Legal Informatics with AWS CloudSearch - AWS Michigan

LEGAL INFORMATICS AWS Michigan

WITH CLOUDSEARCH
October 9, 201 2

GOALS

1. Generalize information retrieval more than you’re used to.

2. Build a basic case search engine with solr/EC2.

3. Build a basic case search engine with CloudSearch.

4. Understand the relative strengths of solr and CloudSearch.

5. Discuss other legal services that CloudSearch can augment.

© Bommarito Consulting

SEARCH:
INFORMATION RETRIEVAL
 (loose – history has built silos where none might exist)

 Wiki: “[the science] of obtaining information resources
relevant to an information need from a collection of
information resources.”

 Examples:
 Search: Google, Yahoo, Bing
 Citation: MLA, Harvard Blue Book
 Classification: Dewey Decimal, LOC

We’ll start by building a basic case search engine, like Lexis or
West.


SEARCH:
INFORMATION RETRIEVAL

pages about Python
Resources Store Engine images of cats

locations near Ashley’s

• Examples:
• Store=ext2, Engine=ext2
• Store=btrfs, Engine=grep
• Store=tar, Engine=inverted index
• Store=Oracle, Engine=PL/SQL
• Store=Postgres, Engine=Sphinx


SOLR

pages about Python
Resources Lucene Solr images of cats


• All APL.
• Lucene
• The text search engine library of choice for Java developers.
• Solr
• Wraps Lucene in a blanket of RESTful goodness.
• Many other search and architectural additions as well.
• (You should know about Tika.)

• (yes, there is also ElasticSearch.)


SOLR

pages about Python
Resources Lucene Solr images of cats


Using Solr
1. Deploy and configure Solr infrastructure.
2. Configure your schema, indexing, etc.
3. Seed index with initial data.
4. If index updates, figure out how to do it without breaking things.
5. Connect to search client with REST.
6. Oops, we don’t have enough capacity for search, update volume, etc.


SOLR

OK, let’s try it.

Launch and connect to an m1.small.
mjbommar@cluster0:~$ ec2run ami-c371cdaa -t m1.small --region us-east-1 –key ec2-keypair –g tomcat
mjbommar@cluster0:~$ ec2din $INSTANCE_ID | grep ‘^INSTANCE’ | awk '{print $4}‘
mjbommar@cluster0:~$ ssh -i ~/.ssh/ec2 ubuntu@$INSTANCE_HOST

Configure a solr deployment under /opt/solr.
ubuntu@domU$ apt-get update --fix-missing && apt-get install default-jdk tomcat6
ubuntu@domU$ cd /opt
ubuntu@domU$ wget http://www.apache.org/dist/lucene/solr/4.0.0-BETA/apache-solr-4.0.0-BETA.tgz
ubuntu@domU$ tar xzf apache-solr-4.0.0-BETA.tgz
ubuntu@domU$ echo ‚SOLR_HOME=/opt/solr‛ >> /etc/environment
ubuntu@domU$ wget –O /etc/tomcat6/Catalina/localhost/solr.xml http://bommarito-
consulting.s3.amazonaws.com/legal-informatics-presentation/solr.xml
ubuntu@domU$ mkdir solr
ubuntu@domU$ cp apache-solr-4.0.0-BETA/dist/apache-solr-4.0.0-BETA.war solr/solr.war
ubuntu@domU$ cd solr


SOLR


Configure the initial collection schema and options.
ubuntu@domU$ mkdir collection1 && cd collection1
ubuntu@domU$ wget http://bommarito-consulting.s3.amazonaws.com/legal-informatics-
presentation/solr-conf-scotus.tar.gz
ubuntu@domU$ tar xzf solr-conf-scotus.tar.gz
ubuntu@domU$ less conf/solrconfig.xml
ubuntu@domU$ less conf/schema.xml

Start tomcat and make sure we’re clean.
ubuntu@domU$ chown –R tomcat6:tomcat6 /opt/solr
ubuntu@domU$ service tomcat6 restart
ubuntu@domU$ tail –f /var/log/tomcat6/catalina.out


SOLR


Schema Example
<schema name="scotus" version="1.5">
<fields>
<field name="title" type="string" indexed="true" stored="true" required="true" multiValued="false" />
<field name="content" type="text_en" indexed="true" stored="true" termVectors="true"
termPositions="true" termOffsets="true" />
</fields>
<uniqueKey>title</uniqueKey>
<types>
<fieldType name="string" class="solr.StrField" sortMissingLast="true" />
<fieldType name="text_en" class="solr.TextField" positionIncrementGap="100">
<analyzer type="index">
<tokenizer class="solr.StandardTokenizerFactory"/>
<filter class="solr.SynonymFilterFactory" synonyms="index_synonyms.txt" ignoreCase="true"
expand="false"/>
…


SOLR


Solr Config Handler Example
<requestHandler name="/query" class="solr.SearchHandler">
<lst name="defaults">
<str name="echoParams">explicit</str>
<str name="wt">json</str>
<str name="indent">true</str>
<str name="df">text</str>
</lst>
</requestHandler>


