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Last pushed: 8 days ago
Short Description
Docker image for Archives Unleashed Toolkit
Full Description

docker-aut




Introduction

This is the Docker image for Archives Unleashed Toolkit. AUT documentation can be found here.

The Archives Unleashed Toolkit is part of the broader Archives Unleashed Project.

Requirements

Install the following dependencies:

  1. Docker

Use

Docker Hub

Make sure that Docker is running. Run the following command to launch the Apache Spark shell with aut available:

docker run --rm -it archivesunleashed/docker-aut

If you want to mount your own data, replace /path/to/your/data in the following command with the directory where your ARC or WARC files are contained.

docker run --rm -it -v "/path/to/your/data:/data" archivesunleashed/docker-aut

You will be brought to a Spark shell. Skip ahead to the example below.

Locally

You can also build this Docker image locally with the following steps:

  1. git clone https://github.com/archivesunleashed/docker-aut.git
  2. cd docker-aut
  3. docker build -t aut .
  4. docker run --rm -it aut

Once the build finishes, you should see:

$ docker run --rm -it aut
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
2017-12-08 00:48:47,200 [main] WARN  NativeCodeLoader - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
2017-12-08 00:48:54,049 [main] WARN  ObjectStore - Version information not found in metastore. hive.metastore.schema.verification is not enabled so recording the schema version 1.2.0
2017-12-08 00:48:54,167 [main] WARN  ObjectStore - Failed to get database default, returning NoSuchObjectException
2017-12-08 00:48:55,002 [main] WARN  ObjectStore - Failed to get database global_temp, returning NoSuchObjectException
Spark context Web UI available at http://172.17.0.2:4040
Spark context available as 'sc' (master = local[*], app id = local-1512694127862).
Spark session available as 'spark'.
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 2.1.1
      /_/

Using Scala version 2.11.8 (OpenJDK 64-Bit Server VM, Java 1.8.0_151)
Type in expressions to have them evaluated.
Type :help for more information.

scala>

Example

When the image is running, you will be brought to the Spark Shell interface. Try running the following command.

Type

:paste

And then paste the following script in:

import io.archivesunleashed.spark.matchbox._
import io.archivesunleashed.spark.rdd.RecordRDD._

val r = RecordLoader.loadArchives("/aut-resources/Sample-Data/*.gz", sc)
.keepValidPages()
.map(r => ExtractDomain(r.getUrl))
.countItems()
.take(10)

Press Ctrl+D in order to execute the script. You should then see the following:

// Exiting paste mode, now interpreting.

import io.archivesunleashed.spark.matchbox._
import io.archivesunleashed.spark.rdd.RecordRDD._
r: Array[(String, Int)] = Array((www.equalvoice.ca,4644), (www.liberal.ca,1968), (greenparty.ca,732), (www.policyalternatives.ca,601), (www.fairvote.ca,465), (www.ndp.ca,417), (www.davidsuzuki.org,396), (www.canadiancrc.com,90), (www.gca.ca,40), (communist-party.ca,39))

scala>

In this case, things are working! Try substituting your own data (mounted using the command above).

To quit Spark Shell, you can exit using <kbd>CTRL</kbd>+<kbd>c</kbd>.

Resources

This build also includes the aut resources repository, which contains NER libraries as well as sample data from the University of Toronto (located in /aut-resources).

The ARC and WARC file are drawn from the Canadian Political Parties & Political Interest Groups Archive-It Collection, collected by the University of Toronto. We are grateful that they've provided this material to us.

If you use their material, please cite it along the following lines:

You can find more information about this collection at WebArchives.ca.

Acknowlegements

This work is primarily supported by the Andrew W. Mellon Foundation. Additional funding for the Toolkit has come from the U.S. National Science Foundation, Columbia University Library's Mellon-funded Web Archiving Incentive Award, the Natural Sciences and Engineering Research Council of Canada, the Social Sciences and Humanities Research Council of Canada, and the Ontario Ministry of Research and Innovation's Early Researcher Award program. Any opinions, findings, and conclusions or recommendations expressed are those of the researchers and do not necessarily reflect the views of the sponsors.

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