GaussDB(DWS) Developer Terms
Term |
Description |
---|---|
A – E |
|
ACID |
Atomicity, Consistency, Isolation, and Durability (ACID). These are a set of properties of database transactions in a DBMS. |
cluster ring |
A cluster ring consists of several physical servers. The primary-standby-secondary relationships among its DNs do not involve external DNs. That is, none of the primary, standby, or secondary counterparts of DNs belonging to the ring are deployed in other rings. A ring is the smallest unit used for scaling. |
Bgwriter |
A background write thread created when the database starts. The thread pushes dirty pages in the database to a permanent device (such as a disk). |
bit |
The smallest unit of information handled by a computer. One bit is expressed as a 1 or a 0 in a binary numeral, or as a true or a false logical condition. A bit is physically represented by an element such as high or low voltage at one point in a circuit, or a small spot on a disk that is magnetized in one way or the other. A single bit conveys little information a human would consider meaningful. A group of eight bits, however, makes up a byte, which can be used to represent many types of information, such as a letter of the alphabet, a decimal digit, or other character. |
Bloom filter |
Bloom filter is a space-efficient binary vectorized data structure, conceived by Burton Howard Bloom in 1970, that is used to test whether an element is a member of a set. False positive matches are possible, but false negatives are not, in other words, a query returns either "possibly in set (possible error)" or "definitely not in set". In the cases, Bloom filter sacrificed the accuracy for time and space. |
CCN |
The Central Coordinator (CCN) is a node responsible for determining, queuing, and scheduling complex operations in each CN to enable the dynamic load management of GaussDB(DWS). |
CIDR |
Classless Inter-Domain Routing (CIDR). CIDR abandons the traditional class-based (class A: 8; class B: 16; and class C: 24) address allocation mode and allows the use of address prefixes of any length, effectively improving the utilization of address space. A CIDR address is in the format of IP address/Number of bits in a network ID. For example, in 192.168.23.35/21, 21 indicates that the first 21 bits are the network prefix and others are the host ID. |
Cgroups |
A control group (Cgroup), also called a priority group (PG) in GaussDB(DWS). The Cgroup is a kernel feature of SUSE Linux and Red Hat that can limit, account for, and isolate the resource usage of a collection of processes. |
CLI |
Command-line interface (CLI). Users use the CLI to interact with applications. Its input and output are based on texts. Commands are entered through keyboards or similar devices and are compiled and executed by applications. The results are displayed in text or graphic forms on the terminal interface. |
CM |
Cluster Manager (CM) manages and monitors the running status of functional units and physical resources in the distributed system, ensuring stable running of the entire system. |
CMS |
The Cluster Management Service (CMS) component manages the cluster status. |
CN |
The Coordinator (CN) stores database metadata, splits query tasks and supports their execution, and aggregates the query results returned from DNs. |
CU |
Compression Unit (CU) is the smallest storage unit in a column-storage table. |
core file |
A file that is created when memory overwriting, assertion failures, or access to invalid memory occurs in a process, causing it to fail. This file is then used for further analysis. A core file contains a memory dump, in an all-binary and port-specific format. The name of a core file consists of the word "core" and the OS process ID. The core file is available regardless of the type of platform. |
core dump |
When a program stops abnormally, the core dump, memory dump, or system dump records the state of the working memory of the program at that point in time. In practice, other key pieces of program state are usually dumped at the same time, including the processor registers, which may include the program counter and stack pointer, memory management information, and other processor and OS flags and information. A core dump is often used to assist diagnosis and computer program debugging. |
DBA |
A database administrator (DBA) instructs or executes database maintenance operations. |
DBLINK |
An object defining the path from one database to another. A remote database object can be queried with DBLINK. |
DBMS |
Database Management System (DBMS) is a piece of system management software that allows users to access information in a database. This is a collection of programs that allows you to access, manage, and query data in a database. A DBMS can be classified as memory DBMS or disk DBMS based on the location of the data. |
DCL |
Data control language (DCL) |
DDL |
Data definition language (DDL) |
DML |
Data manipulation language (DML) |
DN |
Datanode performs table data storage and query operations. |
ETCD |
The Editable Text Configuration Daemon (ETCD) is a distributed key-value storage system used for configuration sharing and service discovery (registration and search). |
ETL |
Extract-Transform-Load (ETL) refers to the process of data transmission from the source to the target database. |
Extension Connector |
Extension Connector is provided by GaussDB(DWS) to process data across clusters. It can send SQL statements to Spark, and can return execution results to your database. |
Backup |
A backup, or the process of backing up, refers to the copying and archiving of computer data in case of data loss. |
backup and restoration |
A collection of concepts, procedures, and strategies to protect data loss caused by invalid media or misoperations. |
standby server |
A node in the GaussDB(DWS) HA solution. It functions as a backup of the primary server. If the primary server is behaving abnormally, the standby server is promoted to primary, ensuring data service continuity. |
crash |
