or BIGINT in MySQL).
Select the rows for deletion - execute "SELECT RecordID FROM YourTable where ServerTimeMillis < ?".
Commit (to release the lock on the ServerTimeMillis index, which I assume you have, quickly)
For each RecordID, execute "DELETE FROM YourTable WHERE RecordID = ?"
Commit after each record or after each X records (I'm not sure whether that would make much difference). Perhaps even one Commit at the end of the DELETE commands will suffice, since with my suggested new logic, only the deleted rows should be locked.
As for changing the isolation level. I don't think you have to do it. I can't suggest whether you can do it or not, since I don't know the logic of your server, and how it will be affected by such a change.
You can try to replace your one huge DELETE with multiple shorter DELETE ... LIMIT n with n being determined after testing (not too small to cause many queries and not too large to cause long locks). Since the locks would last for a few ms (or seconds, depending on your n) you could let the delete thread run continuously (provided it can keep-up; again n can be adjusted so it can keep-up).
Also, table partitioning can help.
I'm trying to create a java program to cleanup and merge rows in my table. The table is large, about 500k rows and my current solution is running very slowly. The first thing I want to do is simply get an in-memory array of objects representing all the rows of my table. Here is what I'm doing:
pick an increment of say 1000 rows at a time
use JDBC to fetch a resultset on the following SQL query
SELECT * FROM TABLE WHERE ID > 0 AND ID < 1000
add the resulting data to an in-memory array
continue querying all the way up to 500,000 in increments of 1000, each time adding results.
This is taking way to long. In fact its not even getting past the second increment from 1000 to 2000. The query takes forever to finish (although when I run the same thing directly through a MySQL browser its decently fast). Its been a while since I've used JDBC directly. Is there a faster alternative?
First of all, are you sure you need the whole table in memory? Maybe you should consider (if possible) selecting rows that you want to update/merge/etc. If you really have to have the whole table you could consider using a scrollable ResultSet. You can create it like this.
// make sure autocommit is off (postgres)
con.setAutoCommit(false);
Statement stmt = con.createStatement(
ResultSet.TYPE_SCROLL_INSENSITIVE, //or ResultSet.TYPE_FORWARD_ONLY
ResultSet.CONCUR_READ_ONLY);
ResultSet srs = stmt.executeQuery("select * from ...");
It enables you to move to any row you want by using 'absolute' and 'relative' methods.
One thing that helped me was Statement.setFetchSize(Integer.MIN_VALUE). I got this idea from Jason's blog. This cut down execution time by more than half. Memory consumed went down dramatically (as only one row is read at a time.)
This trick doesn't work for PreparedStatement, though.
Although it's probably not optimum, your solution seems like it ought to be fine for a one-off database cleanup routine. It shouldn't take that long to run a query like that and get the results (I'm assuming that since it's a one off a couple of seconds would be fine). Possible problems -
is your network (or at least your connection to mysql ) very slow? You could try running the process locally on the mysql box if so, or something better connected.
is there something in the table structure that's causing it? pulling down 10k of data for every row? 200 fields? calculating the id values to get based on a non-indexed row? You could try finding a more db-friendly way of pulling the data (e.g. just the columns you need, have the db aggregate values, etc.etc)
If you're not getting through the second increment something is really wrong - efficient or not, you shouldn't have any problem dumping 2000, or 20,000 rows into memory on a running JVM. Maybe you're storing the data redundantly or extremely inefficiently?
I would like to display 100000 records on browser / multiple pages with minimal impact on memory. ie Per page 100 records.
I would like to move page back and forth. My doubts are
1. Can I maintain all the record inside the memory ? Is this good Idea ?
2) Can I make database connection/query for ever page ? If so how do write a query?
Could anyone please help me..
It's generally not a good idea to maintain so much records in memory. If the application is accessed by several users at the same time, the memory impact will be huge.
I don't know what DBMS are you using, but in MySQL and several others, you can rely on the DB for pagination with a query such as:
SELECT * FROM MyTable
LIMIT 0, 100
The first number after limit is the offset (how many records it will skip) and the second is the number of records it will fetch.
Bear in mind that this is SQL does not have the same syntax on every DB (some don't even support it).
I would not hold the data in memory (either in the browser or in the serving application). Instead I'd page through the results using SQL.
How you do this can be database-specific. See here for one example in MySql. Mechanisms will exist for other databases.
1) No, having all the records in memory kind of defeats the point of having a database. Look into having a scrollable result set, that way you can get the functionality you want without having to play with the SQL. You can also adjust how many records are fetched at a time so that you don't load more records than you need.
