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Learn Apache Solr with Big Data and Cloud Computing (Udemy.com)

Apache Solr, Zookeeper, Clusters, Replication, Cloud, Big data, Search algorithms and Much More

Created by: QScutter Tutorials

Last updated September 2014

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What you will learn

  • Integrate Search functionality into any web or mobile app
  • Understand Cloud
  • Solve Search problem of big data
  • You can build your own search engine

How it compares

Against the other 388 rated Udemy courses in SQL on CourseDuck:

  • Rating3.6 out of 5higher than 1% of them
  • Reviews392#229 of 389 by number of reviews
  • Length5.1 hoursshorter than 59% of them
  • Last updatedSeptember 2014earlier than 99% of them

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Course Description

Solr is the popular, blazing fast open source enterprise search platform from the Apache LuceneTMproject. Its major features include powerful full-text search, hit highlighting, faceted search, near real-time indexing, dynamic clustering, database integration, rich document (e.g., Word, PDF) handling, and geospatial search. Solr is highly reliable, scalable and fault tolerant, providing distributed indexing, replication and load-balanced querying, automated failover and recovery, centralized configuration and more. Solr powers the search and navigation features of many of the world's largest internet sites.

Solr is written in Java and runs as a standalone full-text search server within a servlet container such as Jetty. Solr uses the Lucene Java search library at its core for full-text indexing and search, and has REST-like HTTP/XML and JSON APIs that make it easy to use from virtually any programming language. Solr's powerful external configuration allows it to be tailored to almost any type of application without Java coding, and it has an extensive plugin architecture when more advanced customization is required.

Solr Features

Solr is a standalone enterprise search server with a REST-like API. You put documents in it (called "indexing") via XML, JSON, CSV or binary over HTTP. You query it via HTTP GET and receive XML, JSON, CSV or binary results.

  • Advanced Full-Text Search Capabilities
  • Optimized for High Volume Web Traffic
  • Standards Based Open Interfaces - XML, JSON and HTTP
  • Comprehensive HTML Administration Interfaces
  • Server statistics exposed over JMX for monitoring
  • Linearly scalable, auto index replication, auto failover and recovery
  • Near Real-time indexing
  • Flexible and Adaptable with XML configuration
  • Extensible Plugin Architecture

Solr Uses the LuceneTM Search Library and Extends it!

  • A Real Data Schema, with Numeric Types, Dynamic Fields, Unique Keys
  • Powerful Extensions to the Lucene Query Language
  • Faceted Search and Filtering
  • Geospatial Search with support for multiple points per document and geo polygons
  • Advanced, Configurable Text Analysis
  • Highly Configurable and User Extensible Caching
  • Performance Optimizations
  • External Configuration via XML
  • An AJAX based administration interface
  • Monitorable Logging
  • Fast near real-time incremental indexing and index replication
  • Highly Scalable Distributed search with sharded index across multiple hosts
  • JSON, XML, CSV/delimited-text, and binary update formats
  • Easy ways to pull in data from databases and XML files from local disk and HTTP sources
  • Rich Document Parsing and Indexing (PDF, Word, HTML, etc) using Apache Tika
  • Apache UIMA integration for configurable metadata extraction
  • Multiple search indices

Detailed Features

Schema

  • Defines the field types and fields of documents
  • Can drive more intelligent processing
  • Declarative Lucene Analyzer specification
  • Dynamic Fields enables on-the-fly addition of new fields
  • CopyField functionality allows indexing a single field multiple ways, or combining multiple fields into a single searchable field
  • Explicit types eliminates the need for guessing types of fields
  • External file-based configuration of stopword lists, synonym lists, and protected word lists
  • Many additional text analysis components including word splitting, regex and sounds-like filters
  • Pluggable similarity model per field

Query

  • HTTP interface with configurable response formats (XML/XSLT, JSON, Python, Ruby, PHP, Velocity, CSV, binary)
  • Sort by any number of fields, and by complex functions of numeric fields
  • Advanced DisMax query parser for high relevancy results from user-entered queries
  • Highlighted context snippets
  • Faceted Searching based on unique field values, explicit queries, date ranges, numeric ranges or pivot
  • Multi-Select Faceting by tagging and selectively excluding filters
  • Spelling suggestions for user queries
  • More Like This suggestions for given document
  • Function Query - influence the score by user specified complex functions of numeric fields or query relevancy scores.
  • Range filter over Function Query results
  • Date Math - specify dates relative to "NOW" in queries and updates
  • Dynamic search results clustering using Carrot2
  • Numeric field statistics such as min, max, average, standard deviation
  • Combine queries derived from different syntaxes
  • Auto-suggest functionality for completing user queries
  • Allow configuration of top results for a query, overriding normal scoring and sorting
  • Simple join capability between two document types
  • Performance Optimizations

Core

  • Dynamically create and delete document collections without restarting
  • Pluggable query handlers and extensible XML data format
  • Pluggable user functions for Function Query
  • Customizable component based request handler with distributed search support
  • Document uniqueness enforcement based on unique key field
  • Duplicate document detection, including fuzzy near duplicates
  • Custom index processing chains, allowing document manipulation before indexing
  • User configurable commands triggered on index changes
  • Ability to control where docs with the sort field missing will be placed
  • "Luke" request handler for corpus information

