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    <p>Multi-threading will improve your performance but there are a couple of things you need to know:</p> <ol> <li>Each thread needs its own JDBC connection. Connections can't be shared between threads because each connection is also a transaction.</li> <li>Upload the data in chunks and <code>commit</code> once in a while to avoid accumulating huge rollback/undo tables.</li> <li>Cut tasks into several work units where each unit does one job.</li> </ol> <p>To elaborate the last point: Currently, you have a task that reads a file, parses it, opens a JDBC connection, does some calculations, sends the data to the database, etc.</p> <p>What you should do:</p> <ol> <li>One (!) thread to read the file and create "jobs" out of it. Each job should contains a small, but not too small "unit of work". Push those into a queue</li> <li>The next thread(s) wait(s) for jobs in the queue and do the calculations. This can happen while the threads in step #1 wait for the slow hard disk to return the new lines of data. The result of this conversion step goes into the next queue</li> <li>One or more threads to upload the data via JDBC.</li> </ol> <p>The first and the last threads are pretty slow because they are I/O bound (hard disks are slow and network connections are even worse). Plus inserting data in a database is a very complex task (allocating space, updating indexes, checking foreign keys)</p> <p>Using different worker threads gives you lots of advantages:</p> <ol> <li>It's easy to test each thread separately. Since they don't share data, you need no synchronization. The queues will do that for you</li> <li>You can quickly change the number of threads for each step to tweak performance</li> </ol>
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