A crash (or system crash) is an event in which a computer or a program (such as a software application or an OS) ceases to function properly. Often the program will exit after encountering this type of error. Sometimes the offending program may appear to freeze or hang until a crash reporting service documents details of the crash. If the program is a critical part of the OS kernel, the entire computer may crash (possibly resulting in a fatal system error). |
encoding |
Encoding is representing data and information using code so that it can be processed and analyzed by a computer. Characters, digits, and other objects can be converted into digital code, or information and data can be converted into the required electrical pulse signals based on predefined rules. |
encoding technology |
A technology that presents data using a specific set of characters, which can be identified by computer hardware and software. |
table |
A set of columns and rows. Each column is referred to as a field. The value in each field represents a data type. For example, if a table contains people's names, cities, and states, it has three columns: Name, City, and State. In every row in the table, the Name column contains a name, the City column contains a city, and the State column contains a state. |
tablespace |
A tablespace is a logical storage structure that contains tables, indexes, large objects, and long data. A tablespace provides an abstract layer between physical data and logical data, and provides storage space for all database objects. When you create a table, you can specify which tablespace it belongs to. |
concurrency control |
A DBMS service that ensures data integrity when multiple transactions are concurrently executed in a multi-user environment. In a multi-threaded environment, GaussDB(DWS) concurrency control ensures that database operations are safe and all database transactions remain consistent at any given time. |
query |
Specifies requests sent to the database, such as updating, modifying, querying, or deleting information. |
query operator |
An iterator or a query tree node, which is a basic unit for the execution of a query. Execution of a query can be split into one or more query operators. Common query operators include scan, join, and aggregation. |
query fragment |
Each query task can be split into one or more query fragments. Each query fragment consists of one or more query operators and can independently run on a node. Query fragments exchange data through data flow operators. |
durability |
One of the ACID features of database transactions. Durability indicates that transactions that have been committed will permanently survive and not be rolled back. |
stored procedure |
A group of SQL statements compiled into a single execution plan and stored in a large database system. Users can specify a name and parameters (if any) for a stored procedure to execute the procedure. |
OS |
An operating system (OS) is loaded by a bootstrap program to a computer to manage other programs in the computer. Other programs are applications or application programs. |
secondary server |
To ensure high cluster availability, the primary server synchronizes logs to the secondary server if data synchronization between the primary and standby servers fails. If the primary server suddenly breaks down, the standby server is promoted to primary and synchronizes logs from the secondary server for the duration of the breakdown. |
BLOB |
Binary large object (BLOB) is a collection of binary data stored in a database, such as videos, audio, and images. |
dynamic load balancing |
In GaussDB(DWS), dynamic load balancing automatically adjusts the number of concurrent jobs based on the usage of CPU, I/O, and memory to avoid service errors and to prevent the system from stop responding due to system overload. |
segment |
A segment in the database indicates a part containing one or more regions. Region is the smallest range of a database and consists of data blocks. One or more segments comprise a tablespace. |
F – J |
|
failover |
Automatic switchover from a faulty node to its standby node. Reversely, automatic switchback from the standby node to the primary node is called failback. |
FDW |
A foreign data wrapper (FDW) is a SQL interface provided by Postgres. It is used to access big data objects stored in remote data so that DBAs can integrate data from unrelated data sources and store them in public schema in the database. |
freeze |
An operation automatically performed by the AutoVacuum Worker process when transaction IDs are exhausted. GaussDB(DWS) records transaction IDs in row headings. When a transaction reads a row, the transaction ID in the row heading and the actual transaction ID are compared to determine whether this row is explicit. Transaction IDs are integers containing no symbols. If exhausted, transaction IDs are re-calculated outside of the integer range, causing the explicit rows to become implicit. To prevent such a problem, the freeze operation marks a transaction ID as a special ID. Rows marked with these special transaction IDs are explicit to all transactions. |
GDB |
As a GNU debugger, GDB allows you to see what is going on 'inside' another program while it executes or what another program was doing the moment that it crashed. GDB can perform four main kinds of things (make PDK functions stronger) to help you catch bugs in the act:
|
GDS |
General Data Service (GDS). To import data to GaussDB(DWS), you need to deploy the tool on the server where the source data is stored so that DNs can use this tool to obtain data. |
GIN index |
Generalized inverted index (GIN) is used for handling cases where the items to be indexed are composite values, and the queries to be handled by the index need to search for element values that appear within the composite items. |
GNU |
The GNU Project was publicly announced on September 27, 1983 by Richard Stallman, aiming at building an OS composed wholly of free software. GNU is a recursive acronym for "GNU's Not Unix!". Stallman announced that GNU should be pronounced as Guh-NOO. Technically, GNU is similar to Unix in design, a widely used commercial OS. However, GNU is free software and contains no Unix code. |
