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		<title>What is Indexing and search full_text arabic field using apache solr ?</title>
		<link>https://www.wikitechy.com/interview-questions/apache-solr/what-is-indexing-and-search-full_text-arabic-field-using-apache-solr/</link>
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		<dc:creator><![CDATA[Editor]]></dc:creator>
		<pubDate>Mon, 12 Jul 2021 15:45:41 +0000</pubDate>
				<category><![CDATA[Apache Solr]]></category>
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					<description><![CDATA[Answer:Apache Solr has an Arabic analysis.]]></description>
										<content:encoded><![CDATA[<div class="TextHeading">
<div class="hddn">
<h2 id="arabic-field-using-apache-solr" class="color-purple" style="text-align: justify;">Arabic field using apache solr:</h2>
</div>
</div>
<div class="row" style="text-align: justify;">
<div class="col-sm-12">
<div class="Content">
<div class="hddn">
<ul>
<li>Apache Solr has an Arabic analysis.</li>
<li>If you open the default schema.xml file which comes with Solr, you will see an example of Arabic fieldtype.</li>
<li>You can use CopyField to copy your fields to the Arabic field type.</li>
<li>You have to reindex your content again to get the preferred results.</li>
<li>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.</li>
</ul>
</div>
</div>
<div class="ImageContent">
<div class="hddn"></div>
<div>
<div class="code-embed-wrapper"> <div class="code-embed-infos"> </div> <pre class="language-markdown code-embed-pre line-numbers"  data-start="1" data-line-offset="0"><code class="language-markdown code-embed-code">&lt;?xml version=&quot;1.0&quot; encoding=&quot;UTF-8&quot; ?&gt;<br/><br/>&lt;schema name=&quot;quran&quot; version=&quot;1.5&quot;&gt;<br/><br/>&lt;fields&gt;<br/>    &lt;field name=&quot;_version_&quot; type=&quot;long&quot; indexed=&quot;true&quot; stored=&quot;true&quot;/&gt;<br/>    &lt;field name=&quot;_id&quot; type=&quot;long&quot; indexed=&quot;true&quot; stored=&quot;true&quot; /&gt;<br/>    &lt;field name=&quot;sura_number&quot; type=&quot;int&quot; indexed=&quot;true&quot; stored=&quot;true&quot; /&gt;<br/>    &lt;field name=&quot;verse_number&quot; type=&quot;int&quot; indexed=&quot;true&quot; stored=&quot;true&quot; /&gt;<br/>    &lt;field name=&quot;verse_text&quot; type=&quot;text_ar&quot; indexed=&quot;true&quot; stored=&quot;true&quot;/&gt;<br/> &lt;/fields&gt;<br/><br/>&lt;types&gt;<br/>    &lt;fieldType name=&quot;string&quot; class=&quot;solr.StrField&quot; sortMissingLast=&quot;true&quot; /&gt;<br/>    &lt;fieldType name=&quot;boolean&quot; class=&quot;solr.BoolField&quot; sortMissingLast=&quot;true&quot;/&gt;<br/><br/>    &lt;fieldType name=&quot;int&quot; class=&quot;solr.TrieIntField&quot; precisionStep=&quot;0&quot; positionIncrementGap=&quot;0&quot;/&gt;<br/>    &lt;fieldType name=&quot;float&quot; class=&quot;solr.TrieFloatField&quot; precisionStep=&quot;0&quot; positionIncrementGap=&quot;0&quot;/&gt;<br/>    &lt;fieldType name=&quot;long&quot; class=&quot;solr.TrieLongField&quot; precisionStep=&quot;0&quot; positionIncrementGap=&quot;0&quot;/&gt;<br/>    &lt;fieldType name=&quot;double&quot; class=&quot;solr.TrieDoubleField&quot; precisionStep=&quot;0&quot; positionIncrementGap=&quot;0&quot;/&gt;<br/><br/>    &lt;fieldType name=&quot;date&quot; class=&quot;solr.TrieDateField&quot; precisionStep=&quot;0&quot; positionIncrementGap=&quot;0&quot;/&gt;<br/><br/>    &lt;fieldType name=&quot;location&quot; class=&quot;solr.LatLonType&quot; subFieldSuffix=&quot;_coordinate&quot;/&gt;<br/>    &lt;dynamicField name=&quot;*_coordinate&quot;  type=&quot;tdouble&quot; indexed=&quot;true&quot;  stored=&quot;false&quot;/&gt;<br/><br/>   &lt;!