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Binare transaktionen indizesi recommendations for designing columnstore indexes. A small number of good design decisions helps you achieve the high data compression and query performance that columnstore indexes are designed to provide.

In diesem Artikel wird davon ausgegangen, dass Sie mit der Columnstore-Architektur und -Terminologie vertraut sind. This article assumes you are familiar with columnstore architecture and terminology. Before designing a columnstore index, understand as much as possible about your data requirements. For example, think through the answers to these questions: You might not need a columnstore index.

Rowstore-Indizes mit Heaps oder gruppierten Indizes zeigen binare transaktionen indizesi beste Leistung bei Abfragen, die binare transaktionen indizesi den Daten suchen, nach einem bestimmten Wert suchen oder einen kleinen Bereich von Werten abfragen.

Rowstore tables with heaps binare transaktionen indizesi clustered indexes perform best on queries that seek into the data, searching for a particular value, or for queries on a small range of values. Use rowstore indexes with transactional workloads since they tend to require mostly table seeks instead of large range table scans.

Ein Columnstore-Index ist ein gruppierter oder ein nicht gruppierter Index. A columnstore index is either clustered or nonclustered.

A clustered columnstore index can have one or more nonclustered B-tree indexes. Columnstore indexes are easy to try. If you create a table as a columnstore index, you can easily convert the table back to a rowstore table by dropping the columnstore index.

Here is a summary of the options and recommendations. The clustered columnstore index is more than an index, it is the primary table storage. Er binare transaktionen indizesi beim Data Binare transaktionen indizesi eine hohe Datenkomprimierung sowie eine deutlich bessere Abfrageleistung bei umfangreichen Fakten- und Dimensionstabellen.

It achieves high data compression and a significant improvement in query performance on large data warehousing fact and dimension tables. Clustered columnstore indexes binare transaktionen indizesi best suited for analytics queries rather than transactional queries, since analytics queries tend to perform operations on large ranges of values rather than looking up specific values.

Consider using a clustered columnstore index when: Don't use a clustered columnstore index when: For more information, see Columnstore indexes - data warehousing. Ab SQL Server Beginning with SQL Server The nonclustered B-tree index is updated as changes occur to the columnstore index. This is a powerful feature that you can use to your advantage. By using the secondary B-tree index, you can efficiently search for specific rows without scanning through all the rows.

Other options become available too. Consider using a B-tree index on a columnstore index to: This makes it possible to run the analytics in real-time on a transactional table. While transactions are occurring on the underlying table, you can run analytics on the columnstore index. Since one table manages both indexes, changes are available in real-time to binare transaktionen indizesi the rowstore and the columnstore indexes.

Since a columnstore index achieves 10x better data compression than a rowstore index, it only needs a small binare transaktionen indizesi of extra storage. For example, if the compressed rowstore table takes 20 GB, the columnstore index might require an additional 2 GB. The additional space required also depends on the number of columns in the nonclustered columnstore index. Consider using a nonclustered columnstore index to: You can replace existing B-tree indexes that are designed for analytics with a nonclustered columnstore index.

Ein binare transaktionen indizesi Data Warehouse ist nicht erforderlich. Eliminate the need for a separate data warehouse. Traditionally, companies run transactions on a rowstore table and then load the data into a separate data warehouse to run analytics. For many workloads, you can eliminate the loading process and the separate data warehouse by creating a nonclustered columnstore index on transactional tables. SQL Server It's very easy to try it since you can enable a nonclustered columnstore index with no changes to your OLTP binare transaktionen indizesi.

To binare transaktionen indizesi additional processing resources, you can run the analytics on a readable secondary. Using a readable secondary separates the processing of the transactional workload and the analytics workload. For more information, see Get started with columnstore indexes for real-time operational analytics. Weitere Informationen zur Auswahl des am besten geeigneten Columnstore-Indexes finden Sie im Blog Which columnstore index is right for my workload?

For more information on choosing the best columnstore index, see Sunil Agarwal's blog Which columnstore index is right for my workload? Columnstore indexes support partitioning which is a good way to manage and archive data. Partitioning also improves query performance by limiting operations to one or more partitions. Binare transaktionen indizesi umfangreichen Tabelle lassen sich Datenbereiche praktisch nur mithilfe von Partitionen verwalten.

