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PolarDB:FAQ

Last Updated:Mar 04, 2024

This topic provides answers to frequently asked questions about PolarDB for PostgreSQL.

Basic information

  • What is PolarDB for MySQL?

    PolarDB for MySQL is a cloud-based relational database service. It is deployed in data centers in more than 10 regions around the world. PolarDB provides out-of-the-box online database services. PolarDB for MySQL is fully compatible with PostgreSQL. A PolarDB cluster supports a storage capacity of up to 100 TB. For more information, see What is PolarDB?

  • Why does PolarDB outperform traditional databases?

    Compared with traditional databases, PolarDB can store hundreds of terabytes of data. It also provides a wide array of features, such as high availability, high reliability, rapid elastic upgrades and downgrades, and lock-free backups. For more information, see Benefits.

  • When was PolarDB for MySQL released? When was it available for commercial use?

    PolarDB was released for public preview in September 2017, and available for commercial use in March 2018.

  • What are clusters and nodes?

    PolarDB for MySQL Cluster Edition uses a multi-node cluster architecture. A cluster has one primary node and multiple read-only nodes. A single PolarDB for MySQL cluster can be deployed across zones but not across regions. The PolarDB service is managed based on clusters, and you are charged for the service based on clusters. For more information, see Glossary.

  • Which programming languages are supported?

    PolarDB for MySQL supports programming languages such as Java, Python, PHP, Golang, C, C++, .NET, and Node.js.

  • Do I need to purchase PolarDB-X database middleware to implement sharding after I purchase PolarDB for MySQL?

    Yes, you need to purchase PolarDB-X database middleware to implement sharding after you purchase PolarDB.

  • Does PolarDB for MySQL support table partitioning?

    Yes, PolarDB supports table partitioning.

  • Does PolarDB for MySQL automatically include a partitioning mechanism?

    PolarDB for MySQL implements partitioning at the storage layer. This is transparent and imperceptible to users.

Billing

  • What are the billable items of a PolarDB for MySQL cluster?

    The billable items include the storage space, compute nodes, data backup feature (with a free quota), and SQL Explorer feature (optional). For more information, see Specifications and pricing.

  • Which files are stored in the storage space that incurs fees?

    The storage space that incurs fees stores database table files, index files, undo log files, redo log files, slowlog files, and a few system files. For more information, see Specifications and pricing.

  • How do I use storage plans of PolarDB for MySQL?

    You can purchase storage plans to deduct the storage fees of clusters that use the subscription or pay-as-you-go billing method. For example, if you have three clusters and each cluster has a storage capacity of 40 GB, the total storage capacity is 120 GB. The three clusters can share a storage plan of 100 GB. You are charged for the excess 20 GB of storage space on a pay-as-you-go basis. For more information, see Purchase a storage plan.

Cluster access (read/write splitting)

  • How do I implement read/write splitting in PolarDB for MySQL?

    You need only to use a cluster endpoint in your application so that read/write splitting can be implemented based on the specified read/write mode. For more information, see Create a custom cluster endpoint.

  • How many read-only nodes are supported in a PolarDB for MySQL cluster?

    PolarDB for MySQL uses a distributed cluster architecture. A cluster consists of one primary node and a maximum of 15 read-only nodes. At least one read-only node is required to ensure high availability.

  • Why are loads unbalanced among read-only nodes?

    One possible reason is that only a small number of connections to read-only nodes exist. Another possible reason is that one of the read-only nodes is not specified as a read-only node when you create a custom cluster endpoint.

  • What are the causes of heavy or light loads on the primary node?

    Heavy loads on the primary node may occur due to the following causes: 1. The primary endpoint is used to connect your applications to the cluster. 2. The primary node accepts read requests. 3. A large number of transaction requests exist. 4. Requests are routed to the primary node because of a high primary/secondary replication delay. 5. Read requests are routed to the primary node due to read-only node exceptions.

    A possible cause of light loads on the primary node is that the Offload Reads from Primary Node feature is enabled.

  • How do I reduce the loads on the primary node?

    You can reduce the loads on the primary node by using the following methods:

    • You can use a cluster endpoint to connect to a PolarDB for MySQL cluster. For more information, see Create a custom cluster endpoint.

    • If a large number of transactions cause heavy loads on the primary node, you can enable the transaction splitting feature in the console. This way, some queries in the transactions are routed to read-only nodes. For more information, see Configure transaction splitting.

    • If requests are routed to the primary node because of a replication delay, you can decrease the consistency level. For example, you can use the eventual consistency level. For more information, see Specify a consistency level.

