We use Apache Derby in our commercial application, PaperCut NG. It's proven to be
very reliable, however we occasionally get reports of very bad
performance in some areas. We haven't had the time to investigate them
fully previously (usually upgrading to an external DB like Postgres or
SQL Server fixes the issue). This time we had a look in more detail
with a recent report, and we've found some very strange performance
characteristics ... and would love some advice and assistance.
We have a query that is doing inner joins to 5 tables. It's quite a
simple query, but the core table has about 300,000 rows, and where
limiting the results based on a date in that table that is indexed.
Here's a summary of my situation/findings:
- Using the latest Derby release 10.3.1.4, with a Java 1.5 VM on
- We only have a single WHERE clause, which is on the indexed date
field is restricting the data such that no data is returned. e.g.
log_date > (latest log date). So derby should quickly detect there
is litte/no data to return.
- Running the original query takes 22 minutes running 100% CPU.
- Running a count(*) for the same query is quick (< 1 sec).
- Removing the ORDER BY and changing the select list to just
include a single field from each table and it still takes 22 minutes.
- Changing the select list to retrieve only a single field from 2
of the table and it still takes 22 minutes (I have a log of the query
and the runtime stats for this attached "derby-slow.log").
- Changing the select list to a single field from 1 of the tables
makes the query run fast - less than a second. (I have a log of the
query and the runtime stats for this attached "derby-fast.log").
- Running the original query on the same dataset in PostgreSQL or
SQL Server is very fast (less than a second). This is why we often
recommend customers upsize to Postgres or SQL Server.
- Also the SQL is generated via Hibernate ORM, so we have some
limitations in how we can modify the SQL.
>From the query plan it seems that seems that it stops using the date
index on the "tbl_printer_usage_log" log table, and changes from Hash
joins to Nested Loop joins. On a large table like this when providing
a where clause that on a field that is indexed .... we have to ensure
that derby uses the index.
If I increase the pageCacheSize to 100,000 pages, it reduces the time
of the query to about 2-3 minutes, but it's still very slow compared to
when the correct index is used.
Can anyone please help me understand the following:
If we can understand what's causing this, we'll be able to make a much
more effective use of Derby. At the moment, on customers with large
datasets, we currently just recommend they "upsize" to Postgres or SQL
Server and the problem goes away. However, we'd much prefer to fix
this and have our Derby database behave better.
- Why does the query plan change dramatically, just by changing the
fields that are retrieved?
- Why is derby avoiding the most obvious index? The date field in
the 300,000 row table (the date field is the only field in our where
- Is there anyway to avoid this behavior?
I'd be happy to provide the derby database that exhibits these problems
if someone would like to see what's going on. The database is from a
customer, so I don't want to post it publicly, but if you send me an
email off-list I'd be happy to provide it.
PaperCut Software International Pty. Ltd.
Phone: +61 (3) 9807 5767