Introduction about Elasticsearch
Elasticsearch is a real-time distributed search and analytics engine. It allows us to explore our data at a speed and at a scale never before possible. It is used for full-text search, structured search, analytics, and all three in combination:
• Wikipedia uses Elasticsearch to provide full-text search with highlighted search snippets, and search-as-you-type and did-you-mean suggestions.
• The Guardian uses Elasticsearch to combine visitor logs with social -network data to provide real-time feedback to its editors about the public’s response to new articles.
• Stack Overflow combines full-text search with geolocation queries and uses more-like-this to find related questions and answers.
• GitHub uses Elasticsearch to query 130 billion lines of code.
If you are picking up this book, it is because you have data, and there is no point in
having data unless you plan to do something with it.
Unfortunately, most databases are astonishingly inept at extracting actionable knowl‐
edge from your data. Sure, they can filter by timestamp or exact values, but can they
perform full-text search, handle synonyms, and score documents by relevance? Can
they generate analytics and aggregations from the same data? Most important, can
they do this in real time without big batch-processing jobs?
This is what sets Elasticsearch apart: Elasticsearch encourages you to explore and uti‐
lize your data, rather than letting it rot in a warehouse because it is too difficult to
query.
Elasticsearch is your new best friend