anchor.diff:  
   In addition to the `match_all`, `match`, `bool`, and `range` queries, there are a lot of other query types that are available and we won't go into them here. Since we already have a basic understanding of how they work, it shouldn't be too difficult to apply this knowledge in learning and experimenting with the other query types.
   
  +[[getting-started-aggregations]]
   === Executing Aggregations
   
   Aggregations provide the ability to group and extract statistics from your data. The easiest way to think about aggregations is by roughly equating it to the SQL GROUP BY and the SQL aggregate functions. In Elasticsearch, you have the ability to execute searches returning hits and at the same time return aggregated results separate from the hits all in one response. This is very powerful and efficient in the sense that you can run queries and multiple aggregations and get the results back of both (or either) operations in one shot avoiding network roundtrips using a concise and simplified API.
  
positive.code: 
  Here, we can see our one node named "PB2SGZY", which is the single node that is currently in our cluster.
  
  === List All Indices
  
  Now let's take a peek at our indices:
  
negative.code: 
  You might also notice that the customer index has a yellow health tagged to it. Recall from our previous discussion that yellow means that some replicas are not (yet) allocated. The reason this happens for this index is because Elasticsearch by default created one replica for this index. Since we only have one node running at the moment, that one replica cannot yet be allocated (for high availability) until a later point in time when another node joins the cluster. Once that replica gets allocated onto a second node, the health status for this index will turn to green.
  
  [[getting-started-query-document]]
  === Index and Query a Document
  
  Let's now put something into our customer index. We'll index a simple customer document into the customer index, with an ID of 1 as follows:
  