Differences

This shows you the differences between two versions of the page.

--- admin:lifecycle:design [2009/11/29 19:11]
els
+++ — (current)
@@ Line 1: / Line 1: @@
-{{page>:top_add&nofooter&noeditbtn}}
-<html><div align="center"><span style="color:red">DRAFT</span></div></html>
-====== The Omnidex Application Lifecycle ======
-===== Design =====
-As with most applications, this is the most important step of the entire application lifecycle.  During the design step, key decisions are made about how to approach Omnidex queries and updates in the application.  These decisions can lead to high-performing applications, and they can also lead to poor performance.  It is worth spending the needed time on this step.
-This article focuses on the design steps for an Omnidex Application.  It does not focus on the steps for application design in general.  These steps should be interwoven with the design steps needed for the overall application.  Designing an Omnidex Application has six important steps:
-  - [[#Deciding_on_an_architecture|Deciding on an architecture]]
-  - [[#Understanding_the_data_model|Understanding the data model]]
-  - [[#Designing_an_indexing_strategy|Designing an indexing strategy]]
-  - [[#Prototyping_on_the_data_server|Prototyping on the data server]]
-  - [[#Optimizing_queries|Optimizing queries]]
-  - [[#Prototyping_the_application|Prototyping the application]]
-==== Deciding on an Architecture ====
-An Omnidex architecture is a plan for where the various components of the application will reside and how they will talk to each other.  In the simplest applications, everything resides on a single machine.  There may not even be a web server or an application server.  In more traditional applications, there is a web server, an application server and a data server, often on three separate machines.
-Omnidex adds three new concepts that affect the application architecture: Omnidex Snapshots,  Omnidex Grids and Omnidex Index Servers.  These concepts add a great deal of flexibility to the application architecture and are worth considering before embarking on a full application.
-In brief, Omnidex Snapshots are simple copies of the database stored in flat files that can be indexed and queried as independent databases.  Omnidex Snapshots are quite convenient because they can be heavily indexed and then easily distributed to different servers.  Many businesses direct much of their query traffic to Omnidex Snapshots, gaining performance in their application while reducing the load on their relational database. This assures the highest performance without requiring changes to the data model.
-Omnidex Grids allow large databases to be partitioned to improve performance and scalability.  Databases with over 20 million rows are candidates for Omnidex Grids, and there are several strategies for distributing the nodes of the grid to achieve the greatest flexibility and performance. Omnidex Grids are also a common way to incorporate large amounts to new data.  Large volumes of data can be added to a new node in the grid without having to affect the entire database.
-Omnidex Index Servers are similar to Omnidex Snapshots, but they only distribute the Omnidex indexes rather than a full copy of the database.  In many applications, Omnidex resolves most of the queries using only the Omnidex indexes.  This is especially true in applications that rely heavily on obtaining counts or aggregations.  Applications may direct these types of queries to Omnidex Index Servers, improving performance and easing the load on the data server.
-Architects would benefit from a deeper understanding of these concepts, and are encouraged to ready the article on [[admin:architecture:home|Omnidex Architecture]].
-==== Understanding the Data Model ====
-A good indexing strategy requires an understanding of the data model.  Specifically, it is important to understand the database schema, the table and column cardinalities and the pattern of queries.
-== Database Schema ==
-A basic database schema shows all the tables, their respective columns and datatypes, and their respective primary and foreign constraints. This schema provides an understanding of the table relationships and will be used to optimize table joins.  The schema also provides a list of columns for identifying likely candidates for indexing.
-Database schemas can be obtained from the underlying relational database, or can be obtained using the Omnidex Administrator program.
-== Table and Column Cardinalities ==
-Table cardinalities show the number of rows in each table.  Column cardinalities show the number of distinct values in each column.  For example, a table containing name and addresses about people may have a table cardinality of 300 million, meaning that there are 300 million rows in the table.  The GENDER column may have a column cardinality of two, meaning that there are two distinct values in the column. These cardinalities are important to predicting query performance and to tuning queries.
-Cardinalities can be obtained from the underlying relational database, or can be obtained using the Omnidex Administrator after an UPDATE STATISTICS statement has been completed on a table.
-== Sample SQL Queries ==
