12/17/2022 0 Comments Patterns in sai![]() ![]() ![]() SAI configuration is simpler and is tuned with existingĭatabase parameters, such as in cassandra.yaml. Unlike the Solr-based DSE Search, SAI has no How does schema management compare between DSE Search and SAI? Otherwise rely heavily on maintaining multiple query-specific tables. At its core, SAI is aįiltering engine, and simplifies data modeling and client applications that would ![]() While it does provide some of the sameįunctionality, SAI is not a complete replacement for DSE Search. This case with an SAI index, you would specify just one of the columns that comprisesįor developers, SAI removes several previous pain points, including the need toĭuplicate denormalized data to query non-PrimaryKey columns.įor operators, SAI has several advantages, including the use of significantly lessĭisk space for indexing fewer failure points easier uptime due to the simplifiedĪrchitecture of SAI and fewer copies of data to secure. AĬomposite partition key means that the partition is based on two or more columns. You can alsoĭefine an SAI index using a single column in the table's composite partition key. In this case, SAI issues an invalid query message. Exception: there is no need toĭefine an SAI index based on the partition key when it's comprised of only one column SAI index can be based on any column in the table. SAI makes it possible to define multiple indexes on the same database table. Natural for you, write to just that table, and query it any way you want. Just to cater to particular query patterns. SAI also makes data modeling easier because you do not need to create custom tables Was inspired by SASI to achieve the goal of efficient and simpler filtering via the Keys, but you could not index parts of a composite partition. Such as parts of a composite partition key. Oftentimes, developers ask: "How can I query additional fields outside of theĬassandra partition key?" SAI implements efficient indexes based on a table's columns, What computing challenges does SAI solve? This matters for write performance.įor read performance, again, maximizing use of the Chunk Cache will benefit SAI reads because all on-disk index componentsĪre accessed through this mechanism. If this occurs in your environment, increaseĪside from memory, SAI uses the same tunable parameters for Cassandra, such asĬompaction throughput and compaction executors. If the memtable_flush_writers value is set too low, writes may.Heavy mixed read/write workloads may want to:. ![]() Of memory for the OS and other in-memory structures.įile_cache_size_in_mb to 75% of that value. Increase -XX:MaxDirectMemorySize, leaving approximately 15-20%.Compared with most indexing environments, SAI configuration and related settings ![]()
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