Loading CSV Data from Kafka

In this example, you load data from a Kafka topic named topic_for_gpkafka into a Greenplum Database table named data_from_kafka. You perform the load as the Greenplum role gpadmin. The table data_from_kafka resides in the public schema in a Greenplum database named testdb.

A producer of the Kafka topic_for_gpkafka topic emits customer expense messages in CSV format that include the customer identifier (integer), the month (integer), and an expense amount (decimal). For example, a message for a customer with identifier 123 who spent $456.78 in the month of September follows:

"123","09","456.78"

You will run a Kafka console producer to emit customer expense messages, and use the Greenplum Streaming Server gpkafka load command to transform and load the data into the data_from_kafka table and verify the load operation.

Prerequisites

Before you start this procedure, ensure that you:

Have administrative access to running Kafka and Greenplum Database clusters.
Have configured connectivity as described in the loading Prerequisites.
Identify and note the ZooKeeper hostname and port.
Identify and note the hostname and port of the Kafka broker(s).
Identify and note the hostname and port of the Greenplum Database master node.

This procedure assumes that you have installed the Apache Kafka distribution. If you are using a different Kafka distribution, you may need to adjust certain commands in the procedure.

Procedure

Create a Kafka topic named topic_for_gpkafka. For example:

kafkahost$ $KAFKA_INSTALL_DIR/bin/kafka-topics.sh --create \
    --zookeeper localhost:2181 --replication-factor 1 --partitions 1 \
    --topic topic_for_gpkafka

Open a file named sample_data.csv in the editor of your choice. For example:
```
kafkahost$ vi sample_data.csv
```

Copy/paste the following text to add CSV-format data into the file, and then save and exit:

"1313131","12","1313.13"
"3535353","11","761.35"
"7979797","10","4489.00"
"7979797","11","18.72"
"3535353","10","6001.94"
"7979797","12","173.18"
"1313131","10","492.83"
"3535353","12","81.12"
"1313131","11","368.27"

Stream the contents of the sample_data.csv file to a Kafka console producer. For example:

kafkahost$ $KAFKA_INSTALL_DIR/bin/kafka-console-producer.sh \
    --broker-list localhost:9092 \
    --topic topic_for_gpkafka < sample_data.csv

Verify that the Kafka console producer published the messages to the topic by running a Kafka console consumer. For example:

kafkahost$ $KAFKA_INSTALL_DIR/bin/kafka-console-consumer.sh \
    --bootstrap-server localhost:9092 --topic topic_for_gpkafka \
    --from-beginning

Open a new terminal window, log in to the Greenplum Database master host as the gpadmin administrative user, and set up the Greenplum environment. For example:
```
$ ssh gpadmin@gpmaster
gpmaster$ . /usr/local/greenplum-db/greenplum_path.sh
```
Construct the load configuration file. Open a file named firstload_cfg.yaml in the editor of your choice. For example:
```
gpmaster$ vi firstload_cfg.yaml
```

Fill in the load configuration parameter values based on your environment. This example assumes:

Your Greenplum Database master hostname is gpmaster.
The Greenplum Database server is running on the default port.
Your Kafka broker host and port is localhost:9092.
You want to write the Kafka data to a Greenplum Database table named data_from_kafka located in the public schema of a database named testdb.
You want to write the customer identifier and expenses data to Greenplum. You also want to calculate and write the tax due (7.25%) on the expense data. The firstload_cfg.yaml file would include the following contents:

DATABASE: testdb
USER: gpadmin
HOST: gpmaster
PORT: 5432
KAFKA:
   INPUT:
     SOURCE:
        BROKERS: localhost:9092
        TOPIC: topic_for_gpkafka
     COLUMNS:
        - NAME: cust_id
          TYPE: int
        - NAME: __IGNORED__
          TYPE: int
        - NAME: expenses
          TYPE: decimal(9,2)
     FORMAT: csv
     ERROR_LIMIT: 125
   OUTPUT:
     TABLE: data_from_kafka
     MAPPING:
        - NAME: customer_id
          EXPRESSION: cust_id
        - NAME: expenses
          EXPRESSION: expenses
        - NAME: tax_due
          EXPRESSION: expenses * .0725
   COMMIT:
     MINIMAL_INTERVAL: 2000

Create the target Greenplum Database table named data_from_kafka. For example:

gpmaster$ psql -d testdb

testdb=# CREATE TABLE data_from_kafka( customer_id int8, expenses decimal(9,2),
           tax_due decimal(7,2) );

Exit the psql subsystem:
```
testdb=# \q
```
Run the gpkafka load command to batch load the CSV data published to the topic_for_gpkafka topic into the Greenplum table. For example:
```
gpmaster$ gpkafka load --quit-at-eof ./firstload_cfg.yaml
```
The command exits after it reads all data published to the topic.
Examine the command output, looking for messages identifying the number of rows inserted/rejected. For example:
```
... -[INFO]:- ... Inserted 9 rows
... -[INFO]:- ... Rejected 0 rows
```
Run the gpkafka load command again, this time in streaming mode. For example:
```
gpmaster$ gpkafka load ./firstload_cfg.yaml
```
The command waits for a producer to publish new messages to the topic.

Navigate back to your Kafka host terminal window. Stream the contents of the sample_data.csv file to the Kafka console producer once more:

kafkahost$ $KAFKA_INSTALL_DIR/bin/kafka-console-producer.sh \
--broker-list localhost:9092 \
--topic topic_for_gpkafka < sample_data.csv

Notice the activity in your Greenplum Database master terminal window. gpkafka load consumes the new round of messages and waits.
Interrupt and exit the waiting gpkafka load command by entering Control-c in the Greenplum Database master host terminal window.

View the contents of the Greenplum Database target table data_from_kafka:

gpmaster$ psql -d testdb

testdb=# SELECT * FROM data_from_kafka WHERE customer_id='1313131' 
           ORDER BY expenses;
 customer_id | expenses | tax_due 
-------------+----------+---------
     1313131 |   368.27 |   26.70
     1313131 |   368.27 |   26.70
     1313131 |   492.83 |   35.73
     1313131 |   492.83 |   35.73
     1313131 |  1313.13 |   95.20
     1313131 |  1313.13 |   95.20
(6 rows)

The table contains two entries for each expense because the producer published the sample_data.csv file twice.