Note

This documentation is for a prior release of Kinetica. For the latest documentation, click here.

NiFi Connector Developer Manual

The following guide provides step by step instructions to get started using Kinetica as a data source to read from and write to. Source code for the connector can be found at:

Building the Kinetica NiFi Connector

The connector jar can be built with Maven.

  1. Download the connector source:

    $ git clone https://github.com/kineticadb/kinetica-connector-nifi.git
$ cd kinetica-connector-nifi

  2. If using a version of NiFi other than 1.3.0, update the pom.xml file with the correct version of NiFi in this block:

    <parent>
    <groupId>org.apache.nifi</groupId>
    <artifactId>nifi-nar-bundles</artifactId>
    <version>1.3.0</version>
</parent>

  3. Build the connector jar:

    $ mvn clean package

Installing the Kinetica NiFi Connector into NiFi

Deploy the connector jar built in the previous step to the NiFi libraries directory:

$ cp nifi-GPUdbNiFi-nar/target/nifi-GPUdbNiFi-nar-1.3.0.nar <NiFiHome>/lib

Getting Streaming Data from Kinetica to JSON or CSV Files

  1. Drag a new Processor onto the flow
    • Select the GetKineticaToJSON or GetKineticaToCSV type
  2. Properties tab
    • Server URL: The URL of the Kinetica instance you are using. This will be:
      • Format: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0
      • Example: https://abcdefg.cloud.kinetica.com/hijklmn/gpudb-0;CombinePrepareAndExecute=1;RowsPerFetch=20000
    • Table Name: The name of the table to read from
    • Table Monitor URL: The URL Kinetica will be using to forward any new data inserted into the above table. This will be:
      • Format: tcp://<aws.fqdn>:9002/
      • Example: tcp://abcdefg.cloud.kinetica.com:9002/
    • Delimiter: For CSVs, the delimiter used in the file (e.g., comma, tab, pipe, etc.); defaults to tab
    • Username: Kinetica login username
    • Password: Kinetica login password

The output of GetKineticaToJSON is a JSON file containing the record inserted into the Kinetica table.

The output of GetKineticaToCSV is a CSV file containing the record inserted into the Kinetica table.

Saving Data to Kinetica Using NiFi Attributes

  1. Drag a new Processor onto the flow:

    • Select the PutKinetica type

  2. Settings tab:

    • Under Auto terminate Relationships, check the failure and success options.

  3. Properties tab:

    • Server URL: The URL of the Kinetica instance you are using. This will be:

      • Format: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0
      • Example: https://abcdefg.cloud.kinetica.com/hijklmn/gpudb-0;CombinePrepareAndExecute=1;RowsPerFetch=20000

    • Collection Name: Set this value if you want the table created in a collection.

    • Table Name: The name of the table to write to

    • Schema: A CSV string, where each entry is:

      • Format: <fieldname>|<data type>[|<subtype>]

      • Example:

        X|Float|data,Y|Float|data,TIMESTAMP|Long|data,TEXT|String|store_only|text_search

      For more details on schemas, read the Kinetica documentation.

    • Batch Size: The size of the batch to compress for efficient loading

    • Username: Kinetica login username

    • Password: Kinetica login password

    • Update on Existing PK: If a primary key (PK) is defined for a table, then there are two options for handling each new record pending insert that has a PK value matching an existing record in the target table. If set to true, the record in the target table will be updated with the new record's values; if false, the new record will be discarded; defaults to false

    • Replicate Table: If true, the target table will be replicated; if false, the table will be distributed; defaults to false

    • Date Format: The date format to use to parse values in any datetime fields (e.g., dd-MM-yyyy hh:mm:ss)

    • TimeZone: Provide the timezone if the date is not from your local timezone

  4. Specifying data to be saved into Kinetica:

    • Place processors upstream from this which assigns values to user-defined attributes named <field name>, where <field name> is the name of a field in your table
    • Each record written to your table will contain field values of:
      • the value in the attributes with names <field name> or
      • the value of null if no attribute is found with that field name

Saving Data to Kinetica Using Delimited Files

  1. Drag a new Processor onto the flow

    • Select the PutKineticaFromFile type

  2. Settings tab:

    • Under Auto terminate Relationships, check the failure and success options.

  3. Properties tab:

    • Server URL: The URL of the Kinetica instance you are using. This will be:

      • Format: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0
      • Example: https://abcdefg.cloud.kinetica.com/hijklmn/gpudb-0;CombinePrepareAndExecute=1;RowsPerFetch=20000

    • Collection Name: Set this value if you want the table created in a collection.

    • Table Name: The name of the table to write to

    • Schema: A CSV string, where each entry is:

      • Format: <fieldname>|<data type>[|<subtype>]

      • Example:

        X|Float|data,Y|Float|data,TIMESTAMP|Long|data,TEXT|String|store_only|text_search

      For more details on schemas, read the Kinetica documentation.

    • Delimiter: The delimiter used in the file (e.g., comma, tab, pipe, etc.); defaults to ,

    • Escape Character: The character used to escape other characters in the data (e.g., \); defaults to "

    • Quote Character: The character used to quote column data in the file (e.g., " or '); defaults to "

    • File Has Header: Whether the first line of the file is a header row or not; defaults to true

    • Batch Size: The size of the batch to compress for efficient loading

    • Error Handling: If true, the processor will skip rows that can't be loaded successfully (due to parse error, etc.); if false, the processor will stop loading as soon as an error occurs; defaults to true

    • Username: Kinetica login username

    • Password: Kinetica login password

    • Update on Existing PK: If a primary key (PK) is defined for a table, then there are two options for handling each new record pending insert that has a PK value matching an existing record in the target table. If set to true, the record in the target table will be updated with the new record's values; if false, the new record will be discarded; defaults to false

    • Replicate Table: If true, the target table will be replicated; if false, the table will be distributed; defaults to false

    • Date Format: The date format to use to parse values in any datetime fields (e.g., dd-MM-yyyy hh:mm:ss)

    • TimeZone: Provide the timezone if the date is not from your local timezone

  4. Create a connector between the data source processor and the PutKineticaFromFile processor

    • Details tab: check the with coordinates option.

The input for the PutKineticaFromFile processor is a delimited file.