2) Db connections are expensive to create and destroy but any serious system will pool the connections so the impact on performance won't be that great.
If you want to get a bit more fancy you can do away with pages altogether and just load more records as the user scrolls through the list.
It would not be a good idea, as you are making the browser executable hold all of that.
When I had something like this to do used javascript to render the page, and just made ajax calls to get the next page. There is a slight delay in displaying the next table, as you fetch it, but users are used to that.
If you are showing 100 records/page, use json to pass the data from the server, as javascript can parse it quickly, and then use innerHTML to put the html, as the DOM is much slower in rendering tables.
As mentioned by others here, it is not a good idea to store a large list of results in memory. Query for results for each page is certainly a much better approach. To do that you have two options. One is to use whatever the database specific features your DBMS provides for targeting a specific subsection of results from a query. The other approach is to use the generic methods provided by JDBC to achieve the same effect. This keeps your code from being tied to a specific database:
// get a ResultSet from some query
ResultSet results = ...
if (count > 0) {
results.setFetchSize(count + 1);
results.setFetchDirection(ResultSet.FETCH_FORWARD);
results.absolute(count * beginIndex);
}
for (int rowNumber = 0; results.next(); ++rowNumber) {
if (count > 0 && rowNumber > count) {
break;
}
// process the ResultSet below
...
}
Using a library like Spring JDBC or Hibernate can make this even easier.
In many SQL language, you have a notion of LIMIT (mysql, ...) or OFFSET (mssql).
You can use this kind of thing to limit rows per page
Depends on the data. 100k int's might not be too bad if you are caching that.
T-SQL has SET ##ROWCOUNT = 100 to limit the amount of records returned.
But to do it right and return the total # of pages, you need a more advanced paging SPROC.
It's a pretty hotly dedated topic and there are many ways to do it.
Here's a sample of an old sproc I wrote
CREATE PROCEDURE Objects_GetPaged
(
#sort VARCHAR(255),
#Page INT,
#RecsPerPage INT,
#Total INT OUTPUT
)
AS
SET NOCOUNT ON
--Create a temporary table
CREATE TABLE #TempItems
(
id INT IDENTITY,
memberid int
)
INSERT INTO #TempItems (memberid)
SELECT Objects.id
FROM Objects
ORDER BY CASE #sort WHEN 'Alphabetical' THEN Objects.UserName ELSE NULL END ASC,
CASE #sort WHEN 'Created' THEN Objects.Created ELSE NULL END DESC,
CASE #sort WHEN 'LastLogin' THEN Objects.LastLogin ELSE NULL END DESC
SELECT #Total=COUNT(*) FROM #TempItems
-- Find out the first and last record we want
DECLARE #FirstRec int, #LastRec int
SELECT #FirstRec = (#Page - 1) * #RecsPerPage
SELECT #LastRec = (#Page * #RecsPerPage + 1)
SELECT *
FROM #TempItems
INNER JOIN Objects ON(Objects.id = #TempItems.id)
WHERE #TempItems.ID > #FirstRec AND #TempItems.ID < #LastRec
ORDER BY #TempItems.Id
I would recommend that you choose using CachedRowSet .
A CachedRowSet object is a container for rows of data that caches its rows in memory, which makes it possible to operate without always being connected to its data source.
A CachedRowSet object is a disconnected rowset, which means that it makes use of a connection to its data source only briefly. It connects to its data source while it is reading data to populate itself with rows and again while it is propagating changes back to its underlying data source.
Because a CachedRowSet object stores data in memory, the amount of data that it can contain at any one time is determined by the amount of memory available. To get around this limitation, a CachedRowSet object can retrieve data from a ResultSet object in chunks of data, called pages. To take advantage of this mechanism, an application sets the number of rows to be included in a page using the method setPageSize. In other words, if the page size is set to five, a chunk of five rows of data will be fetched from the data source at one time. An application can also optionally set the maximum number of rows that may be fetched at one time. If the maximum number of rows is set to zero, or no maximum number of rows is set, there is no limit to the number of rows that may be fetched at a time.
After properties have been set, the CachedRowSet object must be populated with data using either the method populate or the method execute. The following lines of code demonstrate using the method populate. Note that this version of the method takes two parameters, a ResultSet handle and the row in the ResultSet object from which to start retrieving rows.
CachedRowSet crs = new CachedRowSetImpl();
crs.setMaxRows(20);
crs.setPageSize(4);
crs.populate(rsHandle, 10);
When this code runs, crs will be populated with four rows from rsHandle starting with the tenth row.
On the similar path, you could build upon a strategy to paginate your data on the JSP and so on and so forth.