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.
For effective administration of ADQM databases, it is recommended to use ADQM Control — a related product that provides extensive functionality for monitoring and analyzing the state of DBMS at the level of tables, columns, user queries, and cluster hosts.
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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.
Learn about the minimum hardware requirements for servers of an ADQM cluster.
This article provides examples that demonstrate how to perform the basic operations with ADQM/ClickHouse tables using the clickhouse-client console client.
This article discusses a typical ADQM cluster — three shards, each one consists of two replicas (in other words, a distributed cluster of 3 nodes with a replication factor of 2).
This article describes the parameters that can be configured for ADQM services via ADCM.
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 software requirements for servers of an 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.
A geo-distributed cluster is a cluster whose nodes are located in several geographically distant data centers. This solution ensures high reliability of the system, which will remain operational even if one of the data centers fails.
ADQM writes general and error text logs that can be useful for analyzing the causes of different errors. Additionally, you can enable logs of other types (for example, collect information about query execution, dependent views, threads, stack traces) that will be saved to special system tables in ADQM.