anchor.diff:  // CONSOLE
   // TEST[continued]
   
  -Dissecting the above, the bool query contains a `match_all` query (the query part) and a `range` query (the filter part). We can substitute any other queries into the query and the filter parts. In the above case, the range query makes perfect sense since documents falling into the range all match "equally", i.e., no document is more relevant than another.
  -
  -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]]
   == Analyze results with 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.
  -
  -To start with, this example groups all the accounts by state, and then returns the top 10 (default) states sorted by count descending (also default):
  +{es} aggregations enable you to get meta-information about your search results
  +and answer questions like, "How many account holders are in Texas?" or 
  +"What's the average balance of accounts in Tennessee?" You can search 
  +documents, filter hits, and use aggregations to analyze the results all in one
  +request. 
  +
  +For example, the following request uses a `terms` aggregation to group
  +all of the accounts in the `bank` index by state, and returns the ten states
  +with the most accounts in descending order:
   
   [source,js]
   --------------------------------------------------
  
positive.code: Expand-Archive elasticsearch-{version}-windows-x86_64.zip
  --------------------------------------------------
  
  . Start elasticsearch from the `bin` directory:
  +
  Linux and macOS:
  +
  
negative.code: // CONSOLE
  // TEST[continued]
  
  To construct more complex queries, you can use a `bool` query to combine
  multiple query criteria. You can designate criteria as required (must match), 
  desirable (should match), or undesirable (must not match).
  
  For example, the following request searches the `bank` index for accounts that
  belong to customers who are 40 years old, but excludes anyone who lives in
  Idaho (ID):
  
  [source,js]
  --------------------------------------------------
  