@ssougou ssougou.blogspot.com Vitess@GoSV What is Vitess ● Sharding middleware for MySQL ● Massively scalable ● HA ● Cloud-native pxhere CC0 Vitess stats Started 2010 7,500+ stars 16,000+ commits

1 VITESS.IO What is Vitess? Cloud Native Database Massively Scalable HA Based on MySQL 2 3 VITESS.IO Vitess Stats Started 2010 Marquee Adopters 100+ Contributors 17,000 + Commits 1000+

A MySQL slave that cannot be promoted to master. Conventionally, these are used for background processing jobs, such as taking backups, dumping data to other systems, heavy analytical queries, MapReduce (smaller) shard. You will need to run one job for each target shard. Also, you cannot run them in parallel because they need to take an rdonly instance offline to perform the comparison. NOTE: This example ApplySchema command applies a schema change to the specified keyspace on every master tablet, running in parallel on all shards. Changes are then propagated to slaves via replication. The command format is: ApplySchema

A MySQL slave that cannot be promoted to master. Conventionally, these are used for background processing jobs, such as taking backups, dumping data to other systems, heavy analytical queries, MapReduce ApplySchema command applies a schema change to the specified keyspace on every master tablet, running in parallel on all shards. Changes are then propagated to slaves via replication. The command format is: ApplySchema MySQL slaves. The master handles write operations, while slaves handle read-only traffic, batch processing operations, and other tasks. Each MySQL instance within the shard should have the same data, excepting

MySQL replica that cannot be promoted to master. Conventionally, these are used for background processing jobs, such as taking backups, dumping data to other systems, heavy analytical queries, MapReduce order, there’s no need to follow this implicit order. Instead, we can commit the shard sessions in parallel. Bulk insert: Vitess supports bulk inserts. This results in a corresponding bulk insert for lookup T2: DDL 2 on table1 T3: Version Event DDL1 // gets written because of the time taken by tracker processing DDL1 T4: DML1 on table1 T5: Version Event DDL2 // gets written AFTER DML1 So now on the replica

MySQL replica that cannot be promoted to master. Conventionally, these are used for background processing jobs, such as taking backups, dumping data to other systems, heavy analytical queries, MapReduce order, there’s no need to follow this implicit order. Instead, we can commit the shard sessions in parallel. Bulk insert: Vitess supports bulk inserts. This results in a corresponding bulk insert for lookup T2: DDL 2 on table1 T3: Version Event DDL1 // gets written because of the time taken by tracker processing DDL1 T4: DML1 on table1 T5: Version Event DDL2 // gets written AFTER DML1 So now on the replica

MySQL replica that cannot be promoted to master. Conventionally, these are used for background processing jobs, such as taking backups, dumping data to other systems, heavy analytical queries, MapReduce order, there’s no need to follow this implicit order. Instead, we can commit the shard sessions in parallel. Bulk insert: Vitess supports bulk inserts. This results in a corresponding bulk insert for lookup T2: DDL 2 on table1 T3: Version Event DDL1 // gets written because of the time taken by tracker processing DDL1 T4: DML1 on table1 T5: Version Event DDL2 // gets written AFTER DML1 So now on the replica

MySQL replica that cannot be promoted to primary. Conventionally, these are used for background processing jobs, such as taking backups, dumping data to other systems, heavy analytical queries, MapReduce Vttablet. The output of the parser is stored in a Abstract Syntax Tree which is used for further processing by the planner. The code for the parser and AST lives here. Parser Vitess uses a yacc-based time. This could be a simple CREATE TABLE or a hours-long running ALTER TABLE. Noteworthy: • Two parallel ALTER TABLE are likely to interfere with each other, competing for same resources, causing total

MySQL replica that cannot be promoted to master. Conventionally, these are used for background processing jobs, such as taking backups, dumping data to other systems, heavy analytical queries, MapReduce MySQL replicas. The master handles write operations, while replicas handle read-only traffic, batch processing operations, and other tasks. Each MySQL instance within the shard should have the same data, excepting in a shard. Example Flags Name Type Definition concurrency Int How many tablets to reload in parallel include_master Boolean Include the master tablet 134 Arguments • – Required

MySQL replica that cannot be promoted to master. Conventionally, these are used for background processing jobs, such as taking backups, dumping data to other systems, heavy analytical queries, MapReduce MySQL replicas. The master handles write operations, while replicas handle read-only traffic, batch processing operations, and other tasks. Each MySQL instance within the shard should have the same data, excepting in a shard. Example Flags Name Type Definition concurrency Int How many tablets to reload in parallel include_master Boolean Include the master tablet 114 Arguments • – Required