![]() ![]() You also need to add each server to all of the others participating in the federation as linked servers. For example, assuming that we create two partitions for data tracking sales records in two different states (‘NJ’ and ‘NY’), we could create two tables Sales_NJ and Sales_NY, the first one in a databases on New Jersey SQL server, the second one in a database on New York SQL server: The criteria used by the CHECK constraint are used to make sure that any of the rows in the table can belong to only a single partition. ![]() Each table should contain the CHECK constraint, enforcing uniqueness of all partitioned data sets. Once you determined the distribution of the data in a table (or tables) across the partitions, you will need to create replicas on each of the servers. Tables that do not qualify as good candidates for partitioning can be copied across federated servers and synchronized through the use of triggers or replication. In such case, you can base your decision on observing and analyzing current data access patterns. Another method can be used if you need to partition already existing set of tables. One way to accomplish this is to determine all foreign keys referencing rows in a local partition and store them on the same server. It is essential to determine optimal placement of data, such that related data is stored together. Implementation of partitioned data and federated servers should be preceded by careful database design. In addition, you should ensure that SQL servers, where the partitions reside, are connected using fast network links (otherwise, latency for operations involving partitioned views might be significant). The read/write type requires SQL Server 2000 Enterprise Edition or SQL Server 2000 Developer Edition (they also need to follow a number of rules defined later in the article). Partitioned views can be read-only or read/write. Such views combine all rows from all partitions and make them appear as a single table. Location code, stored in key column, would be used in this case to determine to which partition a particular row belongs.ĭistributed partitioned views are used to provide transparent access to data residing in separate partitions. For example, a table can contain data that is somehow related to a geographical location. If ranges are chosen properly, then for the majority of queries, it is sufficient to access a single partition only. ![]() Each partition takes the form of a table stored in a database residing on a separate server (A collection of servers with partitioned data is known as a federation). The goal is to load balance distribution of queries by placing each of the ranges in a separate partition residing on a separate SQL server. The ranges need to reflect data access patterns. The choice of these ranges is one of the most critical decisions when developing Distributed Partitioned Views. Each set contains rows for which a value in one of the key columns belongs to a specific range of values. This term means that all rows in a table are divided into distinct sets. This means that if your goal is to create scalable and highly available configuration, you should consider combining both solutions together.ĭistributed Partitioned Views are based on horizontal partitioning of the data. In fact, the probability of data access problems increases (compared to traditional, non-partitioned views), since all partitions within the view need to be accessible in order for the view to function. You should note, however, that Distributed Partitioned Views do not offer high availability. In this article, we will look into Distributed Partitioned Views, which are intended for environments requiring a high degree of scalability. Clusters are used primarily to provide high availability through their support for failover. In the first two articles of the series, I described concepts and implementation details of SQL Server 2000 clustering. ![]()
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