--  Arabic  --&gt;<br/>   &lt;fieldType name=&quot;text_ar&quot; class=&quot;solr.TextField&quot; positionIncrementGap=&quot;100&quot;&gt;<br/>   &lt;analyzer&gt;<br/>   &lt;tokenizer class=&quot;solr.StandardTokenizerFactory&quot;/&gt;<br/>   &lt;!--  normalizes ﻯ to ﻱ, etc  --&gt;<br/>   &lt;filter class=&quot;solr.ArabicNormalizationFilterFactory&quot;/&gt;<br/>   &lt;filter class=&quot;solr.ArabicStemFilterFactory&quot;/&gt;<br/>   &lt;/analyzer&gt;<br/>   &lt;/fieldType&gt;<br/><br/>&lt;/types&gt;<br/><br/>&lt;/schema&gt;</code></pre> </div>
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		<title>How to optimize Apache Solr boost factors using genetic algorithms ?</title>
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		<dc:creator><![CDATA[Editor]]></dc:creator>
		<pubDate>Mon, 12 Jul 2021 15:37:48 +0000</pubDate>
				<category><![CDATA[Apache Solr]]></category>
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					<description><![CDATA[ Answer:When running search indexes with Solr, you might stumble upon is that you ..]]></description>
										<content:encoded><![CDATA[<div class="TextHeading">
<div class="hddn">
<h2 id="optimize-apache-solr-boost-factors" class="color-purple" style="text-align: justify;">Optimize Apache Solr boost Factors:</h2>
</div>
</div>
<div class="row">
<div class="col-sm-12">
<div class="ImageContent" style="text-align: justify;">
<div class="hddn"><img fetchpriority="high" decoding="async" class="aligncenter size-medium" src="https://cdn.wikitechy.com/interview-questions/apache-solr/optimize-apache-solr.png" alt="Optimize apache solr" width="933" height="690" /></div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="the-problem-to-solve" class="color-purple">The problem to solve:</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>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.</li>
</ul>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>Finding those “boosting” values can be quite complex when you have many fields and many scenarios.</li>
<li>Usually getting the values right is a task for very experienced integrators.</li>
</ul>
</div>
</div>
<div class="CodeContent" style="text-align: justify;">
<div class="hddn">
<figure class="highlight"><div class="code-embed-wrapper"> <div class="code-embed-infos"> </div> <pre class="language-markdown code-embed-pre line-numbers"  data-start="1" data-line-offset="0"><code class="language-markdown code-embed-code">/Solr/select?defType=dismax&amp;q=my+query<br/>&amp;qf=title^**42**+description^**23**+footnotes^**5**+dalmatiners^**101**+foo^**9001**+comments</code></pre> </div></figure>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>Looking at it from a more technical perspective &#8211; 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.</li>
</ul>
</div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="measuring-reasonable" class="color-purple">Measuring “reasonable”:</h2>
</div>
</div>
<div class="Content">
<div class="hddn">
<ul style="text-align: justify;">
<li style="list-style-type: none;">
<ul>
<li>In order to solve the problem answer what we expect the outcome to look like.</li>
<li>In other words, we’ve to measure how reasonable a specific solution is.
