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TiCDC Data Integrity Validation for Single-Row Data
Introduce the implementation principle and usage of the TiCDC data integrity validation feature.

TiCDC Data Integrity Validation for Single-Row Data

Starting from v7.1.0, TiCDC introduces the data integrity validation feature, which uses a checksum algorithm to validate the integrity of single-row data. This feature helps verify whether any error occurs in the process of writing data from TiDB, replicating it through TiCDC, and then writing it to a Kafka cluster. The data integrity validation feature only supports changefeeds that use Kafka as the downstream and currently supports the Avro protocol.

Implementation principles

After you enable the checksum integrity validation feature for single-row data, TiDB uses the CRC32 algorithm to calculate the checksum of a row and writes it to TiKV along with the data. TiCDC reads the data from TiKV and recalculates the checksum using the same algorithm. If the two checksums are equal, it indicates that the data is consistent during the transmission from TiDB to TiCDC.

TiCDC then encodes the data into a specific format and sends it to Kafka. After the Kafka Consumer reads data, it calculates a new checksum using the same algorithm as TiDB. If the new checksum is equal to the checksum in the data, it indicates that the data is consistent during the transmission from TiCDC to the Kafka Consumer.

For more information about the algorithm of the checksum, see Algorithm for checksum calculation.

Enable the feature

TiCDC disables data integrity validation by default. To enable it, perform the following steps:

  1. Enable the checksum integrity validation feature for single-row data in the upstream TiDB cluster by setting the tidb_enable_row_level_checksum system variable:

    SET GLOBAL tidb_enable_row_level_checksum = ON;

    This configuration only takes effect for newly created sessions, so you need to reconnect to TiDB.

  2. In the configuration file specified by the --config parameter when you create a changefeed, add the following configurations:

    [integrity]
integrity-check-level = "correctness"
corruption-handle-level = "warn"

  3. When using Avro as the data encoding format, you need to set enable-tidb-extension=true in the sink-uri. To prevent numerical precision loss during network transmission, which can cause checksum validation failures, you also need to set avro-decimal-handling-mode=string and avro-bigint-unsigned-handling-mode=string. The following is an example:

    cdc cli changefeed create --server=http://127.0.0.1:8300 --changefeed-id="kafka-avro-checksum" --sink-uri="kafka://127.0.0.1:9092/topic-name?protocol=avro&enable-tidb-extension=true&avro-decimal-handling-mode=string&avro-bigint-unsigned-handling-mode=string" --schema-registry=http://127.0.0.1:8081 --config changefeed_config.toml

    With the preceding configuration, each message written to Kafka by the changefeed will include the corresponding data's checksum. You can verify data consistency based on these checksum values.

    Note:

    For existing changefeeds, if avro-decimal-handling-mode and avro-bigint-unsigned-handling-mode are not set, enabling the checksum validation feature might cause schema compatibility issues. To resolve this issue, you can modify the compatibility type of the Schema Registry to NONE. For more details, see Schema Registry.

Disable the feature

TiCDC disables data integrity validation by default. To disable this feature after enabling it, perform the following steps:

  1. Follow the Pause Task -> Modify Configuration -> Resume Task process described in Update task configuration and remove all [integrity] configurations in the configuration file specified by the --config parameter of the changefeed.

    [integrity]
integrity-check-level = "none"
corruption-handle-level = "warn"

  2. Execute the following SQL statement in the upstream TiDB to disable the checksum integrity validation feature (tidb_enable_row_level_checksum):

    SET GLOBAL tidb_enable_row_level_checksum = OFF;

    The preceding configuration only takes effect for newly created sessions. After all clients writing to TiDB have reconnected, the messages written by changefeed to Kafka will no longer include the checksum for the corresponding data.

Algorithm for checksum calculation

The pseudocode for the checksum calculation algorithm is as follows:

fn checksum(columns) {
    let result = 0
    for column in sort_by_schema_order(columns) {
        result = crc32.update(result, encode(column))
    }
    return result
}

  • columns should be sorted by column ID. In the Avro schema, fields are already sorted by column ID, so you can directly use the order in columns.

  • The encode(column) function encodes the column value into bytes. Encoding rules vary based on the data type of the column. The specific rules are as follows:

    • TINYINT, SMALLINT, INT, BIGINT, MEDIUMINT, and YEAR types are converted to UINT64 and encoded in little-endian. For example, the number 0x0123456789abcdef is encoded as hex'0x0123456789abcdef'.

    • FLOAT and DOUBLE types are converted to DOUBLE and then encoded as UINT64 in IEEE754 format.

    • BIT, ENUM, and SET types are converted to UINT64.

      • BIT type is converted to UINT64 in binary format.
      • ENUM and SET types are converted to their corresponding INT values in UINT64. For example, if the data value of a SET('a','b','c') type column is 'a,c', the value is encoded as 0b101, which is 5 in decimal.

    • TIMESTAMP, DATE, DURATION, DATETIME, JSON, and DECIMAL types are first converted to STRING and then converted to bytes.

    • CHAR, VARCHAR, VARSTRING, STRING, TEXT, and BLOB types (including TINY, MEDIUM, and LONG) are directly converted to bytes.

    • NULL and GEOMETRY types are excluded from the checksum calculation and this function returns empty bytes.

For more information about the implementation of data consumption and checksum verification using Golang, see TiCDC row data checksum verification.

Note:

  • After enabling the checksum validation feature, DECIMAL and UNSIGNED BIGINT types data will be converted to STRING types. Therefore, in the downstream consumer code, you need to convert them back to their corresponding numerical types before calculating checksum values.
  • The checksum verification process does not include DELETE events. This is because DELETE events only contain the handle key column, while the checksum is calculated based on all columns.