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ElasticSearch Blueprints

ElasticSearch Blueprints

By : Mohan
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ElasticSearch Blueprints

ElasticSearch Blueprints

3 (2)
By: Mohan

Overview of this book

If you are a data enthusiast and would like to explore and specialize on search technologies based on Elasticsearch, this is the right book for you. A compelling case-to-case mapping of features and implementation of Elasticsearch to solve many real-world use cases makes this book the right choice to start and specialize on Elasticsearch.
Table of Contents (10 chapters)
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9
Index

Pagination

While searching, users can't view all the results at once. They like to see one batch at a time. Usually, a single batch contains 10 matched documents, as in Google search results, where each page contains 10 search results. This also gives us an advantage over the search engine as it need not send all the results back at once. The following is how we use pagination in Elasticsearch. Let's say that we are interested in seeing only five results at a time, then to get the first page, we have to use the following parameters:

  • size = 5 (defaults to 10).
  • from = 0, 5, 10, 15, 20 (defaults to 0). This depends on the page number you need.

Also, it should be noted that the total number of pages can be calculated from count/_size. Sample query for the page 5 of the search result where we show 5 results at a time:

{
"from" : 4 ,
"size" : 5,
"query": {… }  }

This is how the complete query looks, which enables pagination and highlighting:

{
  "from": 0,
  "size": 10,
  "query": {
    "simple_query_string": {
      "query": "china",
      "fields": [
        "_all"
      ]
    }
  },
  "highlight": {
    "fields": {
      "html": {
        "pre_tags": [
          "<p>"
        ],
        "post_tags": [
          "</p>"
        ],
        "fragment_size": 10,
        "number_of_fragments": 3
      }
    }
  }
}

The head UI explained

When you open the head page, you see a UI that lists all the indexes and all the information related to it. Also, by looking at the tabs to the left, you know how well your cluster is doing, as shown in the following figure:

The head UI explained

Now, take the Browser tab in the head UI. You will see all the feeds you index here. Note that it shows only the first 10 indexed feeds.

The head UI explained

Now, on selecting one of your feeds, a nice model window appear, showing you the following view:

The head UI explained

In this chapter, we looked at how we can deploy Elasticsearch. We had a quick look at of how to set an analyzer and index some documents. Then, we attempted to search for a document we indexed. We will look at how pagination and highlighting work in later sections of this book.

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