<ul>
<li>For a search engine this can be done with some sample queries and some expectations along with that.</li>
</ul>
</li>
</ul>
</li>
</ul>
<ul>
<li style="text-align: justify;">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).</li>
<li style="text-align: justify;">We can simple test agains the expectations and check whether or not specific boost factor values actually satisfy them.</li>
</ul>
</div>
</div>
</div>
</div>
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		<title>How to link Apache Solr to MongoDB ?</title>
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		<pubDate>Mon, 12 Jul 2021 15:29:04 +0000</pubDate>
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					<description><![CDATA[Answer:New in mongo-connector 2.5.0, to install mongo-connector with the Solr-doc-manager run:]]></description>
										<content:encoded><![CDATA[<div class="TextHeading">
<div class="hddn">
<h2 id="installation" class="color-purple" style="text-align: justify;">Installation</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>New in mongo-connector 2.5.0, to install mongo-connector with the Solr-doc-manager run:</li>
</ul>
</div>
</div>
<div class="CodeContent" style="text-align: justify;">
<div class="hddn">
<figure class="highlight"><div class="code-embed-wrapper"> <div class="code-embed-infos"> </div> <pre class="language-python code-embed-pre line-numbers"  data-start="1" data-line-offset="0"><code class="language-python code-embed-code">Pip install &#039;mongo-connector[solr]&#039;</code></pre> </div></figure>
</div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="setup" class="color-purple">Setup</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>Create Solr cores</li>
</ul>
</div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="make-sure-the-lukerequesthandler-is-enabled" class="color-purple">Make sure the LukeRequestHandler is enabled</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>This line should be present in your solrconfig.xml file:</li>
</ul>
</div>
</div>
<div class="CodeContent" style="text-align: justify;">
<div class="hddn">
<figure class="highlight"><div class="code-embed-wrapper"> <div class="code-embed-infos"> </div> <pre class="language-python code-embed-pre line-numbers"  data-start="1" data-line-offset="0"><code class="language-python code-embed-code">&lt;requestHandler name=&quot;/admin/luke&quot; class=&quot;org.apache.solr.handler.admin.LukeRequestHandler&quot; /&gt;</code></pre> </div></figure>
</div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="set-up-your-schema" class="color-purple">Set up your Schema</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>Mongo Connector stores metadata in every document to help handle rollbacks.</li>
<li>To support these data, you&#8217;ll need to include the following to your schema.xml:</li>
</ul>
<div class="code-embed-wrapper"> <div class="code-embed-infos"> </div> <pre class="language-python code-embed-pre line-numbers"  data-start="1" data-line-offset="0"><code class="language-python code-embed-code">&lt;field name=&quot;_ts&quot; type=&quot;long&quot; indexed=&quot;true&quot; stored=&quot;true&quot; /&gt;<br/>&lt;field name=&quot;ns&quot; type=&quot;string&quot; indexed=&quot;true&quot; stored=&quot;true&quot;/&gt;</code></pre> </div>
</div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="the-basics" class="color-purple">The Basics:</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>Mongo Connector can replicate to Apache Solr search engine by using the Solr DocManager.</li>
<li>To start the connector, you must pass in the base URL for the Solr core to which you want to synchronize.</li>
</ul>
</div>
</div>
<p style="text-align: justify;">The most basic usage is the following:</p>
<div class="code-embed-wrapper"> <div class="code-embed-infos"> </div> <pre class="language-python code-embed-pre line-numbers"  data-start="1" data-line-offset="0"><code class="language-python code-embed-code">Mongo-connector -m localhost:27017 -t http://localhost:8983/solr -d solr_doc_manager</code></pre> </div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="mongo-connector-and-schema-xml" class="color-purple">Mongo Connector and schema.xml</h2>
</div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="configuring-solr" class="color-purple">Configuring Solr</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>Refer to the Apache documentation for configuring Solr and SolrCloud.</li>
</ul>
</div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="n-b-key-names-and-document-flattening" class="color-purple">N.B.: Key Names and Document Flattening</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>Mongo Connector automatically &#8220;flattens&#8221; MongoDB documents.</li>
