JDBC Source Connector Configuration Properties

To use this connector, specify the name of the connector class in the connector.class configuration property.

connector.class=io.confluent.connect.jdbc.JdbcSourceConnector

Connector-specific configuration properties are described below.

Database Connection Security

In the connector configuration you will notice there are no security parameters. This is because SSL is not part of the JDBC standard and will depend on the JDBC driver in use. In general, you will need to configure SSL using the connection.url parameter. For example, with MySQL it would look like:

connection.url="jdbc:mysql://127.0.0.1:3306/sample?verifyServerCertificate=false&useSSL=true&requireSSL=true"

Please check with your specific JDBC driver documentation on support and configuration.

Database

Note

The JDBC connector allows you to configure any driver parameter using the prefix connection.*. For example:

  • For Postgres, you can use the following:

    "connection.loginTimeout": "10"

  • For Oracle, you can use the following:

    "connection.oracle.jdbc.ReadTimeout": "45000"

For more details, see How to set JDBC driver configuration using JDBC connector.

connection.url

JDBC connection URL.

For example: jdbc:oracle:thin:@localhost:1521:orclpdb1, jdbc:mysql://localhost/db_name, jdbc:sqlserver://localhost;instance=SQLEXPRESS;databaseName=db_name

  • Type: string
  • Importance: high
  • Dependents: table.whitelist, table.blacklist
connection.user

JDBC connection user.

  • Type: string
  • Default: null
  • Importance: high
connection.password

JDBC connection password.

  • Type: password
  • Default: null
  • Importance: high
connection.attempts

Maximum number of attempts to retrieve a valid JDBC connection. Must be a positive integer.

  • Type: int
  • Default: 3
  • Valid Values: [1,…]
  • Importance: low
connection.backoff.ms

Backoff time in milliseconds between connection attempts.

  • Type: long
  • Default: 10000
  • Importance: low
catalog.pattern

Catalog pattern to fetch table metadata from the database.

  • Type: string
  • Default: null
    • "" retrieves those without a catalog
    • null (default) indicates that the schema name is not used to narrow the search and that all table metadata is fetched, regardless of the catalog.
  • Importance: medium
table.whitelist

List of tables to include in copying. If specified, table.blacklist may not be set. Use a comma-separated list to specify multiple tables (for example, table.whitelist: "User, Address, Email").

  • Type: list
  • Default: “”
  • Importance: medium
table.blacklist

List of tables to exclude from copying. If specified, table.whitelist may not be set. Use a comma-separated list to specify multiple tables (for example, table.blacklist: "User, Address, Email").

  • Type: list
  • Default: “”
  • Importance: medium
schema.pattern

Schema pattern to fetch table metadata from the database.

  • Type: string

  • Default: null

    • "" retrieves those without a schema.
    • null (default) indicates that the schema name is not used to narrow the search and that all table metadata is fetched, regardless of the schema.

  • Importance: high

    Important

    If you leave this at the default null setting, the connector may time out and fail because of the large amount of table metadata being received. Make sure to set this parameter for large databases.

numeric.precision.mapping

Whether or not to attempt mapping NUMERIC values by precision to integral types. This option is now deprecated. A future version may remove it completely. Please use numeric.mapping instead.

  • Type: boolean
  • Default: false
  • Importance: low
numeric.mapping

Map NUMERIC values by precision and optionally scale to integral or decimal types.

  • Type: string
  • Default: null
  • Valid Values: [none, precision_only, best_fit, best_fit_eager_double]
    • Use none if all NUMERIC columns are to be represented by Connect’s DECIMAL logical type.
    • Use best_fit if NUMERIC columns should be cast to Connect’s INT8, INT16, INT32, INT64, or FLOAT64 based upon the column’s precision and scale.This option may still represent the NUMERIC value as Connect DECIMAL if it cannot be cast to a native type without losing precision. For example, a NUMERIC(20) type with precision 20 would not be able to fit in a native INT64 without overflowing and thus would be retained as DECIMAL.
    • Use best_fit_eager_double if, in addition to the properties of best_fit described above, it is desirable to always cast NUMERIC columns with scale to Connect FLOAT64 type, despite potential of loss in accuracy.
    • Use precision_only to map NUMERIC columns based only on the column’s precision assuming that column’s scale is 0.
    • The none option is the default, but may lead to serialization issues with Avro since Connect’s DECIMAL type is mapped to its binary representation. best_fit is often preferred since it maps to the most appropriate primitive type.
  • Importance: low
dialect.name

The name of the database dialect that should be used for this connector. By default this is empty, and the connector automatically determines the dialect based upon the JDBC connection URL. Use this if you want to override that behavior and use a specific dialect. All properly-packaged dialects in the JDBC connector plugin can be used.

