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Comment:Another minor formatting fix.
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SHA3-256: 9fa2ce3c2b75408594d387684984cd946765776d30bc622a1f4e64d6fe1856d5
User & Date: dan 2017-04-21 19:58:35.957
Context
2017-05-01
14:25
Update this branch with latest trunk changes. (check-in: 11f4761c3a user: dan tags: schemalint)
2017-04-21
19:58
Another minor formatting fix. (check-in: 9fa2ce3c2b user: dan tags: schemalint)
19:56
Fix formatting errors in the previous commit. (check-in: da9a2e5aa9 user: dan tags: schemalint)
Changes
Unified Diff Ignore Whitespace Patch
Changes to ext/expert/README.md. 
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## SQLite Expert Extension

This folder contains code for a simple system to propose useful indexes
given a database and a set of SQL queries. It works as follows:

  1. The user database schema is copied to a temporary database.

  1. All SQL queries are prepared against the temporary database.
     Information regarding the WHERE and ORDER BY clauses, and other query
     features that affect index selection are recorded.

  1. The information gathered in step 2 is used to create candidate indexes
     - indexes that the planner might have made use of in the previous step,
     had they been available.

  1. A subset of the data in the user database is used to generate statistics
     for all existing indexes and the candidate indexes generated in step 3
     above.

  1. The SQL queries are prepared a second time. If the planner uses any
     of the indexes created in step 3, they are recommended to the user.












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## SQLite Expert Extension

This folder contains code for a simple system to propose useful indexes
given a database and a set of SQL queries. It works as follows:

  1. The user database schema is copied to a temporary database.

  1. All SQL queries are prepared against the temporary database.
     Information regarding the WHERE and ORDER BY clauses, and other query
     features that affect index selection are recorded.

  1. The information gathered in step 2 is used to create candidate 
     indexes - indexes that the planner might have made use of in the previous
     step, had they been available.

  1. A subset of the data in the user database is used to generate statistics
     for all existing indexes and the candidate indexes generated in step 3
     above.

  1. The SQL queries are prepared a second time. If the planner uses any
     of the indexes created in step 3, they are recommended to the user.
︙︙