Indexing Considerations in Software

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a database has data being written to it at very high rates, be sure to include only the indexes that you must include to satisfy the most-used queries In contrast, if data is added to your database very infrequently but is constantly queried, you can be more liberal with the number of indexes you apply Remember, though, that there is such a thing as too much of a good thing If you find that your database has periods that are write-intensive followed by periods that are read-intensive, such as an OLAP database, you may find yourself actually creating and dropping indexes based on data loading processes As with anything else, your mileage may vary, but it is often useful to drop your indexes when large data loads are occurring and then re-create them when the data load is finished so that queries can use them to retrieve data On the flip side of that coin, re-creating the index takes resources So you must trade off the speed of the load versus the speed of re-creating the index Sometimes, it is better to leave the indexes in place during the load
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Way back during the requirements gathering phase, you should have been taking note of general metrics for the system For example, about how many orders per day are processed How many employees use the system concurrently What is the duration of the data that must be kept online six months Two years Knowing these bits of information can help determine what the usage of your database will be The usage will help further define the types of indexes you place on your database For example, in the Mountain View Music database, if we know that 90 percent of the customers use the Web interface and 70 percent of those are returning customers, then we need to make sure that the log-in information lookup is a speedy process It would be unacceptable for the customer to have to wait 90 seconds for the log-in to complete Therefore, we can place a priority on the indexing scheme to make sure that this query is fast In contrast, if we know that once a month the customer service manager will pull a report of all customers who ve placed an order in the past 30 days, we can place a lower priority on creating a covering index for that report (if it performs poorly without any help) Knowing these statistics about the usage of your database will greatly increase your ability to index it correctly
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Determining the Appropriate Indexes
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Determining the Appropriate Indexes
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After you ve built your database and have gathered all the notes about its usage, it s time to start creating indexes In this section, we cover the key things to think about when you create indexes for each table
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As we ve discussed, it s crucial to know how your database is being used Specifically, you need to know how much time is spent writing new data to the database and updating existing data You also need to know how much data is being removed from the database, and about how much of the data will be kept online at any given time Then you need to know how much data retrieval there will be How much data will be queried by the applications versus ad hoc queries Will there even be any ad hoc queries How often These answers will help you produce a logical, efficient index scheme From a procedural standpoint, it s a good idea to go through the database table by table often referencing the data model (for logical reference to the entities) and ask questions of the users and application designers about the various ways the data is used Document their responses, and keep those notes handy when you start indexing your tables Be sure to include both the frequency of the queries being run and an estimate of how much data will be retrieved for each query
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