SOLR


Download sample document.
ubuntu@domU$ wget http://bommarito-consulting.s3.amazonaws.com/legal-informatics-
presentation/sample.xml

Sample File
<?xml version="1.0" encoding="UTF-8"?>
<add>
<doc>
<field name="title">Marbury v. Madison</field>
<field name="content">The clerks of the Department of State of the United States may be called
upon to give evidence of transactions in the Department which are not of a confidential
character.</field>
</doc>
</add>

POST the sample document to the Solr update handler.
ubuntu@domU$ curl –header ‘Content-Type: application/xml’ -–data-binary @sample.xml
http://localhost:8080/solr/update?commit=true


SOLR


ubuntu@domU$ curl http://localhost:8080/solr/query?q=content:confidential
{
"responseHeader":{
"status":0,
"QTime":0,
"params":{
"q":"content:confidential"}},
"response":{"numFound":1,"start":0,"docs":[
{
"title":"Marbury v. Madison",
"content":"The clerks of the Department of State of the United States may be called upon
to give evidence of transactions in the Department which are not of a confidential character."}]
}}

Some helpful references:
• http://wiki.apache.org/solr/CommonQueryParameters
• http://wiki.apache.org/solr/SearchHandler
• http://lucene.apache.org/core/4_0_0-BETA/index.html

SOLR

Let’s summarize:
4. If index updates, figure out how to do it without breaking things.
5. Connect to search client over RESTful interface.
6. Oops, we don’t have enough capacity for search, update volume, etc. Scale!

Overall, solr is great. ElasticSearch makes some of these items easier as well.
Can you imagine implementing this from scratch?

However, items 1, 4, and 6 seem like low-hanging fruit for PaaS.


CLOUDSEARCH

pages about Python

Resources CloudSearch images of cats


• Yet another AWS managed service.
• Compare to RDS, but for search.

• Solr vs CloudSearch
• Collection : Domain
• Both RESTful
• CloudSearch schema/text configuration much less flexible


CLOUDSEARCH

pages about Python

Resources CloudSearch images of cats


Using CloudSearch
1. Create a domain
2. Configure schema, indexing, access, etc.
3. Seed index with data.
5. Relax (well, just make sure your billing information is correct).


CLOUDSEARCH


CLOUDSEARCH

OK, let’s try it. Make sure you have your JRE and AWS credentials configured.

Install CloudSearch command line tools.
$ cd /opt
$ sudo wget http://s3.amazonaws.com/amazon-cloudsearch-data/cloud-search-tools-1.0.0.1-
2012.03.05.tar.gz
$ sudo tar xzf cloud-search-tools-1.0.0.1-2012.03.05.tar.gz
$ export CS_HOME=/opt/cloud-search-tools-1.0.0.1-2012.03.05
$ export PATH=$PATH:$CS_HOME/bin
$ export AWS_CREDENTIAL_FILE=/home/user/.ec2/credentials


CLOUDSEARCH

1. Create a domain.
Request domain creation.
$ cs-create-domain -d rehnquist-express

Monitor the domain until available. This can take more than 5-10 minutes.
$ cs-describe-domain -d rehnquist-express
$ grab-a-drink-or-two


CLOUDSEARCH

2. Configure schema, indexing, access, etc.
Configure access policies. This can also take awhile.
$ cs-configure-access-policies -d rehnquist-express --update --allow IP_ADDRESS --service doc
$ cs-configure-access-policies -d rehnquist-express --update --allow all --service search
$ cs-configure-access-policies –d rehnquist-express –retrieve

Configure the schema.
$ cs-configure-fields -d rehnquist-express --name title --type text --option result
$ cs-configure-fields -d rehnquist-express --name content --type text --option result

Show current stopwords.
$ cs-configure-text-options –d rehnquist-express -psw
===== Stop Words =====
State: Active
======================
a
an

Not shown: custom synonyms, stemming rules, stopwords, or ranking.


CLOUDSEARCH

3. Seed index with data.
$ cd /tmp
$ wget http://bulk.resource.org/courts.gov/c/US.tar.bz2 && tar xjf US.tar.bz2
$ for d in `find /tmp/US/ -type d`;
do
cs-generate-sdf --source "$d/*.html" -d rehnquist-express;
done
$ cs-index-documents –d rehnquist-express


CLOUDSEARCH

$ curl ‚http://search-rehnquist-express-5nvzkxgvupbufypbvcmg57lw7m.us-east-
1.cloudsearch.amazonaws.com/2011-02-01/search?q=confidential&return-fields=title‛

