Elasticsearch is a distributed, open source search and analytics engine for all types of data, including textual, numerical, geospatial, structured, and unstructured.
Both Java and Elasticsearch is a popular technology stack companies use. Java is a programming language that was released back in 1996. Currently, Java is acquired by Oracle and still in active development. Elasticsearch is a young technology when we compare it to Java, it has only released in 2010
If we want to create a good search engine with Elasticsearch, knowing how Analyzer works is a must. A good search engine is a search engine that returns relevant results. When the user queried something in our Search Engine, we need to return the documents relevant to the user query.
Typo is something that often happens and can reduce user’s experience, fortunately, Elasticsearch can handle it easily with Fuzzy Query. Handling typos is a must if you’re building an advanced autocomplete system with the Elasticsearch.
Autocomplete is a feature to predict the rest of a word a user is typing. It is an important feature to implement that can improve the user’s experience of your product.
Many people that have just started learning Elasticsearch often confuse the Text and Keyword field data type. The difference between them is simple, but very crucial.
Elasticsearch has been used more and more in the software engineering, data and DevOps fields. In this post I will write about the basics of elasticsearch from developer perspective. So what is the definition of elasticsearch? according to elasticsearch’s website: Elasticsearch is a distributed, open source search and analytics