WebSphere eXtreme Scale Administration Guide > Capacity planning



Sizing memory and partition count calculation


You can calculate the amount of memory and partitions needed for the specific configuration.

WebSphere eXtreme Scale stores data within the address space of Java™ virtual machines (JVM). Each JVM provides processor space for servicing create, retrieve, update, and delete calls for the data that is stored in the JVM. In addition, each JVM provides memory space for data entries and replicas. Java objects vary in size, therefore make a measurement to make an estimate of how much memory you need.

To size the memory that you need, load the application data into a single JVM. When the heap usage reaches 60%, note the number of objects that are used. This number is the maximum recommended object count for each of the Java virtual machines.

To get the most accurate sizing, use realistic data and include any defined indexes in your sizing because indexes also consume memory. The best way to size memory use is to run garbage collection verbosegc output because this output gives you the numbers after garbage collection. You can query the heap usage at any given point through MBeans or programmatically, but those queries give you only a current snapshot of the heap, which might include uncollected garbage, so using that method is not an accurate indication of the consumed memory.


Scaling up the configuration

Number of shards per partition (numShardsPerPartition value)

To calculate the number of shards per partition, or the numShardsPerPartition value, add 1 for the primary shard plus the total number of replica shards you want. 

numShardsPerPartition = 1 + total_number_of_replicas


Number of Java virtual machines (minNumJVMs value) To scale up the configuration, first decide on the maximum number of objects that need to be stored in total.

To determine the number of Java virtual machines you need, use the following formula: 

minNumJVMS=(numShardsPerPartition * numObjs) / numObjsPerJVM

Round this value up to the nearest integer value.


Number of shards (numShards value) At the final growth size, 10 shards for each JVM should be used. As described before, each JVM has one primary shard and (N-1) shards for the replicas, or in this case, 9 replicas. Because you already have a number of Java virtual machines to store the data, you can multiply the number of Java virtual machines by 10 to determine the number of shards: 

numShards = minNumJVMs * 10 shards/JVM


Number of partitions If a partition has one primary shard and one replica shard, then the partition has two shards (primary and replica). The number of partitions is the shard count divided by 2, rounded up to the nearest prime number. If the partition has a primary and two replicas, then the number of partitions is the shard count divided by 3, rounded up to the nearest prime number. 

numPartitions = numShards / numShardsPerPartition


Example of scaling

In this example, the number of entries begins at 250 million. Each year, the number of entries grows about 14%. After 7 years, the total number of entries is 500 million, so plan the capacity accordingly. For high availability, a single replica is needed. With a replica, the number of entries doubles, or 1 billion entries. As a test, 2 million entries can be stored in each JVM. Using the calculations in this scenario the following configuration is needed:


Start configuration Based on the previous calculations, you would start with 250 Java virtual machines and grow toward 500 Java virtual machines over 5 years, which allows you to manage incremental growth until you arrive at the final number of entries.

In this configuation, about 200,000 entries are stored per partition (500 million entries divided by 2503 partitions). You should set the numberOfBuckets parameter on the map that holds the entries to the closest higher prime number, in this example 70887, which keeps the ratio around 3.


When the maximum number of Java virtual machines is reached When you reach the maximum number of 500 Java virtual machines, you can still grow your grid. As the number of Java virtual machines grows beyond 500, the shard count begins to drop below 10 for each JVM, which is below the recommended number. The shards start to become larger, which can cause problems. You should repeat the sizing process considering future growth again, and reset the partition count. This practice requires a full grid restart, or an outage of the grid.


Number of servers

Attention: Do not use paging on a server under any circumstances. A single JVM uses more memory than the heap size. For example, 1 GB of heap for a JVM actually uses 1.4 GB of real memory. Determine the available free RAM on the server. Divide the amount of RAM by the memory per JVM to get the maximum number of Java virtual machines on the server.



Parent topic

Capacity planning


+

Search Tips   |   Advanced Search