gsql |
GaussDB(DWS) interaction terminal. It enables you to interactively type in queries, issue them to GaussDB(DWS), and view the query results. Queries can also be entered from files. gsql supports many meta commands and shell-like commands, allowing you to conveniently compile scripts and automate tasks. |
GTM |
Global Transaction Manager (GTM) manages the status of transactions. |
GUC |
Grand unified configuration (GUC) includes parameters for running databases, the values of which determine database system behavior. |
HA |
High availability (HA) is a solution in which two modules operate in primary/standby mode to achieve high availability. This solution helps to minimize the duration of service interruptions caused by routine maintenance (planned) or sudden system breakdowns (unplanned), improving the system and application usability. |
HBA |
Host-based authentication (HBA) allows hosts to authenticate on behalf of all or some of the system users. It can apply to all users on a system or a subset using the Match directive. This type of authentication can be useful for managing computing clusters and other fairly homogenous pools of machines. In all, three files on the server and one on the client must be modified to prepare for host-based authentication. |
HDFS |
Hadoop Distributed File System (HDFS) is a subproject of Apache Hadoop. HDFS is highly fault tolerant and is designed to run on low-end hardware. The HDFS provides high-throughput access to large data sets and is ideal for applications having large data sets. |
server |
A combination of hardware and software designed for providing clients with services. This word alone refers to the computer running the server OS, or the software or dedicated hardware providing services. |
advanced package |
Logical and functional stored procedures and functions provided by GaussDB(DWS). |
isolation |
One of the ACID features of database transactions. Isolation means that the operations inside a transaction and data used are isolated from other concurrent transactions. The concurrent transactions do not affect each other. |
relational database |
A database created using a relational model. It processes data using methods of set algebra. |
archive thread |
A thread started when the archive function is enabled on a database. The thread archives database logs to a specified path. |
failover |
The automatic substitution of a functionally equivalent system component for a failed one. The system component can be a processor, server, network, or database. |
environment variable |
An environment variable defines the part of the environment in which a process runs. For example, it can define the part of the environment as the main directory, command search path, terminal that is in use, or the current time zone. |
checkpoint |
A mechanism that stores data in the database memory to disks at a certain time. GaussDB(DWS) periodically stores the data of committed and uncommitted transactions to disks. The data and redo logs can be used for database restoration if a database restarts or breaks down. |
encryption |
A function hiding information content during data transmission to prevent the unauthorized use of the information. |
node |
Cluster nodes (or nodes) are physical and virtual severs that make up the GaussDB(DWS) cluster environment. |
error correction |
A technique that automatically detects and corrects errors in software and data streams to improve system stability and reliability. |
process |
An instance of a computer program that is being executed. A process may be made up of multiple threads of execution. Other processes cannot use a thread occupied by the process. |
PITR |
Point-In-Time Recovery (PITR) is a backup and restoration feature of GaussDB(DWS). Data can be restored to a specified point in time if backup data and WAL logs are normal. |
record |
In a relational database, a record corresponds to data in each row of a table. |
cluster |
A cluster is an independent system consisting of servers and other resources, ensuring high availability. In certain conditions, clusters can implement load balancing and concurrent processing of transactions. |
K – O |
|
LLVM |
LLVM is short for Low Level Virtual Machine. Low Level Virtual Machine (LLVM) is a compiler framework written in C++ and is designed to optimize the compile-time, link-time, run-time, and idle-time of programs that are written in arbitrary programming languages. It is open to developers and compatible with existing scripts. GaussDB(DWS) LLVM dynamic compilation can be used to generate customized machine code for each query to replace original common functions. Query performance is improved by reducing redundant judgment conditions and virtual function invocation, and by making local data more accurate during actual queries. |
LVS |
Linux Virtual Server (LVS), a virtual server cluster system, is used for balancing the load of a cluster. |
logical replication |
Data synchronization mode between primary and standby databases or between two clusters. Different from physical replication which replays physical logs, logical replication transfers logical logs between two clusters or synchronizes data through SQL statements in logical logs. |
logical log |
Logs recording database changes made through SQL statements. Generally, the changes are logged at the row level. Logical logs are different from physical logs that record changes of physical pages. |
logical decoding |
Logic decoding is a process of extracting all permanent changes in database tables into a clear and easy-to-understand format by decoding Xlogs. |
logical replication slot |
In a logical replication process, logic replication slots are used to prevent Xlogs from being reclaimed by the system or VACUUM. In GaussDB(DWS), a logical replication slot is an object that records logical decoding positions. It can be created, deleted, read, and pushed by invoking SQL functions. |
MPP |
