Arenadata QuickMarts
Arenadata QuickMarts (ADQM) is a cluster column-oriented DBMS built on ClickHouse. ADQM generates various online analytical reports based on vast amounts of information stored in flat marts. ADQM is much faster than traditional DBMS.
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Sharding is a database design principle that suggests locating parts of the same table on different shards. A shard is a cluster node that can consist of one or more replicas. Replicas are servers that duplicate data within a shard. SELECT and INSERT queries can be sent to any replica of a shard, there is no dedicated master.
This article describes how to resolve an issue with an unsupported encryption type that may occur when you install ADQM on a RED OS host and try to kerberize a cluster using Active Directory.
This article describes the parameters that can be configured for ADQM services via ADCM.
The easiest way to work with ADQM/ClickHouse tables is to use the clickhouse-client console client, which becomes available on each cluster host after ADQM installation. This client allows you to enter queries, pass them to ClickHouse, and view the results.
Indexing is a technique to improve database performance. Indexes are special data structures that allow a database server to quickly find requested rows by values of a key column (or column set) without a full table scan.
Learn about the minimum hardware requirements for servers of an ADQM cluster.
A window function performs a calculation across a set of rows: all rows in a query are divided into groups (windows), and each group has its own aggregates. It does not return a single output row as an aggregate function. A window function adds an aggregated value to each row of the selection result in a separate column.
To connect to ADQM, you can use clickhouse-client — a standard ClickHouse command-line client that allows you to run SQL queries and view their results in your terminal application. Once ADQM is installed, clickhouse-client is available on each server of the ADQM cluster.
The JOIN clause combines columns from two tables into a new table. A set of data rows in a resulting table depends on the JOIN type and the specified join conditions.
An aggregate function computes a single result from a set of input values. For example, you can calculate the sum, average, maximum, or minimum over a set of rows.