Thanks Tyler... so my understanding is, even if Cassandra doesn't do off-heap caching, by having a large-enough memory, it minimize the chance of swapping the java heap to a disk. Is that correct?
-- Y. On Tue, May 15, 2012 at 6:26 PM, Tyler Hobbs <ty...@datastax.com> wrote: > On Tue, May 15, 2012 at 3:19 PM, Yiming Sun <yiming....@gmail.com> wrote: > >> Hello, >> >> I was reading the Apache Cassandra 1.0 Documentation PDF dated May 10, >> 2012, and had some questions on what the recommended memory size is. >> >> Below is the snippet from the PDF. Bullet 1 suggests to have 16-32GB of >> RAM, yet Bullet 2 suggests to limit Java heap size to no more than 8GB. My >> understanding is that Cassandra is implemented purely in Java, so all >> memory it sees and uses is the JVM Heap. >> > > The main way that additional RAM helps is through the OS page cache, which > will store hot portions of SSTables in memory. Additionally, Cassandra can > now do off-heap caching. > > > >> So can someone help me understand the discrepancy between 16-32GB of >> RAM and 8GB of heap? Thanks. >> >> == snippet == >> Memory >> The more memory a Cassandra node has, the better read performance. More >> RAM allows for larger cache sizes and >> reduces disk I/O for reads. More RAM also allows memory tables >> (memtables) to hold more recently written data. Larger >> memtables lead to a fewer number of SSTables being flushed to disk and >> fewer files to scan during a read. The ideal >> amount of RAM depends on the anticipated size of your hot data. >> >> • For dedicated hardware, a minimum of than 8GB of RAM is needed. >> DataStax recommends 16GB - 32GB. >> >> • Java heap space should be set to a maximum of 8GB or half of your total >> RAM, whichever is lower. (A greater >> heap size has more intense garbage collection periods.) >> >> • For a virtual environment use a minimum of 4GB, such as Amazon EC2 >> Large instances. For production clusters >> with a healthy amount of traffic, 8GB is more common. >> > > > > -- > Tyler Hobbs > DataStax <http://datastax.com/> > >