<li>Fields within sub-documents can be referenced by their &#8220;dot-separated path&#8221; within the document.</li>
<li>Likewise, array fields are unrolled, so that individual elements are accessible by the field&#8217;s original name, plus a &#8220;.&#8221;, plus the index within the array that the element occupied.</li>
</ul>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<p align="justify">An example:</p>
<div class="code-embed-wrapper"> <div class="code-embed-infos"> </div> <pre class="language-python code-embed-pre line-numbers"  data-start="1" data-line-offset="0"><code class="language-python code-embed-code">{<br/>    &quot;subdoc&quot;: {<br/>        &quot;a&quot;: 1,<br/>        &quot;b&quot;: 2,<br/>        &quot;c&quot;: 3,<br/>        &quot;array&quot;: [<br/>            {&quot;name&quot;: &quot;elmo&quot;},<br/>            {&quot;name&quot;: &quot;oscar&quot;}<br/>        ]<br/>    }<br/>}</code></pre> </div>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>It will become the following in Solr:</li>
</ul>
<div class="code-embed-wrapper"> <div class="code-embed-infos"> </div> <pre class="language-python code-embed-pre line-numbers"  data-start="1" data-line-offset="0"><code class="language-python code-embed-code">{<br/>    &quot;subdoc.a&quot;: 1,<br/>    &quot;subdoc.b&quot;: 2,<br/>    &quot;subdoc.c&quot;: 3,<br/>    &quot;subdoc.array.0.name&quot;: &quot;elmo&quot;,<br/>    &quot;subdoc.array.1.name&quot;: &quot;oscar&quot;<br/>}</code></pre> </div>
</div>
</div>
<div class="ImageContent" style="text-align: justify;">
<div class="hddn"><img decoding="async" class="aligncenter size-medium" src="https://cdn.wikitechy.com/interview-questions/apache-solr/apache-solr-mongodb.png" alt="Apache Solr Mongodb" width="1002" height="572" /></div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="schema-xml" class="color-purple">Schema.xml</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>In addition, Mongo Connector comes with an example schema.xml file that can help get you started integrating MongoDB with Apache Solr search.</li>
<li>Solr reads schema.xml in order to find field types, fields that documents may have the primary key, and more.</li>
<li>MongoDB Connector try to acquire the schema for Apache Solr by using the LukeRequestHandler at a particular URI admin/luke/?show=schema&amp;wt=json which is appended to the base of the Apache Solr URL.</li>
<li>So, in the above example, Mongo Connector tries to get the schema for Apache Solr by sending a GET request to http://localhost:8983/solr/admin/luke/?show=schema&amp;wt=json.</li>
<li>Mongo Connector will drop fields from MongoDB documents that are not confirmed in your Apache Solr core&#8217;s schema in order to avoid Solr throw exceptions and fail to add those documents.</li>
<li>If you do not describe the fields then you desire in schema.xml and reload the Apache Solr core, Mongo Connector will merrily continue stripping your MongoDB documents of the offending fields.</li>
<li>You can able to check what Apache Solr thinks the schema to your core by visiting the aforementioned endpoint in browser.</li>
</ul>
</div>
</div>
<div class="Content">
<div class="hddn"></div>
</div>
]]></content:encoded>
					
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		<item>
		<title>What is the difference between Apache Solr and ElasticSearch ?</title>
		<link>https://www.wikitechy.com/interview-questions/apache-solr/what-is-the-difference-between-apache-solr-and-elasticsearch/</link>
					<comments>https://www.wikitechy.com/interview-questions/apache-solr/what-is-the-difference-between-apache-solr-and-elasticsearch/#respond</comments>
		
		<dc:creator><![CDATA[Editor]]></dc:creator>
		<pubDate>Mon, 12 Jul 2021 11:53:17 +0000</pubDate>
				<category><![CDATA[Apache Solr]]></category>
		<category><![CDATA[Accenture interview questions and answers]]></category>
		<category><![CDATA[apache solr documentation]]></category>
		<category><![CDATA[apache solr download]]></category>
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					<description><![CDATA[Answer:The main difference between Solr and Elasticsearch is that Solr is a completely open-source search engine.]]></description>
										<content:encoded><![CDATA[<div class="TextHeading">
<div class="hddn">
<h2 id="differences-between-apache-solr-and-elasticsearch" class="color-purple">Differences between Apache Solr and ElasticSearch:</h2>
</div>
</div>
<div class="row">
<div class="col-sm-12">
