apache solr tutorial - Wikitechy

What is Indexing and search full_text arabic field using apache solr ?

Editor — Mon, 12 Jul 2021 15:45:41 +0000

Arabic field using apache solr:

Apache Solr has an Arabic analysis.
If you open the default schema.xml file which comes with Solr, you will see an example of Arabic fieldtype.
You can use CopyField to copy your fields to the Arabic field type.
You have to reindex your content again to get the preferred results.
If each document consists of 3 fields, two fields are integers then the third field is Arabic text with diacritics, the user may use words with or without diacritics or else some letters have diacritics and others without diacritics, you can use schema.xml which helps in such situation.

How to optimize Apache Solr boost factors using genetic algorithms ?

Editor — Mon, 12 Jul 2021 15:37:48 +0000

Optimize Apache Solr boost Factors:

The problem to solve:

When running search indexes with Solr, you might stumble upon is that you have various fields in your documents and you’ve to adjust their weights to get reasonable results.

Finding those “boosting” values can be quite complex when you have many fields and many scenarios.
Usually getting the values right is a task for very experienced integrators.

 
/Solr/select?defType=dismax&q=my+query
&qf=title^**42**+description^**23**+footnotes^**5**+dalmatiners^**101**+foo^**9001**+comments

Looking at it from a more technical perspective – when your Solr query looks like the one above, the question you’ve to answer is how the values for the highlighted numbers should look like to get reasonable results.

Measuring “reasonable”:

- In order to solve the problem answer what we expect the outcome to look like.
- In other words, we’ve to measure how reasonable a specific solution is.
  - For a search engine this can be done with some sample queries and some expectations along with that.

The expectation could come in a form that we explicitly tell which documents we expect in the result lists of specific queries (and at predefined positions).
We can simple test agains the expectations and check whether or not specific boost factor values actually satisfy them.

How to Index multiple tables using SOLR ?

Editor — Mon, 12 Jul 2021 14:56:17 +0000

Index multiple tables using SOLR

There are various ways to do it and it depends on your table schema. Some simple ones would be like:

If you have 2-3 different tables and they are kind of unrelated then in that case you need to have an extensive Solr schema and just index each table separately. You would perform this only when you desire to use Solr for just search on documents present in dissimilar tables.
It’s like you have a table STUDENT (id,name,roll) and TEACHER (id,name,subject,qualification), you need to have these fields in your solr schema (id,name,roll,subject,qualification).
Now index the two tables either by solrj or use Data Import Handler.

If you have different tables and have relations between them then you need to write SQL queries which perform joins between them and get the columns that you would like to index into solr.

Indexing either of the two tables (and not both the tables):

DB-config.xml




query="select * from table1">






query="select * from table2">

Schema.xml

 


stored="true" />
stored="true" />
stored="true" />
stored="true" />

stored="true" />
stored="true" />
indexed="true" stored="true" />
stored="true" />

ElementPropertyID

What is the difference between Apache Solr and ElasticSearch ?

Editor — Mon, 12 Jul 2021 11:53:17 +0000

Differences between Apache Solr and ElasticSearch:

Feature	Solr 6.2.1	ElasticSearch 5.0
Format	XML, CSV, JSON	JSON
HTTP REST API	✔	✔
Binary API	✔ SolrJ	✔ TransportClient, Thrift (through a plugin)
JMX support	✔	☓ ES specific stats are exposed through the REST API
Official client libraries	Java	Java, Groovy, PHP, Ruby, Perl, Python, .NET, Javascript Official list of clients
Community client libraries	PHP, Ruby, Perl, Scala, Python, .NET, Javascript, Go, Erlang, Clojure	Clojure, Cold Fusion, Erlang, Go, Groovy, Haskell, Java, JavaScript, .NET, OCaml, Perl, PHP, Python, R, Ruby, Scala, Smalltalk, Vert.x Complete list
3rd-party product integration (open-source)	Drupal, Magento, Django, ColdFusion, Wordpress, OpenCMS, Plone, Typo3, ez Publish, Symfony2, Riak (via Yokozuna)	Drupal, Django, Symfony2, Wordpress, CouchBase
3rd-party product integration (commercial)	DataStax Enterprise Search, Cloudera Search, Hortonworks Data Platform, MapR	SearchBlox, Hortonworks Data Platform, MapR etc Complete list
Output	JSON, XML, PHP, Python, Ruby, CSV, Velocity, XSLT, native Java	JSON, XML/HTML (via plugin)

What are the advantages of using apache Solr over elasticsearch ?

