Quickstart Guide: Using Terrier for Experiments

If you are interested in using Terrier straight-away in order to index and retrieve from standard test collections, then you may follow the steps described below. We provide step-by-step instructions for the installation of Terrier on Linux/Mac/Unix and Windows operating systems and guide you through your first indexing and retrieval steps on a test collection.

Terrier Requirements

Terrier’s single requirement consists of an installed Java JRE 11 or higher. You can download the JRE, or the JDK (if you want to develop with Terrier, or run the web-based interface), from the Java website.

Download Terrier

Terrier can be obtained from its download page. The site offers pre-compiled releases of the newest and previous Max/Linux/Unix (.tar.gz) and Windows (.zip) downloads of Terrier.

Step by Step Unix Installation

After having downloaded Terrier, copy the file to the directory where you want to install Terrier. Navigate to this directory and execute the following command to decompress the distribution:

tar -zxvf terrier-project-5.6-bin.tar.gz

This will result in the creation of a terrier-project directory in your current directory. Terrier will use the java command in your $PATH, if there is one, or otherwise will resort to looking in $JAVA_HOME. To check that java is in your path, type:

java -version

We are looking for Java version 11 or greater. If the java command is not found, you may have to install the Java, or ensure that the $JAVA_HOME directory to point to your Java installation. If your system does not meet these requirements you can download Java from the Java or OpenJDK websites. If necessary, set the environment variable by including the following line either in your ~/.bashrc file:

export JAVA_HOME=<absolute-path-of-java-installation>

e.g.

export JAVA_HOME=/usr/java/latest

Step by Step Windows Installation

In order to be able to use Terrier on Windows you simply have to extract the contents of the downloaded .zip file into a directory of your choice. Terrier requires Java version 11 or higher. If your system does not meet this requirement you can download an appropriate version from the Java or OpenJDK websites. Finally, Terrier assumes that java.exe is on the path, so you should use the System applet in the control panel, to ensure that your Java\bin folder is in your PATH environment variable.

The following instructions are equally applicable to Windows, with the exception that the script filenames are suffixed by .bat.

Using Terrier

Terrier has a number of in-built commands. All of these can be accessed through the in-built terrier command-line script. While in Terrier’s directory, type bin/terrier to see the available commands (bin\terrier.bat on Windows):

$ bin/terrier 
Terrier version 5.6
No command specified. You must specify a command.
Popular commands:
	batchevaluate	evaluate all run result files in the results directory
	batchindexing	allows a static collection of documents to be indexed
	batchretrieval	performs a batch retrieval "run" over a set of queries
	help		provides a list of available commands
	interactive	runs an interactive querying session on the command-line

All possible commands:
	batchevaluate	evaluate all run result files in the results directory
	batchindexing	allows a static collection of documents to be indexed
	batchretrieval	performs a batch retrieval "run" over a set of queries
	help		provides a list of available commands
	help-aliases	provides a list of all available commands and their aliases
	http		runs a simple JSP webserver, to serve results
	indexstats	display the statistics of an index
	indexutil	utilities for displaying the content of an index
	interactive	runs an interactive querying session on the command-line
	inverted2direct	makes a direct index from a disk index with only an inverted index
	jforests	runs the Jforests LambdaMART LTR implementation
	recompress	allows an inverted index to be recompressed, changing compression
	rest-singleindex	starts a HTTP REST server to serve a single index
	showdocument	displays the contents of a document
	structuremerger	merges 2 disk indices
	trec_eval	runs the NIST standard trec_eval tool

See 'terrier help <command>' to read about a specific command.

Batch Indexing and Retrieval using Terrier

This allows you to easily index, retrieve, and evaluate results on TREC collections. In the next session, we provide you with a step-by-step tutorial of how to use this application.

Interactive Terrier

This allows you to to do interactive retrieval. This is a quick way to test Terrier. If you have installed Terrier on Windows, you can start Interactive Terrier by executing the bin/terrier.bat interactive command. On a Unix system or Mac, you can run interactive Terrier by executing the bin/terrier interactive command. You can configure the retrieval functionalities of Interactive Terrier using properties described in the InteractiveQuerying class.

Desktop Terrier

A sample desktop search application (built using the Swing UI technology) is packaged separately, but can be automatically installed and used from Terrier using the following command:

bin/terrier -Dterrier.mvn.coords=org.terrier:terrier-desktop:5.0 desktop

The desktop search application’s source is available separately from Github.

Tutorial: How to use the Batch (TREC) Terrier

Indexing

This guide will provide step-by-step instructions for using Terrier to index a TREC collection. We assume that the operating system is Linux, and that the collection, along with the topics and the relevance assessments (qrels), are stored in the directory share/vaswani_npl/.