<table class="table-bordered table-striped table table-responsive">
<tbody>
<tr>
<th>Feature</th>
<th>Solr 6.2.1</th>
<th>ElasticSearch 5.0</th>
</tr>
</tbody>
<tbody>
<tr>
<td class="text-leftalign">Format</td>
<td class="text-leftalign">XML, CSV,<br />
JSON</td>
<td class="text-leftalign">JSON</td>
</tr>
<tr>
<td class="text-leftalign">HTTP REST API</td>
<td class="text-leftalign">✔</td>
<td class="text-leftalign">✔</td>
</tr>
<tr>
<td class="text-leftalign">Binary API</td>
<td class="text-leftalign">✔ SolrJ</td>
<td class="text-leftalign">✔ TransportClient, Thrift (through a plugin)</td>
</tr>
<tr>
<td class="text-leftalign">JMX support</td>
<td class="text-leftalign">✔</td>
<td class="text-leftalign"><b>☓</b> ES specific stats are<br />
exposed through the REST API</td>
</tr>
<tr>
<td class="text-leftalign">Official client libraries</td>
<td class="text-leftalign">Java</td>
<td class="text-leftalign">Java, Groovy, PHP, Ruby, Perl, Python, .NET,<br />
Javascript Official list of clients</td>
</tr>
<tr>
<td class="text-leftalign">Community client libraries</td>
<td class="text-leftalign">PHP, Ruby, Perl, Scala, Python, .NET,<br />
Javascript, Go, Erlang, Clojure</td>
<td class="text-leftalign">Clojure, Cold Fusion, Erlang, Go, Groovy, Haskell, Java,<br />
JavaScript, .NET, OCaml, Perl, PHP, Python, R,<br />
Ruby, Scala, Smalltalk, Vert.x Complete list</td>
</tr>
<tr>
<td class="text-leftalign">3rd-party product integration<br />
(open-source)</td>
<td class="text-leftalign">Drupal, Magento, Django, ColdFusion,<br />
Wordpress, OpenCMS, Plone, Typo3,<br />
ez Publish, Symfony2, Riak (via Yokozuna)</td>
<td class="text-leftalign">Drupal, Django, Symfony2,<br />
Wordpress, CouchBase</td>
</tr>
<tr>
<td class="text-leftalign">3rd-party product integration<br />
(commercial)</td>
<td class="text-leftalign">DataStax Enterprise Search,<br />
Cloudera Search, Hortonworks Data<br />
Platform, MapR</td>
<td class="text-leftalign">SearchBlox, Hortonworks Data Platform,<br />
MapR etc Complete list</td>
</tr>
<tr>
<td class="text-leftalign">Output</td>
<td class="text-leftalign">JSON, XML, PHP, Python, Ruby, CSV,<br />
Velocity, XSLT, native Java</td>
<td class="text-leftalign">JSON, XML/HTML (via plugin)</td>
</tr>
</tbody>
</table>
<div class="text-center row">
<div class="col-sm-12">
<div id="bsa-zone_1590522538159-8_123456"></div>
</div>
</div>
<div class="hddn"><img decoding="async" class="aligncenter size-medium" src="https://cdn.wikitechy.com/interview-questions/apache-solr/query-top.png" alt="query top" width="877" height="653" /></div>
</div>
<div class="hddn"><img loading="lazy" decoding="async" class="aligncenter size-medium" src="https://cdn.wikitechy.com/interview-questions/apache-solr/elasticsearch-dashboard-final.png" alt="elasticsearch dashboard final" width="1252" height="875" /></div>
</div>
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		<title>What are the advantages of using apache Solr over elasticsearch ?</title>
		<link>https://www.wikitechy.com/interview-questions/apache-solr/what-are-the-advantages-of-using-apache-solr-over-elasticsearch/</link>
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		<dc:creator><![CDATA[Editor]]></dc:creator>
		<pubDate>Mon, 12 Jul 2021 11:45:17 +0000</pubDate>
				<category><![CDATA[Apache Solr]]></category>
		<category><![CDATA[Accenture interview questions and answers]]></category>
		<category><![CDATA[apache solr advantages]]></category>
		<category><![CDATA[apache solr advantages and disadvantages]]></category>
		<category><![CDATA[apache solr download]]></category>
		<category><![CDATA[apache solr tutorial]]></category>
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					<description><![CDATA[Answer:Apache Solr supports large-scale, search, distributed indexing, and aggregation or statistics operations, enabling to handle applications large and small.]]></description>
										<content:encoded><![CDATA[<div class="TextHeading">
<div class="hddn">
<h2 id="apache-solr-over-elasticsearch" class="color-purple" style="text-align: justify;">Apache Solr over elasticsearch:</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li><b>Real Time, Massive Read, and Write Scalability:</b>
<ul>
<li>Apache Solr supports large-scale, search, distributed indexing, and aggregation or statistics operations, enabling to handle applications large and small.</li>
</ul>
</li>
<li><b>SQL and Streaming Expressions/Aggregations.</b></li>
<li>Security Out of the Box:
<ul>
<li>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.</li>
</ul>
</li>
<li><b>Graph Support:</b>
<ul>
