-
Go to https://www.confluent.io/download/ and download 5.1
-
Move and unpack it:
$ mv ~/Downloads/confluent-5.1.0-2.11.tar.gz ~/cp/
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[…] | |
kafka0: | |
image: "confluentinc/cp-enterprise-kafka:5.2.1" | |
ports: | |
- '9092:9092' | |
- '29094:29094' | |
depends_on: | |
- zookeeper | |
environment: |
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curl -s "http://localhost:8083/connectors"| \ | |
jq '.[]'| \ | |
peco | \ | |
xargs -I{connector_name} curl -s -XDELETE "http://localhost:8083/connectors/"{connector_name} | |
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curl -s "http://localhost:8083/connectors"| \ | |
jq '.[]'| \ | |
xargs -I{connector_name} curl -s "http://localhost:8083/connectors/"{connector_name}"/status" | \ | |
jq -c -M '[.name,.connector.state,.tasks[].state]|join(":|:")' | \ | |
column -s : -t | \ | |
sed 's/\"//g' | \ | |
sort |
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= Testing the Neo4j Connector with Twitter as a source of data | |
Caveat: I have never used Neo4j before. I'm familiar with the general concept of a property graph though. | |
Environment: https://github.com/rmoff/neo4j-streams/blob/master/kafka-connect-neo4j/docker/docker-compose.yml | |
== Start here | |
Create a Twitter source |
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{ | |
"timestamp": "1547735265961", | |
"layers": { | |
"frame": { | |
"frame_frame_interface_id": "0", | |
"frame_interface_id_frame_interface_name": "en0", | |
"frame_frame_encap_type": "1", | |
"frame_frame_time": "Jan 17, 2019 14:27:45.961581000 GMT", | |
"frame_frame_offset_shift": "0.000000000", | |
"frame_frame_time_epoch": "1547735265.961581000", |
This is a series of gists documenting testing done with the numeric.mapping
option in Kafka Connect.
- Oracle
- MS SQL Server
- Postgres
- MySQL - n/a because of #563
—@rmoff January 9, 2019
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--- | |
version: '2' | |
services: | |
zookeeper: | |
image: confluentinc/cp-zookeeper:latest | |
environment: | |
ZOOKEEPER_CLIENT_PORT: 2181 | |
ZOOKEEPER_TICK_TIME: 2000 | |
kafka: |
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# Set up some sample data: | |
docker run --interactive --rm --network ksql-troubleshooting_default \ | |
confluentinc/cp-kafkacat \ | |
kafkacat -b kafka:29092 \ | |
-t topic_with_nulls \ | |
-P <<EOF | |
{"col1":1,"col2":16000,"col3":"foo"} | |
{"col1":2,"col2":42000} | |
{"col1":3,"col2":94000,"col3":"bar"} | |
{"col1":4,"col2":12345} |
asciinema rec \
--idle-time-limit 1 \
-c "docker run --network ksql-troubleshooting_default --interactive --tty --rm confluentinc/cp-ksql-cli:5.0.0 http://ksql-server:8088" \
target.cast