  1. Go to the Terrier folder.
    cd terrier-project-5.6
  1. Setup Terrier for using a TREC test collection by using the trec_setup script (trec_setup.bat on Windows)
  bin/trec_setup <absolute-path-to-collection-files>

In our example we are using a collection called VASWANI_NPL located at share/vaswani_npl/. It follows the format of a traditional TREC test collection, with a corpus file, topics, and relevance assessments (qrels), all using the same TREC format.

$head share/vaswani_npl/corpus/doc-text.trec
<DOC>
<DOCNO>1</DOCNO>
compact memories have flexible capacities  a digital data storage
system with capacity up to bits and random and or sequential access
is described
</DOC>

To setup for this corpus, run:

bin/trec_setup share/vaswani_npl/corpus/

This will result in the creation of a collection.spec file in the etc directory. This file contains a list of the document files contained in the specified corpus directory.

  1. If necessary, check/modify the collection.spec file. This might be required if the collection directory contained files that you do not want to index (READMEs, etc).
  2. Now we are ready to begin the indexing of the collection. This is achieved using the batchindexing command of the terrier script, as follows:
$bin/terrier batchindexing
16:00:03.028 [main] INFO  o.terrier.indexing.CollectionFactory - Finished reading collection specification
16:00:03.046 [main] INFO  o.t.i.MultiDocumentFileCollection - TRECCollection 0% processing share/vaswani_npl/corpus//doc-text.trec
16:00:03.116 [main] INFO  o.t.structures.indexing.Indexer - creating the data structures data_1
16:00:04.885 [main] INFO  o.t.structures.indexing.Indexer - Collection #0 took 1 seconds to index (11429 documents)
16:00:04.918 [main] INFO  o.t.s.indexing.LexiconBuilder - 6 lexicons to merge
16:00:05.045 [main] INFO  o.t.s.indexing.LexiconBuilder - Optimising structure lexicon
16:00:05.047 [main] INFO  o.t.structures.FSOMapFileLexicon - Optimising lexicon with 7756 entries
16:00:05.761 [main] INFO  o.t.structures.indexing.Indexer - Started building the inverted index...
16:00:05.761 [main] INFO  o.t.structures.indexing.Indexer - Started building the inverted index...
16:00:05.766 [main] INFO  o.t.s.i.c.InvertedIndexBuilder - Iteration 1 of 1 iterations
16:00:06.929 [main] INFO  o.t.s.indexing.LexiconBuilder - Optimising structure lexicon
16:00:06.930 [main] INFO  o.t.structures.FSOMapFileLexicon - Optimising lexicon with 7756 entries
16:00:06.954 [main] INFO  o.t.structures.indexing.Indexer - Finished building the inverted index...
16:00:06.954 [main] INFO  o.t.structures.indexing.Indexer - Time elapsed for inverted file: 1

With Terrier’s default settings, the resulting index will be created in the var/index folder within the Terrier installation folder.

Note: If you do not need the direct index structure, e.g. for query expansion, then you can use bin/terrier batchindexing -j for the faster single-pass indexing.

Once indexing completes, you can verify your index by obtaining its statistics, using the indexstats command of Terrier.

$bin/terrier indexstats
16:21:45.086 [main] INFO  org.terrier.applications.TrecTerrier - Collection statistics:
16:21:45.088 [main] INFO  org.terrier.applications.TrecTerrier - number of indexed documents: 11429
16:21:45.088 [main] INFO  org.terrier.applications.TrecTerrier - size of vocabulary: 7756
16:21:45.088 [main] INFO  org.terrier.applications.TrecTerrier - number of tokens: 271581
16:21:45.089 [main] INFO  org.terrier.applications.TrecTerrier - number of pointers: 224573

This displays the number of documents, number of tokens, number of terms, found in the created index.

Querying

Firstly, let’s see if we can obtain search results from our index. We can use the bin/terrier interactive command to query the index for results.

$bin/terrier interactive
16:30:07.139 [main] INFO  o.t.structures.CompressingMetaIndex - Structure meta reading lookup file into memory
16:30:07.146 [main] INFO  o.t.structures.CompressingMetaIndex - Structure meta loading data file into memory
16:30:07.152 [main] INFO  o.t.applications.InteractiveQuerying - time to intialise index : 0.086
Please enter your query: compressed
16:30:26.624 [main] INFO  o.t.matching.PostingListManager - Query 1 with 1 terms has 1 posting lists

	Displaying 1-22 results
0 11196 6.965311483754079
1 6891 6.861351572397433
2 8706 6.6285666210018395
3 6812 6.419975936835514
4 3286 6.0561185692309065
5 4007 5.744292373685925
6 70 5.603313027948017
...
Please enter your query: exit

In responding to the query compressed, Terrier estimated document 11196 to be most relevant, scoring 6.96. 11196 was recorded from the DOCNO tag of the corresponding document.

