Scaling proceeds in two ways when it comes to handling large amounts of data, horizontally or vertically. Vertical scaling deals with the problems of handling large data by adding bigger and bigger machines. Suppose a single machine which has 4 GB of RAM and 4 CPU can handle a concurrency of 100 queries per second on a data size of say 8 GB. As the amount of data increases, the amount of processing required for serving the queries also increases. Therefore, if the data size goes to 16 GB, the query concurrency that the same machine can handle will be 75 queries instead of 100. For vertical scaling, we would replace the current 4 GB + 4 CPU machine with an 8 GB + 8 CPU machine, which should again be able to serve a concurrency of 100 queries per second on a data size of 16 GB. Horizontal scaling would mean that we add another machine of the same configuration 4 GB RAM + 4 CPU to the system and divide 16 GB of data into two parts of 8 GB each. Each machine now hosts...
Apache Solr Search Patterns
By :
Apache Solr Search Patterns
By:
Overview of this book
Table of Contents (17 chapters)
Apache Solr Search Patterns
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
Solr Indexing Internals
Customizing the Solr Scoring Algorithm
Solr Internals and Custom Queries
Solr for Big Data
Solr in E-commerce
Solr for Spatial Search
Using Solr in an Advertising System
AJAX Solr
SolrCloud
Text Tagging with Lucene FST
Index
Customer Reviews