JDBC Configuration Options

Use the following parameters to configure the Kafka Connect for HPE Ezmeral Data Fabric Streams JDBC connector; they are modified in the quickstart-sqlite.properties file.

Configuration Modes

In standalone mode, JDBC connector configuration is specified in the quickstart-sqlite.properties file. Additional configurations such as the offset storage location and the port for the REST interface are specified in the connect-standalone.properties file. See Configuring in Standalone Mode.

/opt/mapr/kafka-connect-jdbc/kafka-connect-jdbc-<version>/etc/kafka-connect-jdbc/quickstart-sqlite.properties
/opt/mapr/kafka/kafka-<version>/config/connect-standalone.properties

In distributed mode, HDFS connector configuration is provided in the POST and PUT requests when creating or modifying the connector. See POST /connectors and PUT /connectors/(string:name)/config for more information about using the REST API. Additional configurations such as defining the topics that will store the connector state, task configuration state, and connector offset state are specified in the connect-distributed.properties file. See Configuring in Distributed Mode .

/opt/mapr/kafka/kafka-<version>/config/connect-distributed.properties

JDBC Source Configuration Options

Table 1. JDBC Source configuration parameters
Parameters	Description
connection.url	JDBC connection URL for the database to load. Type: string Default: “”
connection.user	JDBC connection user. Type: string Default: NULL
connection.password	JDBC connection password. Type: password Default: NULL
connection.attempts	Maximum number of attempts to retrieve a valid JDBC connection. Type: int Default: 3
connection.backoff.ms	Backoff time in milliseconds between connection attempts. Type: long Default: 10000
table.whitelist	List of tables to include in copying. If specified, table.blacklist may not be set. Type: list Default: []
table.blacklist	List of tables to exclude from copying. If specified, table.whitelist may not be set. Type: list Default: []
numeric.precision.mapping	Whether or not to attempt mapping numeric values by precision to integral types. Type: boolean Default: false
schema.pattern	Schema pattern to fetch table metadata from the database. `""` - Retrieves those without a schema. `*` - NULL (default) means that the schema name should not be used to narrow the search, all tables metadata would be fetched, regardless their schema.
mode	The mode for updating a table each time it is polled. Options include: 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. Type: string Default: “” Valid Values: [, bulk, timestamp, incrementing, timestamp+incrementing] 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 autoincrementing column. This column may not be nullable. Type: string Default: “” NOTE If you are using Hive JDBC with incrementing or timestamp mode, you should set the `validate.non.null` property to false because there are no "not null" columns in Hive.
timestamp.column.name	The name of the timestamp column to use to detect new or modified rows. This column may not be nullable. Type: string Default: “”
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 NOTE If this parameter is false, specify exactly all columns that need to be imported to HPE Ezmeral Data Fabric Streams in the query parameter. For example instead of `"query" : "select * from table"`, use `"query" : "select col1, col2 from table"`
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: “”
query	If specified, the query to perform to select new or updated rows. Use this setting to join tables, select subsets of columns in a table, or filter data. If used, this connector will only copy data using this query – whole-table copying will be disabled. Different query modes may still be used for incremental updates, but in order to properly construct the incremental query, it must be possible to append a WHERE clause to this query (i.e. no WHERE clauses may be used). If you use a WHERE clause, it must handle incremental queries itself. Type: string Default: “”
poll.interval.ms	Frequency (milliseconds) to poll for new data in each table. Type: int Default: 5000
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
table.poll.interval.ms	Frequency (milliseconds) 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
topic.prefix	Prefix to prepend to table names to generate the name of the Kafka topic to publish data to, or in the case of a custom query, the full name of the topic to publish to. For example: `/path/to/stream:topic-prefix-`. Type: string Default: “”
table.types	By default, the JDBC connector will only detect tables with type TABLE from the source Database. This config allows a command separated list of table types to extract. Options include: TABLE VIEW SYSTEM TABLE GLOBAL TEMPORARY LOCAL TEMPORY ALIAS SYNONYM Typically, TABLE or VIEW are used. Type: list Default: TABLE
timestamp.delay.interval.ms	How long to wait after a row with certain timestamp appears before it is included in the result. You may choose to add some delay to allow transactions with earlier timestamp to complete. The first execution fetches all available records (for example, starting at timestamp 0) until the current time minus the delay. Every following execution retrieves data from the last time data was fetched until the current time minus the delay. Type: long Default: 0

JDBC Sink Configuration Options

Table 2. JDBC Sink configuration parameters
Parameters	Description
connection.url	JDBC connection URL. Type: string Default: “”
connection.user	JDBC connection user. Type: string Default: NULL
connection.password	JDBC connection password. Type: password Default: NULL
insert.mode	The insertion mode to use. INSERT - Use standard SQL INSERT statements. UPSERT - Use the appropriate upsert semantics for the target database if it is supported by the connector. For example: INSERT or IGNORE UPDATE - Use the appropriate update semantics for the target database if it is supported by the connector. For example: UPDATE Type: string Default: INSERT Valid Values: insert, upsert, update
batch.size	Specifies how many records to attempt to batch together for insertion into the destination table, when possible. Type: int Default: 3000 Valid Values: 0,...
table.name.format	A format string for the destination table name, which may contain `${topic}` as a placeholder for the originating topic name. For example, table_${topic} for the topic `orders` maps to the table name `table_orders`. Type: string Default: ${topic}
pk.mode	The primary key mode, also refer to pk.fields documentation for interplay. Supported modes are: none - No keys utilized. kafka - Kafka coordinates are used as the PK. record_key - Field(s) from the record key are used, which may be a primitive or a struct. record_value - Field(s) from the record value are used, which must be a struct. Type: string Default: none Valid Values: none, kafka, record_key, record_value
pk.fields	List of comma-separated primary key field names. The runtime interpretation of this config depends on the pk.mode: none - Ignored as no fields are used as primary key in thes mode. kafka - Must be a trio representing the Kafka coordinates. Defaults to __connect_topic,__connect_partition,__connect_offset if empty. record_key - If empty, all fields from the key struct will be used, otherwise used to extract the desired fields - for primitive key only a single field name must be configured. record_value - If empty, all fields from the value struct will be used, otherwise used to extract the desired fields. Type: list Default: ""
fields.whitelist	List of comma-separated record value field names. If empty, all fields from the record value are utilized, otherwise used to filter to the desired fields. Note: pk.fields is applied independently in the context of which field(s) form the primary key columns in the destination database, while this configuration is applicable for the other columns. Type: list Default: ""
auto.create	Whether to automatically create the destination table based on record schema if it is found to be missing by issuing CREATE. Type: boolean Default: false
auto.evolve	Whether to automatically add columns in the table schema when found to be missing relative to the record schema by issuing ALTER. Type: boolean Default: false
max.retries	The maximum number of times to retry on errors before failing the task. Type: int Default: 10 Valid Values: 0,..
retry.backoff.ms	The time in milliseconds to wait following an error before a retry attempt is made. Type: int Default: 3000 Valid Values: 0,..

HPE Ezmeral Data Fabric – Customer-Managed 7.9.0 Documentation
Abstract	This site contains documentation for the customer-managed platform of the HPE Ezmeral Data Fabric version 7.9.0 including installation, configuration, administration, and reference content, as well as content for the associated bundled ecosystem components and drivers.
Published	November 2024
Edition	7.9.0