<li>Graph operations over the data allow query and work with difficult relationships between data and then output to formats like GraphML.</li>
</ul>
</li>
<li>Solr Plays Nice With Big Data Toolchains</li>
<li>Kibana and Logstash Both Work with Solr</li>
</ul>
</div>
</div>
<div class="text-center row">
<div><img loading="lazy" decoding="async" class="aligncenter size-medium" src="https://cdn.wikitechy.com/interview-questions/apache-solr/advantages-apche.png" alt="advantages apache" width="935" height="403" /></div>
</div>
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		<item>
		<title>What is the difference between Apache Solr and MongoDB ?</title>
		<link>https://www.wikitechy.com/interview-questions/apache-solr/what-is-the-difference-between-apache-solr-and-mongodb/</link>
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		<dc:creator><![CDATA[Editor]]></dc:creator>
		<pubDate>Mon, 12 Jul 2021 11:39:50 +0000</pubDate>
				<category><![CDATA[Apache Solr]]></category>
		<category><![CDATA[Accenture interview questions and answers]]></category>
		<category><![CDATA[apache solr documentation]]></category>
		<category><![CDATA[apache solr download]]></category>
		<category><![CDATA[apache solr tutorial]]></category>
		<category><![CDATA[apache solr vs elasticsearch]]></category>
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		<category><![CDATA[solr database integration]]></category>
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		<category><![CDATA[what is apache solr used for]]></category>
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		<category><![CDATA[what is solr search]]></category>
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		<guid isPermaLink="false">https://www.wikitechy.com/interview-questions/?p=228</guid>

					<description><![CDATA[Answer:A widely used enterprise
search engine based on Apache Lucene.	One of the most popular document stores]]></description>
										<content:encoded><![CDATA[<h2 id="difference-between-apache-solr-and-mongodb" class="color-purple">Difference between Apache Solr and MongoDB:</h2>
<div class="Content">
<div class="hddn">
<ul>
<li>Here,Some of the examples of document oriented database is MongoDB, Cassandra, and CouchBD.</li>
</ul>
</div>
</div>
<table class="table-bordered table-striped table table-responsive">
<tbody>
<tr>
<th>Name</th>
<th>Apache Solr</th>
<th>MongoDB</th>
</tr>
<tr>
<td class="text-leftalign">Description</td>
<td class="text-leftalign">A widely used enterprise<br />
search engine based on Apache Lucene.</td>
<td class="text-leftalign">One of the most popular document stores</td>
</tr>
<tr>
<td class="text-leftalign">Developer</td>
<td class="text-leftalign">Apache Software Foundation</td>
<td class="text-leftalign">MongoDB, Inc.</td>
</tr>
<tr>
<td class="text-leftalign">Cloud-based</td>
<td class="text-leftalign">No</td>
<td class="text-leftalign">No</td>
</tr>
<tr>
<td class="text-leftalign">Server operating systems</td>
<td class="text-leftalign">All OS with a Java VM<br />
and a servlet container</td>
<td class="text-leftalign">Linux OS X Solaris Windows</td>
</tr>
<tr>
<td class="text-leftalign">Data scheme</td>
<td class="text-leftalign">Yes</td>
<td class="text-leftalign">schema-free</td>
</tr>
<tr>
<td class="text-leftalign">Implementation language</td>
<td class="text-leftalign">Java</td>
<td class="text-leftalign">C++</td>
</tr>
<tr>
<td class="text-leftalign">Secondary indexes</td>
<td class="text-leftalign">Yes</td>
<td class="text-leftalign">Yes</td>
</tr>
<tr>
<td class="text-leftalign">SQL</td>
<td class="text-leftalign">No</td>
<td class="text-leftalign">No</td>
</tr>
</tbody>
</table>
<div class="text-center row">
<div class="col-sm-12">
<div id="bsa-zone_1590522538159-8_123456"></div>
</div>
</div>
<div class="hddn"></div>
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		<title>What is the most ideal approach to use Apache Solr for relational JOIN ?</title>
		<link>https://www.wikitechy.com/interview-questions/apache-solr/what-is-the-most-ideal-approach-to-use-apache-solr-for-relational-join/</link>
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		<dc:creator><![CDATA[Editor]]></dc:creator>
		<pubDate>Mon, 12 Jul 2021 09:28:47 +0000</pubDate>
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					<description><![CDATA[Answer:Run a single-use script that do the joins on the SOLR index (file) to replace the author_id and author_name]]></description>
										<content:encoded><![CDATA[<div class="TextHeading">
<div class="hddn">
<h2 id="apache-solr-for-relational-join" class="color-purple" style="text-align: justify;">Apache Solr for relational JOIN:</h2>
</div>
</div>
<div class="row">
