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DataStax Pulsar Connector

    • Getting Started
      • About the DataStax Apache Pulsar™ Connector
        • System requirements
      • Pulsar Connector release notes
      • Installing DataStax Apache Pulsar™ Connector
      • Pulsar Connector single instance quick start
    • Guides and examples
      • Configuration
        • Configuring parallelism
        • Specify writetime timestamp column
        • Setting row-level TTL values from Pulsar fields
        • Pass Pulsar Connector settings directly to the DataStax Java driver
        • Mapping pulsar topics to database tables
          • Determining topic data structure
          • Mapping basic messages to table columns
          • Mapping a message that contain JSON fields
            • Mapping a message that contains both basic and JSON fields
            • Mapping JSON messages
          • Mapping Avro messages
          • Extract Pulsar record header values
          • Mapping messages to table that has a User Defined Type
          • Mapping a topic to multiple tables
          • Multiple topics to multiple tables
          • Provide CQL queries in mappings
          • The now() function in mappings
      • Operations
        • About operating and maintaining the DataStax Connector
        • Scaling the DataStax Apache Pulsar™ Connector
        • Changing the topic or table schema
        • Restarting the DataStax Apache Pulsar™ Connector
        • Displaying the DataStax Apache Pulsar™ Connector configuration
        • Updating the DataStax Apache Pulsar™ Connector configuration
        • Deleting the DataStax Apache Pulsar™ Connector
        • Getting the DataStax Connector status
      • Security
        • Using internal or LDAP authentication
      • DataStax Apache Pulsar™ Connector metrics
      • Troubleshooting
        • Record fails to write
        • Writing fails because of mutation size
        • Data parsing fails
        • Loading balancing datacenter is not specified
    • Reference
      • DataStax Apache Pulsar™ Connector details
      • DataStax connection
      • Pulsar topic-to-table settings
      • Converting date and times for a topic
      • Using the DataStax Apache Pulsar™ Connector with DataStax Enterprise authentication
        • Internal or LDAP authentication
      • SSL encrypted connection
      • Configure error handling
  • DataStax Pulsar Connector
  • Guides and examples
  • Configuration
  • Mapping pulsar topics to database tables
  • Multiple topics to multiple tables

Multiple topics to multiple tables

The DataStax Apache Pulsar™ Connector allows for mapping multiple topics to multiple tables in a single connector instance.

Most Apache Pulsar™ systems store all messages in the same format and DataStax Apache Pulsar™ Connect workers only support a single converter class for key and value.

In the example stocks_topic, the key is a basic string and the value is regular JSON.

key value

APPLE

{"symbol":"APPL", "value":208, "exchange":"NASDAQ", "industry":"TECH", "ts":"2018-11-26T19:26:27.483"}

EXXON MOBIL

{"symbol":"M",
"value":80,
"exchange":"NYSE",
"industry":"ENERGY",
"ts":"2018-11-26T19:26:27.483"}

GENERAL MOTORS

{"symbol":"GM", "value":38, "exchange":"NYSE", "industry":"AUTO", "ts":"2018-11-26T19:26:27.483"}

AT&T

{"symbol":"AT&T",
"value":33,
"exchange":"NYSE",
"industry":"TELECOM",
"ts":"2018-11-26T19:26:27.483"}

FORD MOTOR

{"symbol":"F", "value":10, "exchange":"NYSE", "industry":"AUTO", "ts":"2018-11-26T19:26:27.483"}

And baseball_topic has the same structure, basic key and JSON value.

key value

redsox

{"number":50,
"firstname":"mookie",
"lastname":"betts",
"street":"4 yawkey way",
"city":"boston"}

redsox

{"number":28, "firstname":"jd", "lastname":"martinez", "street":"4 yawkey way", "city":"boston"}

redsox

{"number":16,
"firstname":"andrew",
"lastname":"benintendi",
"street":"4 yawkey way",
"city":"boston"}

redsox

{"number":41, "firstname":"chris", "lastname":"sale", "street":"4 yawkey way", "city":"boston"}

redsox

{"number":24,
"firstname":"david",
"lastname":"price",
"street":"4 yawkey way",
"city":"boston"}

Map the topics into different keyspaces and tables, stocks_keyspace.stocks_table and baseball_keyspace.baseball_table.

The DataStax Schema definitions:

  • CREATE TABLE stocks_keyspace.stocks_table_by_symbol (
       symbol text,
       ts timestamp,
       exchange text,
       industry text,
       name text,
       value double,
       PRIMARY KEY (symbol, ts));
  • CREATE TABLE baseball_keyspace.baseball_table (
       team text primary key,
       number int,
       firstname text,
       lastname text,
       street text,
       city text);

In the connector configuration, add the following settings:

  • topic:
       stocks_topic:
          stocks_keyspace:
             stocks_table_by_symbol:
                mapping: 'symbol=value.symbol, ts=value.dateTime, exchange=value.exchange, industry=value.industry, name=key.name, value=value.value'
  • topic:
       baseball_topic:
          baseball_keyspace:
             baseball_table:
                mapping: 'team=key, number=value.number, firstname=value.firstname, lastname=value.lastname, street=value.street, city=value.city'
Mapping a topic to multiple tables Provide CQL queries in mappings

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