-Sample SQL queries show the patterns of queries that are expected in an application.  These query patterns are key to determining an indexing strategy.  When an application is first being prototyped, designers often index everything using Omnidex, but this can result in over-indexing and it doesn't insure that the correct indexing options are used on each column.  It also does not insure that table joins and aggregations will be properly optimized.  A review of the query patterns insures the best performance for the least cost.
-Sample queries can be logged in most relational databases.  Omnidex can also log queries; however, that requires that Omnidex is already integrated into the application.
-When analyzing SQL queries, there are several patterns to recognize:
-  * **Table Joins** - It is important to identify which tables are being accessed and how they are being joined together.  Omnidex frequently optimizes table joins.  Also note any nested queries, as these are similar to table joins.
-  * **Criteria Columns** - Columns found in the WHERE clause of a SQL statement usually correlate with Omnidex indexes.  The literal values in the criteria are not particularly important unless they contain LIKE operators and wildcards.  Note any columns that would benefit from textual indexing.
-  * **Aggregations** - Queries that use the COUNT, SUM, AVERAGE, MIN or MAX functions indicate  opportunities for optimization in Omnidex.  Note the columns being aggregated and the columns referenced in the GROUP BY clause.
-  * **Ordering** - Queries that use ORDER BY clauses indicate opportunities for optimization in Omnidex.  Note the sequence of columns referenced in ascending ORDER BY clauses.
-  * **Select Items** - In some situations, Omnidex may fulfill the query solely from the Omnidex indexes.  Select items can be drawn from the indexes, eliminating the need to go to the underlying data.  Note queries that return just a few columns.
-====  Designing an Indexing Strategy ====
-An Omnidex indexing strategy is quite different from a relational database indexing strategy.  With relational databases, it is customary to identify a few commonly-used columns to index.  The relational database uses those indexes to retrieve portions of underlying data, thereby reducing the amount of disk access.  At the same time, these indexes may help resolve some of the criteria, some of the aggregations and some of the ordering.  Once this subset of data has been retrieved from disk, the relational database then processes the data to fulfill the remaining aspects of the query.
-Omnidex takes a different approach. Omnidex encourages administrators to index ALL of the elements of the query, and it will use many indexes at the same time to satisfy a query.  A query may have 20 pieces of criteria, 20 table joins and a complex aggregation; yet with proper indexing, Omnidex can satisfy the query without ever going to the underlying data.  This dramatically reduces the amount of disk access, leading to tremendous increases in performance.
-Omnidex can afford to take this approach because it builds indexes quickly and batches multiple indexes together.  Omnidex also compresses its index, resulting in much less disk space.  It is fairly common to have over a hundred Omnidex indexes on a table, yet the indexes are built more quickly and take less disk space than just a few indexes in the relational database.
-Designing an indexing strategy begins with listing all of the columns that are used as criteria in queries.  While Omnidex can process criteria that is not indexed, it is affordable enough that administrators using start by indexing all of the columns used in criteria.  Based on evaluating the query patterns, administrators will then pick the options needed on each index, such as textual indexing and case sensitivity.
-Table joins are usually optimized by indexing the join columns.  In the case of parent-child relationships, the foreign key in the child is usually indexed.  Some parent-child relationships can even be pre-joined, meaning that the index is created with the internal join information embedded.  Nested queries are usually optimized in a fashion similar to table joins.  The inner query is optimized independently, and then the outer query's corresponding criteria column is indexed.
-Simple counts do not require any special indexing beyond indexing the criteria columns and optimizing the table joins.  More complex aggregations, such as distinct counts, sums, averages, mins and maxs, requiring an index containing the group by columns and the aggregated columns.  Similarly, ascending order by clauses are optimized with an index containing all of the columns in the order by clause.
-Once an initial indexing strategy has been designed, administrators usually create a small test database, perhaps using an Omnidex Snapshot, and then test the sampled queries.  The query plan for each query will show whether it is fully optimized.  The goal of the administrator at this stage is to insure that most, if not all, of the queries are well optimized.
-{{page>:bottom_add&nofooter&noeditbtn}}

Back to top

admin/lifecycle/design.1259521899.txt.gz · Last modified: 2012/10/26 14:25 (external edit)

Sitemap Recent Changes