Caching

  • Configurable Query Result, Filter, and Document cache instances
  • Pluggable Cache implementations, including a lock free, high concurrency implementation
  • Cache warming in background
  • When a new searcher is opened, configurable searches are run against it in order to warm it up to avoid slow first hits. During warming, the current searcher handles live requests.
  • Autowarming in background
  • The most recently accessed items in the caches of the current searcher are re-populated in the new searcher, enabling high cache hit rates across index/searcher changes.
  • Fast/small filter implementation
  • User level caching with autowarming support

SolrCloud

  • Centralized Apache ZooKeeper based configuration
  • Automated distributed indexing/sharding - send documents to any node and it will be forwarded to correct shard

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Instructor Details

QScutter Tutorials

QScutter is a Indian based company that offers an ever growing range of high quality eLearning solutions that teach using studio quality narrated videos backed-up with practical hands-on examples. The emphasis is on teaching real life skills that are essential in today's commercial environment. We provide tutorials for almost all IT topics.

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Reviews

3.6

392 ratings on Udemy

Select a bar to show only those reviews.Select the bar again to show every rating.

By M Lane on 7/6/2023

Total waste of my time waiting and being forced to watch instructor type out commands and demonstrations. He should've been more prepared in advance. Demonstrations were also formatted terribly...too small, no separation of lines. Finally, the presented version of Solr is way outdated. This course needs to be updated!

By Anil Piduri on 12/16/2020

Course not updated with latest version of Solr available. Initial setup using instructions provided by the instructor with latest available version did not work. I had to spend time troubleshooting with online forums to get up and running. Once the base version was up, the course was helpful to learn the key concepts of Solr.

By José Adelino Jacob Póvoa on 9/11/2020

Instrutor tem uma dicção horrível, algumas vezes não se preocupa com dar um zoom nas telas e, em outras, ainda trabalha com telas menores dentro da principal. Além disso, a transcrição (nas legendas) coloca palavras sem sentido (talvez, pelo não entendimento do que foi dito pelo instrutor).

By Paul Jansen van Vuuren on 7/5/2020

I've worked with SOLR before so needed a quick hands on for some of the features like suggest, more like this, spelling, facet ranges, etc. This course offered me what I was looking for.

By Swaminathan Krishnamoorthy on 8/31/2019

I already worked as SOLR developer, this course I choose to recollect all basic of SOLR. I like this course, which is useful for beginners and for me. Is there any advance course available? Need more videos on analyzer, Tokenizer, SOLRJ, API, Custom connector, entity extraction etc as part of Advance SOLR. If possible, give hands on exercise or small POC.

By Mark moyou on 4/1/2019

This was a really great introductory course to Solr. Even though the version of solr in the lectures is out of date the content is priceless. This guy does a great job of explaining all the details in very simple terms. I am a data scientist working for an enterprise search company and interact with Solr everyday. This class has explained many things to me and allowed me to get a $30K increase in salary. For the price the knowledge you get is unbeatable. You can always look at the docs but to get someone to explain stuff to you is difficult and that is what this course delivers. All lessons learned can be applied to later versions of Solr. Thank you for putting this course together you have now made me an expert at my job

By Gabriel Fabian on 1/11/2019

This course is extremely out of date and the content is nearly word for word from the official Apache Solr Reference guide. The instructor does a decent job of explaining the topics but is unavailable for questions and there are no course resources. Do not recommend.

By Mohammad Shaikh on 3/1/2015

would made it 5 star if dataimport handler would had been covered as well as the api SOLRJ, otherwise it kind of has everything, the instructor knows what he is teaching, however he could have slowed down at certain places. Thanks much, i learned a lot from this.

By Jacob Palmer Aves Investments on 10/21/2014

It's clear this is first-take instruction, but the information provided is really informative. I get really excited as a web app product owner when I see the implications of Apache. I definitely recommend this course, for the price you can't beat it!

By Kris Matusiak on 10/2/2014

I wanted an overview of Solr capabilities and of ways to use it. The author addresses most Solr: I can set it up and experiment on my own with confidence after this course. There are tons of configuration details that the course does not address: this is a good thing. Not all of them are relevant at all times. Plus the author quotes sites where to find information about the things he does not get into the details of. The videos are short and atomic: no twenty topics in one video. This makes it easy to find information back later. There is one inconsistency: when dealing with query boosting, the author confuses the operators a little bit: the '^' and the '~'. This could use some clarification: the '~' operator works differently when used on a single term, and when used on multiple terms. The author says he never used these operators himself, but that is not an excuse [that is why one star is taken off the rating]. However, it only takes a little look through the documentation to get what is the purpose of these operators. In ten minutes, the author sets up an entire Solr cloud! He makes it look easy: which it is supposed to be. This is a definite plus point. Maybe showing an example with actual running nodes would be an improvement: the configuration is different when working on the local machine only. All in all: suitable for Solr beginners that want to quickly set it up and see what it can do, or test if it is suitable for their application.

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Overall Score : 72 / 100