    • If the primary node accepts read requests, the loads on the primary node may also become heavy. In this case, you can disable the feature that allows the primary node to accept read requests in the console. This reduces the number of read requests that are routed to the primary node.

  • Why am I unable to immediately retrieve the newly inserted data?

    The possible cause is that the specified consistency level does not allow you to immediately retrieve the newly inserted data. The cluster endpoints of PolarDB for MySQL support the following consistency levels:

    • Eventual consistency: This consistency level does not ensure that you can immediately retrieve the newly inserted data regardless of whether based on the same session (connection) or different sessions.

    • Session consistency: This consistency level ensures that you can immediately retrieve the newly inserted data based on the same session.

    Note

    A high consistency level results in heavy loads on the primary node. This compromises the performance of the primary node. Exercise caution when you select the consistency level. In most scenarios, the session consistency level can ensure service availability. For a few SQL statements that require strong consistency, you can add the /* FORCE_MASTER */ hint to the SQL statements to meet the consistency requirements. For more information, see Consistency levels.

  • How do I force an SQL statement to be executed on the primary node?

    If you use a cluster endpoint, add /* FORCE_MASTER */ or /* FORCE_SLAVE */ before an SQL statement to forcibly specify where the SQL statement is routed. For more information, see Add hints to specify routing directions of SQL statements.

    • /* FORCE_MASTER */ is used to forcibly route requests to the primary node. This method applies to a few scenarios where strong consistency is required for read requests.

    • /* FORCE_SLAVE */ is used to forcibly route requests to a read-only node. This method applies to scenarios where the PolarDB for MySQL proxy requests that special syntax be routed to a read-only node to ensure accuracy. For example, if you use this method, statements that call stored procedures and use multistatement are routed to the primary node by default.

    Note
    • Hints are assigned the highest priority for routing and are not limited by consistency levels or transaction splitting. Before you use hints, evaluate the impacts on your business.

    • The hints cannot contain the statements that change environment variables, such as /*FORCE_SLAVE*/ set names utf8;. This kind of statements may cause unexpected query results.

  • Can I assign different endpoints to different services? Can I use different endpoints to isolate my services?

    Yes, you can create multiple custom endpoints and assign them to different services. If the underlying nodes are different, the custom cluster endpoints can be used to isolate the services and do not affect each other. For more information about how to create a custom endpoint, see Create a custom cluster endpoint.

  • How do I separately create a single-node endpoint for one of the read-only nodes if multiple read-only nodes exist?

    You can create a single-node endpoint only if the Read/write Mode parameter for the cluster endpoint is set to Read Only and the cluster has three or more nodes. For more information, see Create a custom cluster endpoint.

    Warning

    However, if you create a single-node endpoint for a read-only node and the read-only node becomes faulty, the single-node endpoint may be unavailable for up to 1 hour. We recommend that you do not create single-node endpoints in your production environment.

  • What is the maximum number of single-node endpoints that I can create in a cluster?

    If your cluster has three nodes, you can create a single-node endpoint for only one of the read-only nodes. If your cluster has four nodes, you can create single-node endpoints for two of the read-only nodes, one for each. Similar rules apply if your cluster has five or more nodes.

  • Read-only nodes have loads when I use only the primary endpoint. Does the primary endpoint support read/write splitting?

    No, the primary endpoint does not support read/write splitting. The primary endpoint is always connected to only the primary node. Read-only nodes may have a small number of queries per second (QPS). This is a normal case and is irrelevant to the primary endpoint.

Management and maintenance

  • Does a replication delay occur when I replicate data from the primary node to the read-only nodes?

    Yes, a replication delay of a few milliseconds occurs.

  • When does a replication delay increase?

    A replication delay increases in the following scenarios:

    • The primary node processes a large number of write requests and generates excess redo logs. As a result, these redo logs cannot be replayed on the read-only nodes in time.

    • To process heavy loads, the read-only nodes occupy a large number of resources that are used to replay redo logs.

    • The system reads and writes redo logs at a low speed due to I/O bottlenecks.

  • How do I ensure the consistency of query results if a replication delay occurs?

    You can use a cluster endpoint and select an appropriate consistency level for the cluster endpoint. The following consistency levels are listed in descending order: session consistency, and eventual consistency. For more information, see Create a custom cluster endpoint.

  • Can the recovery point objective (RPO) be zero if a single node fails?

    If you keep the default values of PolarDB cluster parameters, the RPO is not zero. You can modify the value of the sychronous_commit parameter to set the RPO to zero. For more information about the default values of specific parameters, see Default values of cluster parameters.

