Skip to main content

Mysql JDBC driver and Streaming large resultset

We are moving one legacy component from Berkeley db to mysql so that we can replicate it to distribute read requests and shard it to scale it. I had to dump the entire db contents and stream it over http to some other component. the db content for a single customer can range from 100K to 3-4 Million records. We are using spring JDBC to make the task of dealing with jdbc api simple. Now I was using a ResultSetExtractor to stream the resultset like this.

            ResultSetExtractor resultSet = new ResultSetExtractor() {
                @Override
                public Object extractData(ResultSet result) throws SQLException, DataAccessException {
                    while(result.next()){
                        XXXXX
                    }
                    return "";
                }
            };

getJdbcTemplate(context).getJdbcOperations().query( sql, resultSetExtractor);

But it appears that Mysql native JDBC driver loads entire resultset into memory before passing the control onto ResultSetExtractor and that was causing OOM.

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.


This is explained here http://dev.mysql.com/doc/refman/5.0/en/connector-j-reference-implementation-notes.html 

It seems SimpleJdbcTemplate doesnt have a setFetchSize method and JdbcTemplate has a setFetchSize but that doesn not work when you call the query method and if you use statement then the applySettings method applies fetchSize only if its >0.  So the solution is to use PreparedStatement directly

callback = new PreparedStatementCallback() {
                @Override
                public Void doInPreparedStatement(PreparedStatement pstmt) throws SQLException, DataAccessException {
                    ResultSet rs = pstmt.executeQuery();
                    resultSetExtractor.extractData(rs);
                    rs.close();
                    return null;
                }
            };

        executeStreamed(jdbcTemplate, callback, sql);

    /**
     * http://dev.mysql.com/doc/refman/5.0/en/connector-j-reference-implementation-notes.html
     * Unless you specify the statement settings as below the mysql driver is going to load all results in memory.
     *
     * @param jdbcTemplate
     * @param callback
     * @param sql
     */
    protected void executeStreamed(SimpleJdbcTemplate jdbcTemplate, PreparedStatementCallback callback, final String sql) {
        PreparedStatementCreator creator = new PreparedStatementCreator() {
            @Override
            public PreparedStatement createPreparedStatement(Connection conn) throws SQLException {
                PreparedStatement pstmt = conn.prepareStatement(sql, java.sql.ResultSet.TYPE_FORWARD_ONLY,
                        java.sql.ResultSet.CONCUR_READ_ONLY);
                pstmt.setFetchSize(Integer.MIN_VALUE);
                return pstmt;
            }
        };
        jdbcTemplate.getJdbcOperations().execute(creator, callback);
    }


Comments

  1. Alternatively, we can subclass JdbcTemplate and override applySettings method and use this subclass.

    ReplyDelete

Post a Comment

Popular posts from this blog

Haproxy and tomcat JSESSIONID

One of the biggest problems I have been trying to solve at our startup is to put our tomcat nodes in HA mode. Right now if a customer comes, he lands on to a node and remains there forever. This has two major issues: 1) We have to overprovision each node with ability to handle worse case capacity. 2) If two or three high profile customers lands on to same node then we need to move them manually. 3) We need to cut over new nodes and we already have over 100+ nodes.  Its a pain managing these nodes and I waste lot of my time in chasing node specific issues. I loath when I know I have to chase this env issue. I really hate human intervention as if it were up to me I would just automate thing and just enjoy the fruits of automation and spend quality time on major issues rather than mundane task,call me lazy but thats a good quality. So Finally now I am at a stage where I can put nodes behing HAProxy in QA env. today we were testing the HA config and first problem I immediately

Adding Jitter to cache layer

Thundering herd is an issue common to webapp that rely on heavy caching where if lots of items expire at the same time due to a server restart or temporal event, then suddenly lots of calls will go to database at same time. This can even bring down the database in extreme cases. I wont go into much detail but the app need to do two things solve this issue. 1) Add consistent hashing to cache layer : This way when a memcache server is added/removed from the pool, entire cache is not invalidated.  We use memcahe from both python and Java layer and I still have to find a consistent caching solution that is portable across both languages. hash_ring and spymemcached both use different points for server so need to read/test more. 2) Add a jitter to cache or randomise the expiry time: We expire long term cache  records every 8 hours after that key was added and short term cache expiry is 2 hours. As our customers usually comes to work in morning and access the cloud file server it can happe

Spring 3.2 quartz 2.1 Jobs added with no trigger must be durable.

I am trying to enable HA on nodes and in that process I found that in a two test node setup a job that has a frequency of 10 sec was running into deadlock. So I tried upgrading from Quartz 1.8 to 2.1 by following the migration guide but I ran into an exception that says "Jobs added with no trigger must be durable.". After looking into spring and Quartz code I figured out that now Quartz is more strict and earlier the scheduler.addJob had a replace parameter which if passed to true would skip the durable check, in latest quartz this is fixed but spring hasnt caught up to this. So what do you do, well I jsut inherited the factory and set durability to true and use that public class DurableJobDetailFactoryBean extends JobDetailFactoryBean {     public DurableJobDetailFactoryBean() {         setDurability(true);     } } and used this instead of JobDetailFactoryBean in the spring bean definition     <bean id="restoreJob" class="com.xxx.infrastructure.quar