the way data is stored is so different that any comparisons can hardly make sense, and this ultimately led to an overuse of types in cases where they were more harmful than helpful.An index is stored in a set of shards, which are themselves Lucene indices. This already gives you a glimpse of the limits of using a new index all the time: Lucene indices have a small yet fixed overhead in terms of disk space, memory usage and file descriptors used. For that reason, a single large index is more efficient than several small indices: the fixed cost of the Lucene index is better amortized across many documents.
types are a convenient way to store several types of data in the same index, in order to keep the total number of indices low for the reasons exposed above... One nice property of types is that searching across several types of the same index comes with no overhead compared to searching a single type: it does not change how many shard results need to be merged
getIndices method:IndexBuilder model assists with the creation and mapping of indexes. Mappings define the allowable data types within your documents and allow for better and more accurate search aggregations. Let's say we have a book model that we intend to make searchable. We are storing this in our bookshop index, under the type of book. Let's create the index (if it doesn't exist) and map the type of book:new() method is called:IndexBuilder object to the [email protected] instance's applyIndex( required IndexBuilder indexBuilder ) method, if we wished.new() method to do so:IndexBuilder model also provides a convenience method for updating the mapping or settings on an index:getAliases method allows you to retrieve a map containing information on aliases in use in the connected cluster.aliases and unassgined. The former is a map of aliases with their corresponding index, the latter is an array of indexes which are unassigned to any alias.AliasBuilder for assistance in adding and removing index aliases.applyAliases method. These operations are performed in the same transaction (i.e. atomic), so it's safe to use for switching the alias from one index to another.v1.0.0 the MappingBuilder model provides a fluent closure-based sytax for defining and mapping indexes. This builder can be accessed by injecting it into your components:new method of the IndexBuilder also accepts a closure as the second (properties) argument. If a closure is passed, a MappingBuilder instance is passed as an argument to the closure:MappingBuilder has one primary method: create. create takes a callback with a MappingBlueprint object, usually aliased as mapping.MappingBlueprint gives a fluent api to defining a mapping. It has methods for all the ElasticSearch mapping types:object expects a closure which will be provided another MappingBlueprint. The results will be set as the properties of the object call.onMissingMethod and will use the method name (as snake case) as the parameter name and the first argument passed as the parameter value.You can also add parameters using theaddParameter( string name, any value )orsetParameters( struct map )methods.
fields which expects a closure argument and allows you to create multiple field definitions for a mapping.user mapping that gets repeated for managers as well.getPartial method 1. A WireBox mapping to a component with a getPartial methodreindex method on the Client.false to the waitForCompletion flag. When this flag is set to false the method will return a Task instance, which can be used to follow up on the completion status of the reindex process.source and destination.waitForCompletion and the reindex action fails, a cbElasticsearch.JestClient.ReindexFailedException will be thrown. You can disable the exception by passing false to the throwOnError parameter.