Batch Retrieval

Information retrieval has a history of evaluating search effectiveness automatically, using many queries with associated relevance assessments, in a batch manner. In order to perform batch retrieval using an existing index, follow the steps described below.

  1. First of all we have to do some configuration. Much of Terrier’s functionality is controlled by properties. You can pre-set these in the etc/terrier.properties file, or specify each on the command-line. Some commonly used properties have short options to set these on the command-line (use bin/terrier help <command> to see these). To perform retrieval and evaluate the results of a batch of queries, we need to know:

    a. The location of the queries (also known as topic files) - specified using the trec.topics property, or the short -t command-line option to batchretrieve.

    b. The weighting model (e.g. TF_IDF) to use - specified using trec.model property or the -w option to batchretrieve. The default weighting model for Terrier is DPH.

    c. The corresponding relevance assessments file (or qrels) for the topics - specified by trec.qrels or -q option to batchevaluate.

  2. Let’s do a retrieval run. The batchretrieve command instructs Terrier to do a batch retrieval run, i.e. retrieving the documents estimated to be the most relevant for each query in the topics file. However, instead of having the trec.topics property set in the terrier.properties file, we specify it on the command-line using the -t option (all other configuration will remain using Terrier’s default settings):

    $bin/terrier batchretrieve -t share/vaswani_npl/query-text.trec
    ...
    16:14:43.440 [main] INFO  o.t.matching.PostingListManager - Query 93 with 10 terms has 10 posting lists
    16:14:43.444 [main] INFO  o.t.a.batchquerying.TRECQuerying - Time to process query: 0.006
    16:14:43.461 [main] INFO  o.t.a.batchquerying.TRECQuerying - Settings of Terrier written to var/results/DPH_0.res.settings
    16:14:43.461 [main] INFO  o.t.a.batchquerying.TRECQuerying - Finished topics, executed 93 queries in 0.866 seconds, results written to var/results/DPH_0.res
    Time elapsed: 0.987 seconds.

This will result in a .res file in the var/results directory called DPH_0.res. We call each .res file a run, and contains Terrier’s answers to each of the 93 queries.

You can also configure more options on the command-line, including arbitrary properties using the -D option to any Terrier command. So the following two commands are equivalent:

$bin/terrier batchretrieve -w BM25 -c bm25.b:0.4 -t share/vaswani_npl/query-text.trec
$bin/terrier batchretrieve -Dtrec.model=BM25 -c bm25.b:0.4 -Dtrec.topics=share/vaswani_npl/query-text.trec

We have instructed Terrier to perform retrieval using the BM25 weighting model – BM25 is a classical Okapi model firstly defined by Stephen Robertson, instead of the default DPH, which is a Divergence From Randomness weighting model (to learn more, see the description of the DFR framework). -c bm25.b:0.4 instructs Terrier to use the value 0.4 as the b parameter value for the weighting model. Note - if you do not specify bm25.b:0.4, then the default parameter value will be used for that weighting model.

The parameters of NB: The parameters of other weighting models can be set using other similar controls - for instance, some DFR weighting models will respond to a “dfr.c” control.

  1. Now we will evaluate the obtained results by using the batchevaluate command:
    $bin/terrier batchevaluate -q share/vaswani_npl/qrels
    16:27:28.527 [main] INFO  o.t.evaluation.TrecEvalEvaluation - Evaluating result file: var/results/DPH_0.res
    Average Precision: 0.2836

Terrier will look at the var/results directory, evaluate each .res file and save the output in a .eval file named exactly the same as the corresponding .res file.

  1. We can change the retrieval approach used by Terrier to perform retrieval. For instance, query expansion (QE) can enabled by using the -q option.
bin/terrier batchretrieve -q

See the guide for configuring retrieval for more information about QE. Note that your index must have a direct index structure to support QE, which is not built by default with single-pass indexing (see Configuring Indexing for more information). Query expansion has various configurable properties - see Configuring Retrieval for more details.

Afterwards we can run the evaluation again by using batchevaluate comand.

bin/terrier batchevaluate -q share/vaswani_npl/qrels
  1. Now we can look at all the Mean Average Precision (MAP) values of the runs by inspecting the .eval files in var/results:

The obtained MAP for DPH should be 0.2836. The obtained MAP for BM25 should be 0.2992. The obtained MAP for DPH with query expansion should be 0.2992.

Interacting with Terrier

You can interact with your index using a Web-based querying interface. Firstly, start the included HTTP server:

$bin/terrier http

You can then enter queries and view results at http://localhost:8080 (If you are running Terrier on another machine, replace localhost with the hostname of the remote machine). Terrier can provide more information in the search results – for more information on configuring the Web interface, please see Using Web-based results.


Webpage: http://terrier.orgContact: School of Computing ScienceCopyright (C) 2004-2020 University of Glasgow. All Rights Reserved.