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Elasticsearch 8.x Cookbook

You're reading from   Elasticsearch 8.x Cookbook Over 180 recipes to perform fast, scalable, and reliable searches for your enterprise

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Product type Paperback
Published in May 2022
Publisher Packt
ISBN-13 9781801079815
Length 750 pages
Edition 5th Edition
Languages
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Author (1):
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Alberto Paro Alberto Paro
Author Profile Icon Alberto Paro
Alberto Paro
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Toc

Table of Contents (20) Chapters Close

Preface 1. Chapter 1: Getting Started 2. Chapter 2: Managing Mappings FREE CHAPTER 3. Chapter 3: Basic Operations 4. Chapter 4: Exploring Search Capabilities 5. Chapter 5: Text and Numeric Queries 6. Chapter 6: Relationships and Geo Queries 7. Chapter 7: Aggregations 8. Chapter 8: Scripting in Elasticsearch 9. Chapter 9: Managing Clusters 10. Chapter 10: Backups and Restoring Data 11. Chapter 11: User Interfaces 12. Chapter 12: Using the Ingest Module 13. Chapter 13: Java Integration 14. Chapter 14: Scala Integration 15. Chapter 15: Python Integration 16. Chapter 16: Plugin Development 17. Chapter 17: Big Data Integration 18. Chapter 18: X-Pack 19. Other Books You May Enjoy

Using explicit mapping creation

If we consider the index as a database in the SQL world, mapping is similar to the create table definition.

Elasticsearch can understand the structure of the document that you are indexing (reflection) and create the mapping definition automatically. This is called explicit mapping creation.

Getting ready

To execute the code in this recipe, you will need an up-and-running Elasticsearch installation, as described in the Downloading and installing Elasticsearch recipe of Chapter 1, Getting Started.

To execute these commands, you can use any HTTP client, such as curl (https://curl.haxx.se/), Postman (https://www.getpostman.com/), or similar platforms. I suggest using the Kibana console to provide code completion and better character escaping for Elasticsearch.

To understand the examples and code in this recipe, basic knowledge of JSON is required.

How to do it…

You can explicitly create a mapping by adding a new document to Elasticsearch. For this, perform the following steps:

  1. Create an index, as shown in the following code:
    PUT test

The output will be as follows:

{ "acknowledged" : true, "shards_acknowledged" : true,
 "index" : "test" }
  1. Put a document in the index, as shown in the following code:
    PUT test/_doc/1
    {"name":"Paul", "age":35}

The output will be as follows:

{
  "_index" : "test", "_id" : "1", "_version" : 1,
  "result" : "created",
  "_shards" : {"total" : 2, "successful" : 1, "failed" : 0 },
  "_seq_no" : 0,  "_primary_term" : 1
}
  1. Get the mapping with the following code:
    GET test/_mapping
  2. The mapping that's auto-created by Elasticsearch should look as follows:
    {
      "test" : {
        "mappings" : {
          "properties" : {
            "age" : { "type" : "long" },
            "name" : {
              "type" : "text",
              "fields" : {
                "keyword" : {"type" : "keyword", "ignore_above" : 256 }
    } } } } } }
  3. To delete the index, you can use the following command:
    DELETE test

The output will be as follows:

{ "acknowledged" : true }

How it works…

The first command line (Step 1) creates an index where we can configure the mappings in the future, if required, and store documents in it.

The second command (Step 2) inserts a document in the index (we'll learn how to create the index in the Creating an index recipe of Chapter 3, Basic Operations, and record indexing in the Indexing a document recipe of Chapter 3, Basic Operations).

Elasticsearch reads all the default properties for the field of the mapping and starts to process them as follows:

  • If the field is already present in the mapping and the value of the field is valid (it matches the correct type), Elasticsearch does not need to change the current mappings.
  • If the field is already present in the mapping but the value of the field is of a different type, it tries to upgrade the field type (that is, from integer to long). If the types are not compatible, it throws an exception, and the indexing process fails.
  • If the field is not present, it tries to auto-detect the type of field. It updates the mappings with a new field mapping. (In the case of a null value, it skips the mapping update until it encounters a concrete type.)

There's more…

In Elasticsearch, every document has a unique identifier, called an ID for a single index, which is stored in the special _id field of the document.

The _id field can be provided at index time or can be assigned automatically by Elasticsearch if it is missing.

When a mapping type is created or changed, Elasticsearch automatically propagates mapping changes to all the nodes in the cluster so that all the shards are aligned to process that particular type.

In Elasticsearch 7.x, there was a default type (_doc): it was removed in Elasticsearch 8.x and above.

See also

Please refer to the following recipes in Chapter 3Basic Operations:

  • The Creating an index recipe, which is about putting new mappings in an index while it's being created
  • The Putting a mapping in an index recipe, which is about extending a mapping in an index
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Elasticsearch 8.x Cookbook - Fifth Edition
Published in: May 2022
Publisher: Packt
ISBN-13: 9781801079815
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