Search-Engines | CMU 11642 course work - a complete search engine | Search Engine library
kandi X-RAY | Search-Engines Summary
kandi X-RAY | Search-Engines Summary
CMU 11642 course work - a complete search engine
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Top functions reviewed by kandi - BETA
- Main entry point
- Displays the first n postings for a given term
- Displays a term vector
- Lists all term vectors in a document
- Read the ranking map
- Normalizes scores for each document
- Initialize candidate documents
- Sets the maxVent documents
- Converts a timing result into a string
- Returns the tf score for a given field
- Returns the default score for a given document
- Gets the score for a document
- Displays the inverted list
- Gets total feature score
- Returns the default score for the query
- Changes the current index to another index
- Returns a string representation of this query operator
- Get the default score for the query
- Gets the document score for the specified document iterator
- Returns the default score for the query
- Sets the ini ranking map
- Main test method
- Read a query file and generate a query file
- Read query intents map
- Evaluates the query and returns the inverted list
- Main method
Search-Engines Key Features
Search-Engines Examples and Code Snippets
Community Discussions
Trending Discussions on Search-Engines
QUESTION
I am working on my diploma exam with topic of Full-Text Search in Apache SOLR. Within the introduction, I should elaborate what are the purpose and advantages of Apache SOLR, i.e. why would one opt for Full-Text Search engine like SOLR instead of MySQL, for instance. Using literature like "SOLR in action (2013)" one would say it's rather easy to determine when to use SOLR, ElasticSearch or something else, instead of MySQL - for that era. There is also this great question from 2010 on SO: Comparison of full text search engine - Lucene, Sphinx, Postgresql, MySQL?. Alas, as great as it was around 2010, answers now seem painfully obsolete. E.g. "MySQL MyISAM table type supports Full-Text Search, but InnoDB does not". Several years after this InnoDB also added Full-Text Search support. Now, there are some articles that manage to shed some light on this, like https://lucidworks.com/post/full-text-search-engines-vs-dbms/ which states that advantages of Full-Text Search systems are
search speed, variety of indexing and querying options, ranking and relevancy capabilities...
Yet, there are lot of other articles stating things like
MySQL Full-Text Search will now fit your needs in 80% of cases
etc, and it seems that over past 10 years MySql, MongoDB, PostgreSQL and other relational database Full-Text Search capability increased dramatically.
Yet, graph on https://db-engines.com/en/ranking_trend/system/Elasticsearch%3BMySQL%3BSolr shows that Full-Text Search engines are not losing popularity, but their usage is growing, and even SOLR that was losing pace steadily, now seems to be waking up.
So, there must be something to it? Is it that:
- SOLR, Elastic, Sphinx... are still considerably faster than their relational counterparts?
- there is larger variety of options, like advanced, customizable tokenization, faceting? Maybe better languages support?
- relational databases can't handle well enough search on very large number of documents?
etc.
In short, what would make you take Apache SOLR or Elastic nowadays, instead of MySQL or other relational database with their increased Full-Text search capabilities? Why are Apache SOLR and Elastic Search still that popular when using them requires another stack of resources and administration if you already have data in your relational or NoSQL database?
So the central question is: If I have system that uses MySQL database for data storage, and I need to add full text search capabilities for one or several fields, to include fuzzy search (typos), synonyms, stemming, to handle relevancy and ranking in custom way, is it generally better to use MySQL FTS (so no need for another stack of resources and administration) or a dedicated full text search engine like Apache SOLR or Elastic search is significantly enough better at this?
...ANSWER
Answered 2021-Nov-09 at 19:30Specialized indexing solutions like Apache Solr, ElasticSearch, Sphinx Search are usually faster than the built-in fulltext indexing of MySQL or GIST of PostreSQL, etc. The specialized solutions often have more features like stemming, more sophisticated searching including faceting, and also storing extra data in a "document" associated with the indexed text.
On the other hand, using one of those complementary solutions means extra complexity to copy data into the indexing solution. How frequently do you need to update the index? Is it efficient to update the index incrementally, or do you basically need to clobber the index and create a fresh index from your whole dataset?
Whereas using the builtin indexing features of your RDBMS have the advantage that the index is probably kept in sync with the most recent data updates automatically. And the search capabilities may be good enough for your needs. Keeping the index maintenance simple and automated has a lot of positive value.
Besides, any of the solutions, even a sub-optimal one, is orders of magnitude better than the naïve approach many developers use: textcolumn LIKE '%keyword%'
what would make you take Apache SOLR or Elastic nowadays, instead of MySQL or other relational database with their increased Full-Text search capabilities?
Better performance, more sophisticated search support, and it helps to move those expensive search queries to a dedicated search engine, and lighten the load on your RDBMS.
QUESTION
I'm sure this is a basic question, but I just cannot find the right words to ask the almighty search-engines. I'm using the word "selected" in quotes because I don't know the right term for it. I'm sure if I did the question would be readily answered already.
When you press on most webpages, you are able to cycle through the links on the page such that when you press the browser visits the link in question. This is what a selected link looks like in Firefox:
I want to be able to do this automatically on page load, such that immediately after load takes you to the link of my choosing, but any other shenanigans like inputting in an input field cancels this behavior. I've looked through the DOM browser and can see nothing jumping out differentiates "This is a link" from other links on this page.
...ANSWER
Answered 2021-Feb-05 at 12:16It is called focus and you can have only one element focused. As soon as you click to an input your focus moves to it. That's why you can't have focused link while writing in an input at the same time.
Focus determines where keyboard events go in the page at any given moment.
Source & you can read more at: Introduction to Focus | Web Fundamentals
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install Search-Engines
You can use Search-Engines like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the Search-Engines component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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