i am new to the Grails and Redis .

i have to build a project by using above technologies.

i feel comfort with Grails but i coming to Redis i know basic command now to run it thats it i dont know more than that.

can u help me out .

give me the basic stuff which need to practice and i am using STS tool.give me the sample project which build on both Grails and Redis .

and pls explain me how to configure Redis in config.groovy.

i am waiting for ur help and suggestions .

if possible please mail me to ” sivakotiuday@gmail.com” .

thank you.

Your Uday.

Absolutely – this is always the balance to deal with – larger objects vs more objects

just in order to add some context.

Redis 1.1 ( currently in beta, download it from Git) supports MSET (multi-set) and MGET (already in 1.0). So it’s possible to set multiple fields in a single operation.
Redis 1.2 will support an Hash type.
Redis 1.1 supports append-only journal for better durability, with three different fsync() policies (never, every second, after every write).

Redis 1.1 is 10x faster with operations like LRANGE or SMEMBERS or MGET involving more data than 1 Kbyte. This is very important in your scenario if your objects are > 1k.

For any info please drop a message into the Redis Google Group and we’ll try to help.

Cheers,
Salvatore (author of Redis)

In our mysql table, there are about 20 columns, row size could go up to 2,000. Even if Redis could support 100,000 update/second, the network bandwidth is a problem as 100,000 * 2,000=200M per second if using serialized documents as you said.

Your test shows redis could show 300,000 update/second, if using serialzied documents, then the entire row will be replaced, if the row size is 1,000 (in our case, the row size could go up to 8,000, the row has about 50 columns), then every second 300,000 * 1,000=300M data will be transferred over network, the network card is hard to support that. So if I could operate one one column, that will save lots of network bandwidth

There are multiple choices. The most common is to store serialized documents in Redis – if you change one of the columns well you basically change the whole document. This works well if your update is basically replace if it is something like increment you may want to store column as a separate value.

1: I am looking at redis and see whether there is a chance to use it to replace mysql memory engine. As there are some insert, the table lock blocks the throughput, but one insert could touch/set many columns, say 10 columns, so if insert runs 1000/second in mysql, then for redis, that’s 1000*10=10,000 set/second as redis can’t set many columns (not sure whether I am right, but I looks through the doc and can’t find a way to do so) as one command as mysql. For query many columns such as 10 columns, redis could return a list, so one query could be mapped to one get. So does that mean if an app has lots of insert/update which touch many columns, then redis is not a good choice?

I understand that the single-threadedness of the slave will slow down the slave, even cause it to lag behind the master. But that shouldn’t have any effect on the master, right? So what caused the master’s performance to drop from 30k updates/sec to 10k updates/sec when replication was turned on in your test?

Andy

The overhead of replication is really rather small. The problem is replication is single thread so slave capacity is pretty much limited to performance when all queries are ran by single thread.

The one thing that strikes me is the performance penalty of MySQL replication. In your test replication reduces MySQL performance by 67% (from 30K to 10K updates/sec).

67% is a very large performance degradation, is it typical for replication to have such big slowdown? What about replication that causes such a huge performance drop? Is it the binlog? innodb_support_xa?

What if I have a MySQL server without replication, but still have binlog & innodb_support_xa enabled for data recovery purpose? What kind of performance penalty would that incur? Hopefully a lot less than 67%?

Andy