Skip to content

Latest commit

 

History

History
101 lines (69 loc) · 3.33 KB

README.md

File metadata and controls

101 lines (69 loc) · 3.33 KB
Raw

Simple Dockerized AsterixDB

This projects aims to make it easy to get started with AsterixDB. It is based on Docker and Docker compose. Currently, the following features are supported:

  • The sample cluster (which consists of one cluster controller and two node controllers) in a single container
  • HDFS (with name node and data nodes in their own respective containers)
  • External tables on S3

Starting AsterixDB without HDFS

If you do not need HDFS, you can use the docker image without docker-compose:

docker run --rm -it -p 19002:19002 -p 19006:19006 ingomuellernet/asterixdb

Starting AsterixDB with HDFS

The following should be enough to bring up all required services:

docker-compose up

Varying the number of HDFS Data Nodes

To change the number of HDFS data nodes, use the --scale flag of docker-compose:

docker-compose up --scale datanode=3

Building the Image Locally

Above command uses a pre-built docker image. If you want the image to be build locally, do the following instead:

docker-compose --file docker-compose-local.yml up

If you are behind a corporate firewall, you will have to configure Maven (which is used to build part of AsterixDB) as follows before running above command:

export MAVEN_OPTS="-Dhttp.proxyHost=your.proxy.com -Dhttp.proxyPort=3128 -Dhttps.proxyHost=your.proxy.com -Dhttps.proxyPort=3128"

Uploading Data to HDFS

The data/ folder is mounted into the HDFS namenode container, from where you can upload it using the HDFS client in that container (docker-asterixdb_namenode_1 may have a different name on your machine; run docker ps to find out):

docker exec -it docker-asterixdb_namenode_1 hadoop fs -mkdir /dataset
docker exec -it docker-asterixdb_namenode_1 hadoop fs -put /data/file.parquet /dataset/
docker exec -it docker-asterixdb_namenode_1 hadoop fs -ls /dataset

Running Queries

Once started, you should be able to use the server by accssing http://localhost:19006. Alternatively, the REST API is accessible on the standard port.

Creating an External Table on HDFS

Suppose you have the following file test.json:

{"s": "hello world", "i": 42}

Upload it to /dataset/test.json on HDFS as described above. Then run the following in the web interface:

CREATE TYPE t1 AS OPEN {};

CREATE EXTERNAL DATASET TestHdfs(t1)
USING hdfs (
  ("hdfs"="hdfs://namenode:8020"),
  ("path"="/dataset/test.json"),
  ("input-format"="text-input-format"),
  ("format"="json")
);

Creating an External Table on S3

Suppose you have stored test.json from above on s3://my-bucket-name/test.json in the eu-west-1 region on S3. Then the following command creates an external table based on that file:

CREATE TYPE t1 AS OPEN {};  -- omit if type exists already

CREATE EXTERNAL DATASET TestS3(t1)
USING S3 (
  ("accessKeyId"="YOURACCESSKEYID"),
  ("secretAccessKey"="YOURSECRETACCESSKEY"),
  ("region"="eu-west-1"),
  ("serviceEndpoint"="https://s3.eu-west-1.amazonaws.com:443"),
  ("container"="my-bucket-name"),
  ("definition"="test.json"),
  ("format"="json")
);