By Jayant Kumar
Leverage the ability of Apache Solr to energy up your small business by way of navigating your clients to their facts quick and efficiently
About This Book
examine the simplest use circumstances for utilizing Solr in e-commerce, ads, real-estate, and different sites
discover Solr internals and customise the scoring set of rules in Solr
this can be an easy-to-follow e-book with a step by step method of assist you get the easiest out of Solr seek patterns
Who This booklet Is For
This ebook is for builders who already understand how to exploit Solr and are paying for complicated suggestions for bettering their seek utilizing Solr. This e-book can also be for those who paintings with analytics to generate graphs and stories utilizing Solr. furthermore, when you are a seek architect who's anticipating scale your seek utilizing Solr, it is a should have publication for you.
It will be beneficial while you're conversant in the Java programming language.
Apache Solr is an open resource seek platform equipped on a Java library known as Lucene. It serves as a seek platform for plenty of web pages, because it has the potential of indexing and looking out a number of web pages to fetch wanted results.
We commence with a short creation of analyzers and tokenizers to appreciate the demanding situations linked to enforcing large-scale indexing and multilingual seek performance. We then circulation directly to operating with customized queries and figuring out how filters paintings internally. whereas doing so, we additionally create our personal question language or Solr plugin that does proximity searches. moreover, we talk about how Solr can be utilized for real-time analytics and take on difficulties confronted in the course of its implementation in e-commerce seek. We then dive deep into the spatial positive factors similar to indexing techniques and search/filtering innovations for a spatial seek. We additionally do an in-depth research of difficulties confronted in an advert serving platform and the way Solr can be utilized to unravel those problems.
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Extra info for Apache Solr Search Patterns
22 ] Chapter 1 Using the Java binary format of data for indexing Instead of using XML files, we can use the Java bin format for indexing. This reduces a lot of overhead of parsing an XML file and converting it into a binary format that is usable. The way to use the Java bin format is to write our own program for creating fields, adding fields to documents, and finally adding documents to the index. add(doc2); //Add the collection of documents to the Solr server and commit. commit(); Here is the reference to the API for the HttpSolrServer program http://lucene.
Thus, it is important to decide whether to normalize diacritics or not. Let us translate the same sentence into Japanese and see what we get: Japanese Now that the complete sentence does not have any whitespace to separate the words, how do we identify words or tokens and index them? The Japanese analyzer available in our Solr schema configuration is text_ja. This analyzer identifies the words in the sentence and creates tokens. A few tokens identified are as follows: Japanese tokens It also identifies some of the stop words and removes them from the sentence.
During the search, we can use a WhiteSpaceTokenizer and a LowerCaseFilter tokenizer to tokenize and process our input text. In a real-life situation, it is advisable to take multiple examples with different use cases and work around the scenarios to provide the desired solutions for those use cases. Given that the numbers of examples are large, the derived solution should satisfy most of the cases. If we translate the same sentence into German, here is how it will look: German Solr comes with an inbuilt field type for German - text_de, which has a StandardTokenizer class followed by a lowerCaseFilter class and a stopFilter class for German words.
Apache Solr Search Patterns by Jayant Kumar