  • How are node specifications upgraded in the backend, for example, upgrading node specifications from 2 cores and 8 GB memory to 4 cores and 16 GB memory? What are the impacts of the upgrade on my services?

    The proxy and database nodes of PolarDB for MySQL must be upgraded to the latest configurations. A rolling upgrade method is used to upgrade multiple nodes to minimize the impacts on your services. Each upgrade takes about 10 to 15 minutes. The impacts on your services last for no more than 30 seconds. During this period, one to three transient connection errors may occur. For more information, see Change specifications.

  • How long does it take to add a node? Are my services affected when the node is added?

    It takes about 5 minutes to add a node. Your services are not affected when the node is added. For more information about how to add a node, see Add a read-only node.

    Note

    After you add a read-only node, a read session is established to forward read requests to the read-only node. A read/write splitting connection that is created before a read-only node is added does not forward requests to the read-only node. You must close the connection and establish the connection again. For example, you can restart the application to establish the connection.

  • How long does it take to upgrade a kernel minor version to the latest revision version? Are my services affected when the upgrade is complete?

    PolarDB for MySQL uses a rolling upgrade method to upgrade multiple nodes to minimize the impacts on your services. In most cases, an upgrade requires less than 30 minutes to complete. PolarProxy or the database engine is restarted during the upgrade. This may interrupt services. We recommend that you perform the upgrade during off-peak hours. Make sure that your application can automatically reconnect to your database. For more information, see Version Management.

  • How is an automatic failover implemented?

    PolarDB for MySQL uses an active-active high-availability cluster architecture. This architecture supports automatic failovers between the primary node that supports reads and writes and the read-only nodes. The system automatically elects a new primary node. Each node in a PolarDB for MySQL cluster has a failover priority. This priority determines the probability at which a node is elected as the primary node during a failover. If multiple nodes have the same failover priority, they all have the same probability of being elected as the primary node. For more information, see Automatic failover and manual failover.

Backup and restoration

  • How does PolarDB for MySQL back up data?

    PolarDB for MySQL uses snapshots to back up data. For more information, see Backup method 2: Manual backup.

  • How fast can a database be restored?

    It takes 40 minutes to restore or clone 1 TB of data in a database based on backup sets or snapshots. If you want to restore data to a specific time point, you must include the time required to replay the redo logs. It takes about 20 to 70 seconds to replay 1 GB of redo log data. The total restoration time is the sum of the time required to restore data based on backup sets and the time required to replay the redo logs.

Performance and capacity

  • What is the maximum number of tables? What is the upper limit for the number of tables if I want to ensure that the performance is not compromised?

    The maximum number of tables depends on the number of files. For more information, see Limits.

  • Can table partitioning improve the query performance of PolarDB for MySQL?

    In most cases, if the SQL query statement falls into a partition, the performance can be improved.

  • Can I create 10,000 databases in PolarDB for MySQL? What is the upper limit for the number of databases?

    Yes, you can create 10,000 databases in PolarDB for MySQL. The maximum number of databases that you can create depends on the number of files. For more information, see Limits.

  • How are the input/output operations per second (IOPS) limited and isolated? Do the multiple nodes of a PolarDB for MySQL cluster compete for I/O resources?

    The IOPS is specified for each node of a PolarDB for MySQL cluster based on the node specifications. The IOPS of each node is isolated from that of the other nodes and does not affect each other.

  • Is the primary node affected if the performance of the read-only nodes is compromised?

    Yes, the memory consumption of the primary node is slightly increased if the loads on the read-only nodes are excessively heavy and the replication delay increases.

  • What is the impact on the database performance if I enable the SQL Explorer (full SQL log audit) feature?

    The database performance is not affected if you enable the SQL Explorer feature.

  • Which high-speed network protocol does PolarDB for MySQL use?

    PolarDB for MySQL uses dual-port Remote Direct Memory Access (RDMA) to ensure high I/O throughput between compute nodes and storage nodes, and between data replicas. Each port provides a data rate of up to 25 Gbit/s at a low latency.

  • What is the maximum bandwidth that I can use if I access PolarDB for MySQL from the Internet?

    If you access PolarDB for MySQL from the Internet, the maximum bandwidth is 10 Gbit/s.

  • What can I do if it takes a long time to restart nodes?

    A larger number of files in your cluster result in the longer time that is consumed to restart nodes. In this case, you can set the innodb_fast_startup parameter to ON to accelerate the restart process. For more information about how to modify the parameter, see Specify cluster and node parameters.