Running the Stream Processor
Run and manage Stream Processor images individually, or as part of a group
Simple example Docker workflow
Simple example Kubernetes workflow
For clarity in the examples below, environment variables are used to configure the pipelines; a config.yaml
file could be used as well.
Setup
Working from the following project directory:
$ ls
spec.q
With the following spec.q
:
cat spec.q
.qsp.run
.qsp.read.fromCallback[`upd]
.qsp.window.timer[00:00:05]
.qsp.write.toConsole[]
Running in Kubernetes
To deploy and run in Kubernetes using the provided Coordinator service, follow the Kubernetes configuration and deployment instructions for launching the Coordinator within the cluster. The instructions also detail how to deploy and teardown a pipeline once the Coordinator service has started.
Running in Docker Compose
The above examples can be run in Docker Compose with an appropriate Docker Compose file (docker-compose.yaml
).
Configuration to add Service Discovery or Monitoring
docker-compose.yaml
example:
version: "3.3"
services:
controller:
image: portal.dl.kx.com/kxi-sp-controller:1.10.0
ports:
- 6000:6000
environment:
- KDB_LICENSE_B64
command: ["-p", "6000"]
deploy:
restart_policy:
condition: on-failure
worker:
image: portal.dl.kx.com/kxi-sp-worker:1.10.0
ports:
- 5000
environment:
- KDB_LICENSE_B64
- KXI_SP_SPEC=/app/spec.q
- KXI_SP_PARENT_HOST=controller:6000
volumes:
- .:/app
command: ["-p", "5000"]
deploy:
restart_policy:
condition: on-failure
depends_on:
- controller
With this Docker Compose file, the Controller and Worker can be created at once with:
docker-compose up
Multiple Workers in Docker Compose
First, create a YAML file called templates.yaml
containing all common configuration for each Worker service:
services:
worker_common:
image: portal.dl.kx.com/kxi-sp-worker:1.10.0
ports:
- 5000
environment:
- KDB_LICENSE_B64
- KXI_SP_SPEC=/app/spec.q
- KXI_SP_PARENT_HOST=controller:6000
volumes:
- .:/app
command: ["-p", "5000"]
deploy:
restart_policy:
condition: on-failure
Now, we can easily create multiple Worker services in docker-compose.yaml
, each with a unique ordinal:
version: "3.3"
services:
controller:
image: portal.dl.kx.com/kxi-sp-controller:1.10.0
ports:
- 6000:6000
environment:
- KDB_LICENSE_B64
- KXI_SP_MIN_WORKERS=3
command: ["-p", "6000"]
deploy:
restart_policy:
condition: on-failure
worker_1:
extends:
file: templates.yaml
service: worker_common
environment:
- KXI_SP_ORDINAL=1
depends_on:
- controller
worker_2:
extends:
file: templates.yaml
service: worker_common
environment:
- KXI_SP_ORDINAL=2
depends_on:
- controller
worker_3:
extends:
file: templates.yaml
service: worker_common
environment:
- KXI_SP_ORDINAL=3
depends_on:
- controller
Notice that we have added a new environment variable to the Controller, KXI_SP_MIN_WORKERS
. This designates how many Workers the Controller will wait for before starting all registered Workers. Also of note is the KXI_SP_ORDINAL
environment variable for each Worker. This ordinal must be set to a unique integer for each Worker when using multiple Workers with the same Controller. See Environment Variables for more information about configuring Workers and Controllers with environment variables.
Running separate containers
Running with one Worker
First, create a kx
network and a Controller to orchestrate and manage the pipeline.
docker network create kx
docker run -it -p 6000:6000 \
--network=kx \
-e "KDB_LICENSE_B64=$KDB_LICENSE_B64" \ # Set the kdb+ license to use
--restart unless-stopped \ # Restart the Controller if it dies
portal.dl.kx.com/kxi-sp-controller:1.10.0 -p 6000
A Controller then needs Workers to orchestrate. We need to know the hostname of the Controller.
docker ps
CONTAINER ID IMAGE .. PORTS NAMES
0d05f4679db2 kxi-sp-controller:1.10.0 .. 0.0.0.0:6000->6000/tcp, :::6000->6000/tcp cranky_mclaren
Note the container ID of the Controller, and change the KXI_SP_PARENT_HOST
below to the container ID output from that command.
Bind in the project directory to make the spec available.
A Worker can be created with:
docker run -it -p 5000:5000 \
--network=kx \
-v "$(pwd)":/app \ # Bind in the project directory
-e KXI_SP_SPEC="/app/spec.q" \ # Point to the bound spec file
-e KXI_SP_PARENT_HOST="0d05f4679db2:6000" \ # Point Worker to its Controller
-e "KDB_LICENSE_B64=$KDB_LICENSE_B64" \ # Set the kdb+ license to use
--restart unless-stopped \ # Restart the Worker if it dies
portal.dl.kx.com/kxi-sp-worker:1.10.0 -p 5000
Running with multiple Workers
Rather than running the pipeline with a single Worker, some pipelines (such as those reading from Kafka or callback functions) can be parallelized by orchestrating multiple Workers.
To do this, start a new Controller with a greater number of required Workers:
$ docker run -it -p 6000:6000 \
--network=kx \
-e "KDB_LICENSE_B64=$KDB_LICENSE_B64" \
-e KXI_SP_MIN_WORKERS=3 \ # Set this pipeline to use 3 Workers
--restart unless-stopped \
portal.dl.kx.com/kxi-sp-controller:1.10.0 -p 6000
Then launch the required number of Workers. Here we use a loop to set each to a known port.
Change KXI_SP_PARENT_HOST
to the new Controller’s container ID.
for port in 5001 5002 5003;
do
docker run -it -p $port:5000 \
--network=kx \
-v "$(pwd)":/app \
-e KXI_SP_SPEC="/app/spec.q" \
-e KXI_SP_PARENT_HOST="0d05f4679db2:6000" \
-e "KDB_LICENSE_B64=$KDB_LICENSE_B64" \
portal.dl.kx.com/kxi-sp-worker:1.10.0 -p 5000
done
There will now be three Workers up and running, on ports 5001, 5002, and 5003.