For large tables, the binare transaktionen indizesi practical way to manage ranges of data is by using partitions. The advantages of partitions for rowstore tables also apply to columnstore indexes. For example, both rowstore and columnstore tables use partitions to: Additionally, with a columnstore index, you use partitioning to: By using partitions, you can limit your queries to scan only specific partitions which limits the number of rows to scan.

For example, if the index is partitioned by year and the query is analyzing data from last year, it only needs to scan the data in one partition. Unless you have a large enough data size, a columnstore index performs best with fewer partitions than what you might use for a rowstore index.

Wenn die Partitionen nicht jeweils mindestens eine Million Zeilen aufweisen, gelangen die meisten Zeilen in den Deltastore. Dort profitieren sie nicht von der Leistungssteigerung der Columnstore-Komprimierung. If you don't have at least one million rows per partition, most of your rows might go to the deltastore where they don't receive the performance benefit of columnstore compression. For example, if you load one million rows into a table with 10 partitions and each partition receivesrows, all of the rows will go to delta rowgroups.

Sollte ich meinen Columnstore-Index binare transaktionen indizesi von Sunil Agarwal. For more information about partitioning, see Sunil Agarwal's blog post, Should Binare transaktionen indizesi partition my columnstore index? The columnstore index offers two choices for data compression: Columnstore compression typically achieves 10x better compression rates over rowstore indexes. It is the standard compression method for columnstore indexes and enables fast query performance.

Archive compression is designed for maximum compression when query performance is not as important. It achieves higher data compression rates than columnstore compression, but it comes with a price. It takes longer to compress binare transaktionen indizesi decompress the data, so it is not well-suited for fast query performance. Im Folgenden werden einige Optimierungen beschrieben, mit deren Hilfe sich die Abfrageleistung nach der Konvertierung der Tabelle verbessert.

There are a couple optimizations that will improve query performance after the binare transaktionen indizesi is converted, described next. You can configure the maximum number of processors for converting a heap or clustered B-tree index to a columnstore index. Since the B-tree index already stores rows in a sorted order, preserving that order when the rows get compressed binare transaktionen indizesi the columnstore index can improve query performance.

Im Columnstore-Index werden die Daten nicht sortiert. The columnstore index does not sort the data, but it does use metadata to track the minimum and maximum binare transaktionen indizesi of each column segment in each rowgroup.

When scanning for a range of values, it can quickly compute when to skip the rowgroup. When the data is ordered, more rowgroups can be skipped. To preserve the sorted order during conversion: Dadurch wird auch der Name des Indexes beibehalten. This also preserves the name of the index. Binare transaktionen indizesi you have scripts that already use the name of the rowstore index you won't need to update them. This example converts a clustered rowstore index on a table named MyFactTable to a clustered columnstore index.

These are binare transaktionen indizesi for creating and maintaining binare transaktionen indizesi indexes. Binare transaktionen indizesi create an empty columnstore index for: Voraussetzungen Prerequisites In diesem Artikel wird davon ausgegangen, dass Sie mit der Columnstore-Architektur und -Terminologie vertraut binare transaktionen indizesi.

How large is my table? Do my queries mostly perform analytics that scan large ranges of values? Columnstore indexes are designed to work well for large range scans rather than looking up specific values. Does my workload perform lots of updates and deletes? Binare transaktionen indizesi indexes work well when the data is stable.

Do I have fact and dimension tables for a data warehouse? Do I need to perform analytics on a transactional workload? If this is the case, see the columnstore design guidance for real-time operational analytics.

Durchschnittlich zehnfach Average of 10x Nicht gruppierte B-Strukturindizes in einem gruppierten Columnstore-Index Nonclustered B-tree indexes on a clustered columnstore index Verwendungszweck: Enforce primary key and foreign key constraints on a clustered columnstore index.

Beschleunigen von Binare transaktionen indizesi, die nach bestimmten Werten oder kleinen Wertebereichen suchen 2. Speed up queries that search for specific values or small ranges of values.

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