#Mysql optimizer cost model full

There are additional considerations for optimizations (e.g.For HJ, we need to decide which table is the (hash table) build side and the other becomes the probe side of the plan. Typically, we want to choose the table (keyspace) with a smaller result set to be the outer table. For NLJ, we need to decide which table is the outer table in which one is the inner table. Once the join type is chosen, additional decisions have to be made on order within the join. For query service, the nested loop is the default and for analytics service, the hash join is the default. Couchbase query service and analytics service both support the nested loop (NLJ) and hash join (HJ). JOIN TYPE: Each query engine is capable of certain types of joins.N1QL Optimizer doesn’t reorder the joins yet. Here, we select the sequence in which the joins are performed. For example, ((t1 INNER JOIN t2) INNER JOIN t3) is the same as ((t3 INNER JOIN t2) INNER JOIN t1). Depending on the type of join, we can change the order without changing the meaning and result of the query. JOINS are performed on two keyspaces (tables) at a time. JOIN ORDER: The purpose is to limit the size of the intermediate result set.Here we select one or more indexes for each keyspace, decide the predicates (spans) for each scan request, decide whether it’s covering or not.

#Mysql optimizer cost model full

ACCESS PATH: Select from available indexes or full scan (primary index scan in case of Couchbase) for each keyspace (equivalent to tables).The type of rewrites depends on the specific capabilities and nuances of the optimizer in subsequent phases. This includes evaluating constant filters, converting joins, subquery flattening, folding the subqueries and more. REWRITE: Rewrite the query to its optimal equivalent form to make the optimization easier.The optimizer, broadly speaking, does the following: For real-world workloads, decisions based on statistics are much better than rule-based decisions. Bad decisions have huge negative performance implications. The same is true for NoSQL systems with optimizers. It’s not an exaggeration to say RDBMS would not have been so successful in handling such rich use cases at such low cost without a CBO. The cost-based optimizer (CBO) changed everything, correctly optimizing the query for a variety of data, data skew and workloads. This led to the complexity of rules, user-defined optimizer hints and the query plan efficiency issues for complex queries. Initial implementations of SQL used rule-based optimizers. With the extraordinary flexibility of a query language, comes extraordinary responsibility to optimize and run the queries efficiently. Therefore even NoSQL databases have to care about optimization. This article explains how major NoSQL databases have implemented various elements of SQL. This benefits app development and data analysis. You can select, join, project any relation (table or intermediate relations) without planning all of the combinations ahead. As a language, it’s extraordinarily flexible, even when the underlying schema isn’t. SQL is the most successful 4th generation language. Databases with a better optimizer will make it easier to develop, manage and meet the SLAs. These decisions have major implications on query performance, system throughput and your ability to meet the SLAs. Knowing this, why would you accept a static rule (or query shape !) based optimization on your business-critical database workload?

The optimizers try to come up with a plan to execute the query with the least resources: CPU, memory. In 2019, when it matters - like getting to your kid’s recital or a ballgame on time - would you use a static direction map that doesn’t account for the traffic? Google Maps’ route optimizer will optimize for time.

Answers here are brief and nonexhaustive. What are the performance implications without a CBO?.Here, I’ve tried to answer the questions from NoSQL users unfamiliar with the benefits of CBO. In Couchbase 6.5, we announced the cost-based optimizer (CBO-preview) for N1QL in query service. This is the guiding light for SQL and NoSQL optimizers. Less everything for the query plan it creates. Do less: Less memory, less CPU, less disk, less IO, less instructions, less partitions, less overflow. There is no truer statement on the goals of a query optimizer.