A mapping is analogous to the table in a database; it contains fields that are equivalent to the columns in a table. However, a mapping is only a logical separation; it does not physically separate the data between mappings as tables do in a database. When data gets added to an index, they are all stored as documents in Lucene. Although Elasticsearch supports schema-less data ingestion, we should always predefine fields so that we know exactly what data types are mapped instead of relying on Elasticsearch to detect data types, which sometimes may produce undesired results. In this section, we will demonstrate field mappings for a news article's index.
We will be using the put mapping API to predefine fields. Here is an example:
curl -XPUT "localhost:9200/news/_mapping/article" -d '
{
"article" : {
"properties" : {
"title" : {"type" : "string", "store" : true, "index" : "analyzed" },
"content": {"type" : "string", "store" : true, "index...