This document introduces common performance issues that might exist in DM and how to deal with them.
Before diagnosing an issue, you can refer to the DM Benchmark Report.
When diagnosing and handling performance issues, make sure that:
- The DM monitoring component is correctly configured and installed.
- You can view monitoring metrics on the Grafana monitoring dashboard.
- The component you diagnose works well; otherwise, possible monitoring metrics exceptions might interfere with the diagnosis of performance issues.
In the case of a large latency in the data migration, to quickly figure out whether the bottleneck is inside the DM component or in the TiDB cluster, you can first check
DML queue remain length in Write SQL Statements to Downstream.
To diagnose performance issues in the relay log unit, you can check the
binlog file gap between master and relay monitoring metric. For more information about this metric, refer to monitoring metrics of the relay log. If this metric is greater than 1 for a long time, it usually indicates that there is a performance issue; if this metric is 0, it usually indicates that there is no performance issue.
If the value of
binlog file gap between master and relay is 0, but you suspect that there is a performance issue, you can check
binlog pos. If
master in this metric is much larger than
relay, a performance issue might exist. In this case, diagnose and handle this issue accordingly.
read binlog event duration refers to the duration that the relay log reads binlog from the upstream database (MySQL/MariaDB). Ideally, this metric is close to the network latency between DM-worker and MySQL/MariaDB instances.
For data migration in one data center, reading binlog data is not a performance bottleneck. If the value of
read binlog event durationis too large, check the network connection between DM-worker and MySQL/MariaDB.
For data migration in the geo-distributed environment, try to deploy DM-worker and MySQL/MariaDB in one data center, while deploying the TiDB cluster in the target data center.
The process of reading binlog data from the upstream database includes the following sub-processes:
- The upstream MySQL/MariaDB reads the binlog data locally and sends it through the network. When no exception occurs in the MySQL/MariaDB load, this sub-process usually does not become a bottleneck.
- The binlog data is transferred from the machine where MySQL/MariaDB is located to the machine where DM-worker is located via the network. Whether this sub-process becomes a bottleneck mainly depends on the network connection between DM-worker and the upstream MySQL/MariaDB.
- DM-worker reads binlog data from the network data stream and constructs it as a binlog event. When no exception occurs in the DM-worker load, this sub-process usually does not become a bottleneck.
After reading the binlog event into the DM memory, DM's relay processing unit decodes and verifies data. This usually does not lead to performance bottleneck; therefore, there is no related performance metric on the monitoring dashboard by default. If you need to view this metric, you can manually add a monitoring item in Grafana. This monitoring item corresponds to
dm_relay_read_transform_duration, a metric from Prometheus.
When writing a binlog event to a relay log file, the relevant performance metric is
write relay log duration. This value should be microseconds when
binlog event size is not too large. If
write relay log duration is too large, check the write performance of the disk. To avoid low write performance, use local SSDs for DM-worker.
The main operations of the Load unit are to read the SQL file data from the local and write it to the downstream. The related performance metric is
transaction execution latency. If this value is too large, check the downstream performance by checking the monitoring of the downstream database. You can also check whether there is a large network latency between DM and the downstream database.
To diagnose performance issues in the Binlog replication unit, you can check the
binlog file gap between master and syncer monitoring metric. For more information about this metric, refer to monitoring metrics of the Binlog replication.
- If this metric is greater than 1 for a long time, it usually indicates that there is a performance issue.
- If this metric is 0, it usually indicates that there is no performance issue.
binlog file gap between master and syncer is greater than 1 for a long time, check
binlog file gap between relay and syncer to figure out which unit the latency mainly exists in. If this value is usually 0, the latency might exist in the relay log unit. Then you can refer to relay log unit to resolve this issue; otherwise, continue checking the Binlog replication unit.
The Binlog replication unit decides whether to read the binlog event from the upstream MySQL/MariaDB or from the relay log file according to the configuration. The related performance metric is
read binlog event duration, which generally ranges from a few microseconds to tens of microseconds.
If DM's Binlog replication processing unit reads the binlog event from upstream MySQL/MariaDB, to locate and resolve the issue, refer to read binlog data in the "relay log unit" section.
If DM's Binlog replication processing unit reads the binlog event from the relay log file, when
binlog event sizeis not too large, the value of
read binlog event durationshould be microseconds. If
read binlog event durationis too large, check the read performance of the disk. To avoid low write performance, use local SSDs for DM-worker.
The Binlog replication unit constructs DML, parses DDL, and performs table router conversion from binlog event data. The related metric is
transform binlog event duration.
The duration is mainly affected by the write operations upstream. Take the
INSERT INTO statement as an example, the time consumed to convert a single
VALUES greatly differs from that to convert a lot of
VALUES. The time consumed might range from tens of microseconds to hundreds of microseconds. However, usually this is not a bottleneck of the system.
When the Binlog replication unit writes the converted SQL statements to the downstream, the related performance metrics are
DML queue remain length and
transaction execution latency.
After constructing SQL statements from binlog event, DM uses
worker-count queues to concurrently write these statements to the downstream. However, to avoid too many monitoring entries, DM performs the modulo
8 operation on the IDs of concurrent queues. This means that all concurrent queues correspond to one item from
DML queue remain length indicates in the concurrent processing queue, the number of DML statements that have not been consumed and have not started to be written downstream. Ideally, the curves corresponding to each
q_* are almost the same. If not, it indicates that the concurrent load is extremely unbalanced.
If the load is not balanced, confirm whether tables need to be migrated have primary keys or unique keys. If these keys do not exist, add the primary keys or the unique keys; if these keys do exist while the load is not balanced, upgrade DM to v1.0.5 or later versions.
When there is no noticeable latency in the entire data migration link, the corresponding curve of
DML queue remain lengthis almost always 0, and the maximum does not exceed the value of
batchin the task configuration file.
If you find a noticeable latency in the data migration link, and the curve of
DML queue remain lengthcorresponding to each
q_*is almost the same and is almost always 0, it means that DM fails to read, convert, or concurrently write the data from the upstream in time (the bottleneck might be in the relay log unit). For troubleshooting, refer to the previous sections of this document.
If the corresponding curve of
DML queue remain length is not 0 (usually the maximum is not more than 1024), it indicates that there is a bottleneck when writing SQL statements to the downstream. You can use
transaction execution latency to view the time consumed to execute a single transaction to the downstream.
transaction execution latency is usually tens of milliseconds. If this value is too large, check the downstream performance based on the monitoring of the downstream database. You can also check whether there is a large network latency between DM and the downstream database.
To view the time consumed to write a single statement such as
COMMIT to the downstream, you can also check
statement execution latency.