  • Type: string
  • Default: “”
  • Valid Values: [, Db2DatabaseDialect, MySqlDatabaseDialect, SybaseDatabaseDialect, GenericDatabaseDialect, OracleDatabaseDialect ,SqlServerDatabaseDialect, PostgreSqlDatabaseDialect, SqliteDatabaseDialect, DerbyDatabaseDialect , SapHanaDatabaseDialect, MockDatabaseDialect, VerticaDatabaseDialect]
  • Importance: low

Mode

mode

The mode for updating a table each time it is polled. Options include:

  • Type: string
  • Default: “”
  • Valid Values: [, bulk, timestamp, incrementing, timestamp+incrementing]
    • bulk: perform a bulk load of the entire table each time it is polled
    • incrementing: use a strictly incrementing column on each table to detect only new rows. Note that this will not detect modifications or deletions of existing rows.
    • timestamp: use a timestamp (or timestamp-like) column to detect new and modified rows. This assumes the column is updated with each write, and that values are monotonically incrementing, but not necessarily unique.
    • timestamp+incrementing: use two columns, a timestamp column that detects new and modified rows and a strictly incrementing column which provides a globally unique ID for updates so each row can be assigned a unique stream offset.
  • Importance: high
  • Dependents: incrementing.column.name, timestamp.column.name, validate.non.null
incrementing.column.name

The name of the strictly incrementing column to use to detect new rows. Any empty value indicates the column should be autodetected by looking for an auto-incrementing column. This column may not be nullable.

  • Type: string
  • Default: “”
  • Importance: medium
timestamp.column.name

Comma-separated list of one or more timestamp columns to detect new or modified rows using the COALESCE SQL function. Rows whose first non-null timestamp value is greater than the largest previous timestamp value seen will be discovered with each poll. At least one column should not be nullable.

  • Type: string
  • Default: “”
  • Importance: medium
timestamp.initial

The epoch timestamp (in milliseconds) used for initial queries that use timestamp criteria. Use -1 to use the current time. If not specified, all data will be retrieved.

  • Type: long
  • Default: null
  • Importance: low
validate.non.null

By default, the JDBC connector will validate that all incrementing and timestamp tables have NOT NULL set for the columns being used as their ID/timestamp. If the tables don’t, JDBC connector will fail to start. Setting this to false will disable these checks.

  • Type: boolean
  • Default: true
  • Importance: low
query

If specified, query can select new or updated rows. Use this setting if you want to join tables, select subsets of columns in a table, or filter data. If used, the connector copies data using this query and whole-table copying is disabled.

  • Type: string
  • Default: “”
  • Importance: medium

Tip

You can use query with a WHERE clause if you enable mode=bulk. This loads all rows from a table at each iteration. To specify a WHERE clause in other query modes, it must be possible to append a WHERE clause to the query. See Specifying a WHERE clause with query modes for a detailed explanation.

quote.sql.identifiers

When to quote table names, column names, and other identifiers in SQL statements. For backward compatibility, the default is always.

  • Type: string
  • Default: always
  • Importance: medium
query.suffix

Suffix to append at the end of the generated query.

  • Type: string
  • Default: “”
  • Importance: low
query.retry.attempts

The number of times to retry SQL exceptions encountered when executing queries.

  • Type: int
  • Default: -1
  • Importance: low
transaction.isolation.mode

The mode to control which transaction isolation level is used when running queries against the database. By default, no explicit transaction isolation mode is set. SQL_SERVER_SNAPSHOT will only work against a connector configured to write to SQL Server. Options include: DEFAULT, READ_UNCOMMITTED, READ_COMMITTED, REPEATABLE_READ, SERIALIZABLE, and SQL_SERVER_SNAPSHOT.

  • Type: string
  • Default: DEFAULT
  • Valid Values: [DEFAULT, READ_UNCOMMITED, READ_COMMITED, REPEATABLE_READ, SERIALIZABLE, SQL_SERVER_SNAPSHOT]
  • Importance: low

Connector

table.types

By default, the JDBC connector will only detect tables with type TABLE from the source Database. This config allows a comma-separated list of table types to extract.

  • Type: list.

    • TABLE
    • VIEW
    • SYSTEM TABLE
    • GLOBAL TEMPORARY
    • LOCAL TEMPORARY
    • ALIAS
    • SYNONYM

    In most cases it only makes sense to have either TABLE or VIEW.