<div class="col-sm-12">
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>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.</li>
<li>After that you can have new documents indexed with both fields, doing the JOIN one at a time.</li>
<li>In common, SOLR works with entirely denormalized information.</li>
<li>If it is more than just authors&#8217; names, you could still denormalize the information, repeating your documents for every one of the related author documents.</li>
<li>Another technique is SOLR 4 has &#8220;JOIN&#8221; ability.</li>
<li>You&#8217;d first need to at least contain a pipeline wherever author information is indexed into SOLR in real-time.</li>
<li>Utilize Elastic Search to simply deal with the complex SOLR queries involving JOIN-like operations.</li>
</ul>
</div>
</div>
<div class="Content">
<div class="hddn"></div>
</div>
</div>
</div>
]]></content:encoded>
					
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		<title>What is the internal architecture of Apache solr ?</title>
		<link>https://www.wikitechy.com/interview-questions/apache-solr/what-is-the-internal-architecture-of-apache-solr/</link>
					<comments>https://www.wikitechy.com/interview-questions/apache-solr/what-is-the-internal-architecture-of-apache-solr/#respond</comments>
		
		<dc:creator><![CDATA[Editor]]></dc:creator>
		<pubDate>Mon, 12 Jul 2021 09:24:15 +0000</pubDate>
				<category><![CDATA[Apache Solr]]></category>
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					<description><![CDATA[Answer:The requests that send to Solr are processed by the request handlers.]]></description>
										<content:encoded><![CDATA[<div class="row">
<div class="col-sm-12">
<div class="TextHeading">
<div class="hddn">
<h2 id="solr-architecture-%e2%94%80-building-blocks" class="color-purple" style="text-align: justify;">Solr Architecture ─ Building Blocks</h2>
</div>
</div>
<p style="text-align: justify;">Following are the major building blocks of Apache Solr:</p>
<div class="ImageContent" style="text-align: justify;">
<div class="hddn"><img loading="lazy" decoding="async" class="aligncenter size-medium" src="https://cdn.wikitechy.com/interview-questions/apache-pig/solr-architecture.png" alt="solr architecture" width="600" height="390" /></div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="solr-architecture-%e2%94%80-building-blocks-request-handler" class="color-red">Solr Architecture ─ Building Blocks Request Handler:</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>The requests that send to Solr are processed by the request handlers.</li>
<li>The requests may be a query requests otherwise index update requests.</li>
<li>It is based on our requirement; we need to choose the request handler.</li>
<li>To pass a request to Solr, we generally map the handler to a certain URI end-point and the particular request will be served by it.</li>
</ul>
</div>
</div>
<div class="hddn"><img loading="lazy" decoding="async" class="aligncenter size-medium" src="https://cdn.wikitechy.com/interview-questions/apache-solr/how-apache-solr-works.gif" alt="how apache solr works" width="575" height="335" /></div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="search-component" class="color-purple">Search Component:</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>The search component is a type of search provided in Apache Solr.</li>
<li>It might be spell checking, faceting, query, and hit highlighting and so on.</li>
<li>These search components are registered as search handlers. Multiple components can be registered to a search handler.</li>
</ul>
</div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="query-parser" class="color-purple">Query Parser:</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>The Apache Solr query parser parses the queries that we pass to Solr and verifies the queries for syntactical errors.</li>
<li>After parsing the queries, it translates them to a format which Lucene understands.</li>
</ul>
</div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="response-writer" class="color-pink">Response Writer:</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>A response writer is the component which generates the formatted outcome for the user queries.</li>
<li>Apache Solr supports response formats some are XML, JSON, CSV, etc.</li>
<li>We have different response writers for each type of response.</li>
</ul>
</div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="analyser-tokenizer" class="color-red">Analyser/tokenizer:</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>Lucene recognizes data in the form of tokens.</li>
