Concurrency and scaling in SQream DB¶
The number of queries that a SQream DB cluster can process is determined by the complexity of the workload and the size of the cluster.
In general, SQream DB supports
n concurrent statements by having
n workers in a cluster. Each worker uses a fixed slice of a GPU’s memory, with usual values are around 8-16GB of GPU memory per worker.
Scaling when data sizes grow¶
SQream DB scales well by adding more storage and querying on large data sets - more or less linearly.
Scaling when queries are queueing¶
SQream DB scales well by adding more workers, GPUs, and finally nodes to support more concurrent statements.
What to do when queries are slow¶
Adding more workers or GPUs does not boost the performance of a single statement or query.
To boost the performance of a single statement, start by examining the best practices and ensure the guidelines are followed.
Adding additional RAM to nodes, using more GPU memory, and faster CPUs or storage can also help.
Analyzing complex workloads can be challenging. SQream’s experienced customer support has the experience to advise on these matters to ensure the best experience.
Visit SQream’s support portal for additional support.