I recently pulled and built the 7.1beta1 code and ran our regression
tests against this version. Our app is java based and uses the JDBC
drivers for client access. Almost all of our regression tests failed.
In looking into this further there are some significant problems with
the latest JDBC code.
Specifically the code that has been added to provide caching of byte's
doesn't work correctly. This code makes some assumptions that are not
valid, specifically it assumes that when a new SQL statement is
executed, all previously used byte's are no longer in use and can be
reused. Specifically the pg_stream.deallocate() call that appears in
the Connection.ExecSQL() method:
// Deallocate all resources in the stream associated
// with a previous request.
// This will let the driver reuse byte arrays that has already
// been allocated instead of allocating new ones in order
// to gain performance improvements.
The assumption here is invalid. For example if code does the following:
1) execute a query A
2) for each row of the result set execute a different query B
When the query B is executed for the first row of query A, the
deallocate() method gets called which causes *all* byte's originating
from the pg_stream object (which includes the row data in the ResultSet
object) to be reclaimed and reused, including those associated with the
subsequent rows of query A.
So what ends up happening is that the data in query A's result set
starts to get corrupted as the underlying byte's get reused by
Believe me this causes all sorts of problems.
A similar problem can be found with the getBytes() method of result
set. This method returns the underlying byte to the caller. The
caller could keep this object around for well past the next ExecSQL call
and find that the value gets corrupted as it is being reused in
In addition to the above bugs with this caching code, there are other
significant problems as well. The code as written never frees up any of
these cached objects. This causes significant problems when connections
are long lived (i.e. in a connection pool). This results in essentially
a memory leak. To illustrate the problem lets say a connection
performed the following queries:
select 10_byte_char_column from foo;
select 11_byte_char_column from bar;
select 12_byte_char_column from foo_bar;
select 13_byte_char_column from foo_foo;
further assume that each query returns 1000 rows.
After the first query runs the cache will contain 1000 byte arrays =
After the second query runs the cache will contain 1000 byte arrays
+ 1000 byte arrays = 21K.
After the third query runs the cache will contain 1000 byte arrays +
1000 byte + 1000 byte arrays = 33K.
As you can see, over time it can easily be the case that the amount of
memory eaten up could be large, especially if lots of queries are being
run that return thousands of rows of differing sized values. While it
is true the example above is worst case (i.e. it doesn't show any reuse
of what is in the cache), this worst case makes the entire caching
feature as it is currently written a problem for me as my connection
pool logic will keep these connections open for long periods of time
during which they will be performing a wide variety of differing sql
statements, many of which will return large numbers of rows.
Finally, my app does a lot of queries that select values that are > 256
bytes long. The current cache implementation doesn't help in these
cases at all (as it only caches arrays up to 256 bytes), but it is with
these large byte's where the overhead of allocating and then garbage
collecting them is greatest and could most take advantage caching
I have looked at the source code and thought about how to fix the above
problems, and I have not been able to come up with anything that works
well. While is certainly would be possible to code something that
solves these problems, I fear that the result would actually be slower
than the current situation in 7.0 where no cache exists and lots of
arrays are allocated and then reclaimed by the garbage collector.
I would suggest that the cache code be pulled out for 7.1beta2, until a
better overall solution is found.
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