<li>Apache Solr analyses the content, divides it into tokens, and passes these tokens to Lucene.</li>
<li>An analyser examines the text of fields and generates a token stream.</li>
<li>A tokenizer breaks the token stream prepared by the analyser into tokens.</li>
</ul>
</div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="update-request-processor" class="color-pink">Update Request Processor:</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>Whenever we send an update request to Apache Solr, the request is run through a set of plugins (signature, logging, indexing), collectively known as update request processor.</li>
<li>This processor is responsible for modifications that are adding a field, dropping a field, etc.</li>
</ul>
</div>
</div>
<div class="hddn" style="text-align: justify;"><img loading="lazy" decoding="async" class="aligncenter size-medium" src="https://cdn.wikitechy.com/interview-questions/apache-solr/apache-solr-with-hadoop.gif" alt="apache solr with hadoop" width="622" height="335" /></div>
</div>
</div>
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		<title>What are the features of Apache Solr ?</title>
		<link>https://www.wikitechy.com/interview-questions/apache-solr/what-are-the-features-of-apache-solr/</link>
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		<dc:creator><![CDATA[Editor]]></dc:creator>
		<pubDate>Mon, 12 Jul 2021 09:01:12 +0000</pubDate>
				<category><![CDATA[Apache Solr]]></category>
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					<description><![CDATA[Answer:Apache Solr contains powerful capabilities such as phrases]]></description>
										<content:encoded><![CDATA[<div class="TextHeading">
<div class="hddn">
<h2 id="features-of-apache-solr" class="color-green" style="text-align: justify;">Features of Apache Solr</h2>
</div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="advanced-full-text-search-capabilities" class="color-purple">Advanced Full-Text Search Capabilities:</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>Apache Solr contains powerful capabilities such as phrases, wildcards, grouping, joins and much more across several data type.</li>
</ul>
</div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="optimized-for-high-volume-traffic" class="color-purple">Optimized for High Volume Traffic:</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>It is proven at very large scales throughout the world.</li>
</ul>
</div>
</div>
<div class="text-center row" style="text-align: justify;"></div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="standards-based-open-interfaces-xml-json-and-http" class="color-purple">Standards Based Open Interfaces &#8211; XML, JSON and HTTP:</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>Solr uses the tools that use to make application building a snap.</li>
</ul>
</div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="comprehensive-administration-interfaces" class="color-purple">Comprehensive Administration Interfaces:</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>It ships with a built-in, responsive administrative UI to build it simple and to manage the Solr instances.</li>
</ul>
</div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="ease-monitoring" class="color-purple">Ease Monitoring:</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>It publishes many of metric information via JMX.</li>
</ul>
</div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="highly-scalable-and-fault-tolerant" class="color-purple">Highly Scalable and Fault Tolerant:</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>Built on the battle-tested Apache Zookeeper, It makes ease to scale up and down.</li>
<li>It bakes in distribution, replication, and rebalancing as well as fault tolerance out of the box.</li>
</ul>
</div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="flexible-and-adaptable-with-easy-configuration" class="color-purple">Flexible and Adaptable with easy configuration:</h2>
</div>
</div>
<div class="Content" style="text-align: justify;">
<div class="hddn">
<ul>
<li>Solr’s is planned to adapt your needs as simplifying configuration.</li>
</ul>
</div>
</div>
<div class="TextHeading" style="text-align: justify;">
<div class="hddn">
<h2 id="near-real-time-indexing" class="color-purple">Near Real-Time Indexing:</h2>
</div>
</div>
<div class="Content">
<div class="hddn">
<ul>
<li style="text-align: justify;">Apache Solr takes a benefit of Lucene&#8217;s Near Real-Time Indexing capabilities to ensure you to see your content when you would like to notice it</li>
</ul>
</div>
</div>
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