docker-aut

Attention

The master branch aligns with the master branch of The Archives Unleashed Toolkit. It can be unstable at times. Stable branches are available for each AUT release.

Introduction

This is the Docker image for Archives Unleashed Toolkit. AUT documentation can be found here. If you need a hand installing Docker, check out our Docker Install Instructions, and if you want a quick tutorial, check out our Toolkit Lesson.

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

Overrides

You can add any Spark flags to the build if you need too.

docker run --rm -it archivesunleashed/docker-aut:latest /spark/bin/spark-shell --packages "io.archivesunleashed:aut:0.70.1-SNAPSHOT" --conf spark.network.timeout=100000000 --conf spark.executor.heartbeatInterval=6000s

Once the build finishes, you should see:

Spark context Web UI available at http://c1c9c5ad6970:4040
Spark context available as 'sc' (master = local[*], app id = local-1565792045935).
Spark session available as 'spark'.
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 2.4.5
      /_/
         
Using Scala version 2.11.12 (OpenJDK 64-Bit Server VM, Java 1.8.0_212)
Type in expressions to have them evaluated.
Type :help for more information.

scala>

PySpark

It is also possible to start an interactive PySpark console. This requires specifying Python bindings and the aut package, both of which are included in the Docker image under /aut/target.

To lauch an interactive PySpark console:

docker run --rm -it archivesunleashed/docker-aut /spark/bin/pyspark --py-files /aut/target/aut.zip --jars /aut/target/aut-0.70.1-SNAPSHOT-fatjar.jar`

Once the build finishes you should see:

Python 3.6.9 (default, Oct 17 2019, 11:10:22) 
[GCC 8.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
20/05/29 14:21:39 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /__ / .__/\_,_/_/ /_/\_\   version 2.4.5
      /_/

Using Python version 3.6.9 (default, Oct 17 2019 11:10:22)
SparkSession available as 'spark'.
>>>

For more information, see the Archives Unleashed Toolkit with PySpark of the Toolkit README.

Example

Spark Shell (Scala)

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._

RecordLoader.loadArchives("/aut-resources/Sample-Data/*.gz", sc).webgraph().show(10)

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

// Exiting paste mode, now interpreting.

+----------+--------------------+--------------------+--------------------+     
|crawl_date|                 src|                dest|              anchor|
+----------+--------------------+--------------------+--------------------+
|  20091218|http://www.equalv...|http://www.equalv...|                    |
|  20091218|http://www.equalv...|http://www.equalv...|       RSS SUBSCRIBE|
|  20091218|http://www.equalv...|http://www.equalv...|Bulletin d’AVE - ...|
|  20091218|http://www.equalv...|http://www.equalv...|MORE ABOUT EV'S Y...|
|  20091218|http://www.equalv...|http://www.thesta...|Coyle: Honouring ...|
|  20091218|http://www.equalv...|http://gettingtot...|Getting to the Ga...|
|  20091218|http://www.equalv...|http://www.snapde...|                    |
|  20091218|http://www.libera...|http://www.libera...|Liberal Party of ...|
|  20091218|http://www.libera...|http://www.libera...|   Michael Ignatieff|
|  20091218|http://www.libera...|http://www.libera...|        Introduction|
+----------+--------------------+--------------------+--------------------+
only showing top 10 rows

import io.archivesunleashed._

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 CTRL+c.

PySpark

When the images is running, you will be brought to the PySpark interface. Try running the following commands:

from aut import *
WebArchive(sc, sqlContext, "/aut-resources/Sample-Data/*.gz").webgraph().show(10)

You should then see the following:

+----------+--------------------+--------------------+--------------------+
|crawl_date|                 src|                dest|              anchor|
+----------+--------------------+--------------------+--------------------+
|  20091218|http://www.equalv...|http://www.equalv...|                    |
|  20091218|http://www.equalv...|http://www.equalv...|       RSS SUBSCRIBE|
|  20091218|http://www.equalv...|http://www.equalv...|Bulletin d’AVE - ...|
|  20091218|http://www.equalv...|http://www.equalv...|MORE ABOUT EV'S Y...|
|  20091218|http://www.equalv...|http://www.thesta...|Coyle: Honouring ...|
|  20091218|http://www.equalv...|http://gettingtot...|Getting to the Ga...|
|  20091218|http://www.equalv...|http://www.snapde...|                    |
|  20091218|http://www.libera...|http://www.libera...|Liberal Party of ...|
|  20091218|http://www.libera...|http://www.libera...|   Michael Ignatieff|
|  20091218|http://www.libera...|http://www.libera...|        Introduction|
+----------+--------------------+--------------------+--------------------+
only showing top 10 rows

>>>

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

To quit the PySpark console, you can exit using CTRL+c.

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:

• University of Toronto Libraries, Canadian Political Parties and Interest Groups, Archive-It Collection 227, Canadian Action Party, http://wayback.archive-it.org/227/20051004191340/http://canadianactionparty.ca/Default2.asp

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.