Editor — Mon, 12 Jul 2021 11:45:17 +0000

Apache Solr over elasticsearch:

Real Time, Massive Read, and Write Scalability:
- Apache Solr supports large-scale, search, distributed indexing, and aggregation or statistics operations, enabling to handle applications large and small.
SQL and Streaming Expressions/Aggregations.
Security Out of the Box:
- Using Solr, security is built in, integrating with systems such as kerberos, SSL, and LDAP to not only secure the system, also secure the content inside of it.
Graph Support:
- Graph operations over the data allow query and work with difficult relationships between data and then output to formats like GraphML.
Solr Plays Nice With Big Data Toolchains
Kibana and Logstash Both Work with Solr

What is the difference between Apache Solr and MongoDB ?

Editor — Mon, 12 Jul 2021 11:39:50 +0000

Difference between Apache Solr and MongoDB:

Here,Some of the examples of document oriented database is MongoDB, Cassandra, and CouchBD.

Name	Apache Solr	MongoDB
Description	A widely used enterprise search engine based on Apache Lucene.	One of the most popular document stores
Developer	Apache Software Foundation	MongoDB, Inc.
Cloud-based	No	No
Server operating systems	All OS with a Java VM and a servlet container	Linux OS X Solaris Windows
Data scheme	Yes	schema-free
Implementation language	Java	C++
Secondary indexes	Yes	Yes
SQL	No	No

What is the most ideal approach to use Apache Solr for relational JOIN ?

Editor — Mon, 12 Jul 2021 09:28:47 +0000

Apache Solr for relational JOIN:

Run a single-use script that do the joins on the SOLR index (file) to replace the author_id and author_name, or include the field if you need both. Updating 10,000,000+ documents will get a while, however it is definitely achievable.
After that you can have new documents indexed with both fields, doing the JOIN one at a time.
In common, SOLR works with entirely denormalized information.
If it is more than just authors’ names, you could still denormalize the information, repeating your documents for every one of the related author documents.
Another technique is SOLR 4 has “JOIN” ability.
You’d first need to at least contain a pipeline wherever author information is indexed into SOLR in real-time.
Utilize Elastic Search to simply deal with the complex SOLR queries involving JOIN-like operations.

What are the features of Apache Solr ?

Editor — Mon, 12 Jul 2021 09:01:12 +0000

Features of Apache Solr

Advanced Full-Text Search Capabilities:

Apache Solr contains powerful capabilities such as phrases, wildcards, grouping, joins and much more across several data type.

Optimized for High Volume Traffic:

It is proven at very large scales throughout the world.

Standards Based Open Interfaces – XML, JSON and HTTP:

Solr uses the tools that use to make application building a snap.

Comprehensive Administration Interfaces:

It ships with a built-in, responsive administrative UI to build it simple and to manage the Solr instances.

Ease Monitoring:

It publishes many of metric information via JMX.

Highly Scalable and Fault Tolerant:

Built on the battle-tested Apache Zookeeper, It makes ease to scale up and down.
It bakes in distribution, replication, and rebalancing as well as fault tolerance out of the box.

Flexible and Adaptable with easy configuration:

Solr’s is planned to adapt your needs as simplifying configuration.

Near Real-Time Indexing:

Apache Solr takes a benefit of Lucene’s Near Real-Time Indexing capabilities to ensure you to see your content when you would like to notice it