{"rank":"-text_relevance","match-expr":"(label
'confidential')","hits":{"found":449,"start":0,"hit":[{"id":"d__data_workspace_lle_data_us_454_454
_us_170_80_1103_80_885_html","daa":{}},{"id":"d__data_workspace_lle_data_us_508_508_us_165_91_2054
_html","data":{}},{"id":"d__data_workspace_lle_data_us_340_340_us_332_21_html","data":{}},{"id":"d
__data_workssace_lle_data_us_484_484_us_19_86_422_html","data":{}},{"id":"d__data_workspace_lle_da
ta_us_510_510_us_1103___2_html","data":{}},{"id":"d__data_workspace_lle_data_us_291_291_us___338_h
tml","data":{}},{"id":"d__data_workspace_lle_data_us_537_537_us_941_01_1521_html","data":{}},{"id"
:"d__data_workspace_lle_data_us_537_537_us_941_01_1708_html","data":{}},,"id":"d__data_workspace_l
le_data_us_357_357_us_144_621_html","data":{}},{"id":"d__data_workspace_lle_data_us_351_351_us_345
_503_html","data":{}}]},"info":{"rid":"b7c167f6c2da6dd31b0fda497afcf1775b775c683dee5a356e2b9115965
a3eb688f6fc18e0a36950","time-ms":3,"cpu-time-ms":0}}


CLOUDSEARCH

What about pricing?
“Sticky” opex
Type Estimated Capacity* $/hr. $/mo.

Small 1M docs 0.12 $86

Large 4M docs 0.48 $346

Extra Large 8M docs 0.68 $489

* 1k documents, no result storage.

Variable opex
• $0.10 per 1,000 upload
• $0.98/GB per index
• $0.12/GB network out


CLOUDSEARCH

What about pricing?

Building this sample:

Some cycles on office servers not counted.


CLOUDSEARCH

Next steps:
• Try CloudSearch with Boto:
• http://boto.cloudhackers.com/en/latest/cloudsearch_tut.html

• Write your own custom content transformer with Tika:
• http://tika.apache.org/1.2/formats.html

• Understand how types, search, faceting, and results interact and constrain in
CloudSearch.

• Understand how response times are affected by document count, document
size, types, search, faceting, and results.


SEARCH SUMMARY

Solr CloudSearch

• Can share infrastructure and • Managed service.
application containers. • Highly scalable per unit of labor.
• Highly flexible configuration via • Like all AWS services, stop
XML. paying immediately when
• Can customize or extend by you’re done.
writing Java.

Best solution probably depends on relative scarcity of SA/developer
labor and document volume.

THINK MORE VARIABLE

Case search is a pretty simple, static example. You build a Lexis/West
clone, monetize with some ads or a subscription, and figure out how to handle
monthly or yearly updates as cheaply as possible.

Think more variable – what might CloudSearch help with in legal services? Prime
tasks should have durations or scales that are hard to meet with fixed assets.


THINK MORE VARIABLE

Here’s an idea, shamelessly copied from some of my marketing material:

Imagine you’re a smaller law firm that specializes in HR disputes. As part of a time-
sensitive non-solicitation claim filed by your client, you’ve subpoenaed email from
fifteen employees at a client’s competitor. It’s Friday afternoon at 5PM, and you finally
receive a hard drive with the emails. However, in an effort to overwhelm your small
team, the other party has dumped 10GB of data on your plate. There’s no way you can
search through this by hand. You have a hearing on Wednesday, but need to prepare a
memo for your client by Monday morning. Do you disappoint your client and motion to
reschedule? How could you possibly make the deadline? If only you could just press a
button and get something like Google for your data…

Discovery is a perfect task for CloudSearch.
• Very tight deadlines.
• Short project lifetimes.
• Wide variety of data volumes.


THINK MORE VARIABLE

For public corporations, you might have enough
compliance or discovery work to keep something an
application running 24/7.

Enter KnowCave – a SolidLogic project.
• Deep search
• Natural language content alert
• Responsive, multi-device interface

http://knowcave.com


REFERENCES

 B o m m a r i to C o n s u l t i n g B l o g
 Installing AWS Cloud Search Command Line Tools
 Building an AWS CloudSearch domain for the Supreme Court
 eDiscover y Consulting in the Cloud: Searching an Outlook mailbox and attachments
 Generating AWS CloudSearch SDF for Emails
 S o l i d L o g i c K n o w C ave
 E l e c t r o ni c D i s c ove r y Re f e r e n c e M o d e l
 EDRM Stages Explained
 C o r n e l l L e g a l I n f o r m a t i o n I n s t i t ute
 Federal Rules of Civil Procedure
 A m a z o n We b S e r v i c e s
 CloudSearch documentation
 CloudSearch command line tools
 Windows
 Linux/Mac
 I n te r n a t i o n al A s s o c i a t i o n f o r A r t i fi c ia l I n te l l i g e nc e a n d L aw
 B o to
 A p a c h e T i ka
 A p a c h e Lu c e n e
 Apache Solr
 E l a s t i c S e a rc h


THANKS!

You can get these slides on my blog – http://bommaritollc.com/blog/.
Here’s the post.

 Michael J Bommarito II
 CEO, Bommarito Consulting, LLC
 Email: michael@bommaritollc.com
 Web: http://bommaritollc.com/


Legal Informatics with AWS CloudSearch - AWS Michigan

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Legal Informatics with AWS CloudSearch - AWS Michigan