Question

Our company has a Batch Application which runs every day, It does some database related jobs mostly, import data into database table from file for example.

There are 20+ tasks defined in that application, each one may depends on other ones or not.
The application execute tasks one by one, the whole application runs in a single thread.

It takes 3~7 hours to finish all the tasks. I think it’s too long, so I think maybe I can improve performance by multi-threading.

I think as there is dependency between tasks, it not good (or it’s not easy) to make tasks run in parallel, but maybe I can use multi-threading to improve performance inside a task.

for example : we have a task defined as “ImportBizData”, which copy data into a database table from a data file(usually contains 100,0000+ rows). I wonder is that worth to use multi-threading?

As I know a little about multi-threading, I hope some one provide some tutorial links on this topic.

Answer 1

Multi-threading will improve your performance but there are a couple of things you need to know:

1. Each thread needs its own JDBC connection. Connections can’t be shared between threads because each connection is also a transaction.
2. Upload the data in chunks and commit once in a while to avoid accumulating huge rollback/undo tables.
3. Cut tasks into several work units where each unit does one job.

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.

What you should do:

1. 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
2. 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
3. One or more threads to upload the data via JDBC.

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)

Using different worker threads gives you lots of advantages:

1. 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
2. You can quickly change the number of threads for each step to tweak performance