  • Default: TABLE

  • Importance: low

poll.interval.ms

Frequency in ms to poll for new data in each table.

  • Type: int
  • Default: 5000
  • Importance: high
batch.max.rows

Maximum number of rows to include in a single batch when polling for new data. This setting can be used to limit the amount of data buffered internally in the connector.

  • Type: int
  • Default: 100
  • Importance: low
table.poll.interval.ms

Frequency in ms to poll for new or removed tables, which may result in updated task configurations to start polling for data in added tables or stop polling for data in removed tables.

  • Type: long
  • Default: 60000
  • Importance: low
topic.prefix

Prefix to prepend to table names to generate the name of the Apache Kafka® topic to publish data to, or in the case of a custom query, the full name of the topic to publish to.

  • Type: string
  • Importance: high
timestamp.delay.interval.ms

How long to wait after a row with certain timestamp appears before we include it in the result. You may choose to add some delay to allow transactions with earlier timestamp to complete. The first execution will fetch all available records (i.e. starting at timestamp 0) until current time minus the delay. Every following execution will get data from the last time we fetched until current time minus the delay.

  • Type: long
  • Default: 0
  • Importance: high
db.timezone

The name of the JDBC timezone used in the connector when querying with time-based criteria. This should be the timezone of the database as well as all the columns being queried. The value set in db.timezone will also be used for timestamp columns while pushing the records to Kafka. Defaults to UTC.

  • Type: string
  • Default: UTC
  • Valid Values: Any valid JDK time zone
  • Importance: medium
timestamp.granularity

Define the granularity of the Timestamp column. Options include:

  • Type: string
  • Default: connect_logical
  • Valid Values: [connect_logical, nanos_long, nanos_string, nanos_iso_datetime_string]
    • connect_logical (default): represents timestamp values using Kafka Connect’s built-in representations
    • nanos_long: represents timestamp values as nanos since epoch
    • nanos_string: represents timestamp values as nanos since epoch in string
    • nanos_iso_datetime_string: uses the iso format ‘yyyy-MM-dd’T’HH:mm:ss.n’
  • Importance: low

Auto topic creation

For more information about Auto topic creation, see Configuring Auto Topic Creation for Source Connectors.

Configuration properties accept regular expressions (regex) that are defined as Java regex.

topic.creation.groups

A list of group aliases that are used to define per-group topic configurations for matching topics. A default group always exists and matches all topics.

  • Type: List of String types
  • Default: empty
  • Possible Values: The values of this property refer to any additional groups. A default group is always defined for topic configurations.
topic.creation.$alias.replication.factor

The replication factor for new topics created by the connector. This value must not be larger than the number of brokers in the Kafka cluster. If this value is larger than the number of Kafka brokers, an error occurs when the connector attempts to create a topic. This is a required property for the default group. This property is optional for any other group defined in topic.creation.groups. Other groups use the Kafka broker default value.

  • Type: int
  • Default: n/a
  • Possible Values: >= 1 for a specific valid value or -1 to use the Kafka broker’s default value.
topic.creation.$alias.partitions

The number of topic partitions created by this connector. This is a required property for the default group. This property is optional for any other group defined in topic.creation.groups. Other groups use the Kafka broker default value.

  • Type: int
  • Default: n/a
  • Possible Values: >= 1 for a specific valid value or -1 to use the Kafka broker’s default value.
topic.creation.$alias.include

A list of strings that represent regular expressions that match topic names. This list is used to include topics with matching values, and apply this group’s specific configuration to the matching topics. $alias applies to any group defined in topic.creation.groups. This property does not apply to the default group.

  • Type: List of String types
  • Default: empty
  • Possible Values: Comma-separated list of exact topic names or regular expressions.
topic.creation.$alias.exclude

A list of strings representing regular expressions that match topic names. This list is used to exclude topics with matching values from getting the group’s specfic configuration. $alias applies to any group defined in topic.creation.groups. This property does not apply to the default group. Note that exclusion rules override any inclusion rules for topics.

  • Type: List of String types
  • Default: empty
  • Possible Values: Comma-separated list of exact topic names or regular expressions.
topic.creation.$alias.${kafkaTopicSpecificConfigName}

Any of the Changing Broker Configurations Dynamically for the version of the Kafka broker where the records will be written. The broker’s topic-level configuration value is used if the configuration is not specified for the rule. $alias applies to the default group as well as any group defined in topic.creation.groups.

  • Type: property values
  • Default: Kafka broker value