Massive Parallel Processing (MPP) refers to cluster architecture that consists of multiple machines. The architecture is also called a cluster system. |
MVCC |
Multi-Version Concurrency Control (MVCC) is a protocol that allows a tuple to have multiple versions, on which different query operations can be performed. A basic advantage is that read and write operations do not conflict. |
NameNode |
The NameNode is the centerpiece of a Hadoop file system, managing the namespace of the file system and client access to files. |
Node Group |
In GaussDB(DWS), a Node Group refers to a DN set, which is a sub-cluster. Node Groups can be classified into Storage Node Groups, which store local table data; and Computing Node Groups, which perform aggregation and join for queries. |
OLAP |
Online analytical processing (OLAP) is the most important application in the database warehouse system. It is dedicated to complex analytical operations, helps decision makers and executives to make decisions, and rapidly and flexibly processes complex queries involving a great amount of data based on analysts' requirements. In addition, the OLAP provides decision makers with query results that are easy to understand, allowing them to learn the operating status of the enterprise. These decision makers can then produce informed and accurate solutions based on the query results. |
OM |
Operations Management (OM) provides management interfaces and tools for routine maintenance and configuration management of the cluster. |
ORC |
Optimized Row Columnar (ORC) is a widely used file format for structured data in a Hadoop system. It was introduced from the Hadoop HIVE project. |
client |
A computer or program that accesses or requests services from another computer or program. |
free space management |
A mechanism for managing free space in a table. This mechanism enables the database system to record free space in each table and establish an easy-to-search data structure, accelerating operations (such as INSERT) performed on the free space. |
cross-cluster |
In GaussDB(DWS), users can access data in other DBMS through foreign tables or using an Extension Connector. Such access is cross-cluster. |
junk tuple |
A tuple that is deleted using the DELETE and UPDATE statements. When deleting a tuple, GaussDB(DWS) only marks the tuples that are to be cleared. The Vacuum thread will then periodically clear these junk tuples. |
column |
An equivalent concept of "field". A database table consists of one or more columns. Together they describe all attributes of a record in the table. |
logical node |
Multiple logical nodes can be installed on the same node. A logical node is a database instance. |
schema |
Collection of database objects, including logical structures, such as tables, views, sequences, stored procedures, synonyms, indexes, clusters, and database links. |
schema file |
A SQL file that determines the database structure. |
P – T |
|
Page |
Minimum memory unit for row storage in the GaussDB(DWS) relational object structure. The default size of a page is 8 KB. |
PostgreSQL |
An open-source DBMS developed by volunteers all over the world. PostgreSQL is not controlled by any companies or individuals. Its source code can be used for free. |
Postgres-XC |
Postgres-XC is an open source PostgreSQL cluster to provide write-scalable, synchronous, multi-master PostgreSQL cluster solution. |
Postmaster |
A thread started when the database service is started. It listens to connection requests from other nodes in the cluster or from clients. After receiving and accepting a connection request from the standby server, the primary server creates a WAL Sender thread to interact with the standby server. |
RHEL |
Red Hat Enterprise Linux (RHEL) |
redo log |
A log that contains information required for performing an operation again in a database. If a database is faulty, redo logs can be used to restore the database to its original state. |
SCTP |
The Stream Control Transmission Protocol (SCTP) is a transport-layer protocol defined by Internet Engineering Task Force (IETF) in 2000. The protocol ensures the reliability of datagram transport based on unreliable service transmission protocols by transferring SCN narrowband signaling over IP network. |
savepoint |
A savepoint marks the end of a sub-transaction (also known as a nested transaction) in a relational DBMS. The process of a long transaction can be divided into several parts. After a part is successfully executed, a savepoint will be created. If later execution fails, the transaction will be rolled back to the savepoint instead of being totally rolled back. This is helpful for recovering database applications from complicated errors. If an error occurs in a multi-statement transaction, the application can possibly recover by rolling back to the save point without terminating the entire transaction. |
session |
A task created by a database for a connection when an application attempts to connect to the database. Sessions are managed by the session manager. They execute initial tasks to perform all user operations. |
shared-nothing architecture |
A distributed computing architecture, in which none of the nodes share CPUs or storage resources. This architecture has good scalability. |
SLES |
SUSE Linux Enterprise Server (SLES) is an enterprise Linux OS provided by SUSE. |
SMP |
Symmetric multiprocessing (SMP) lets multiple CPUs run on a computer and share the same memory and bus. To ensure an SMP system achieves high performance, an OS must support multi-tasking and multi-thread processing. In databases, SMP means to concurrently execute queries using the multi-thread technology, efficiently using all CPU resources and improving query performance. |
SQL |
Structure Query Language (SQL) is a standard database query language. It consists of DDL, DML, and DCL. |
SSL |
Secure Socket Layer (SSL) is a network security protocol introduced by Netscape. SSL is a security protocol based on the TCP and IP communications protocols and uses the public key technology. SSL supports a wide range of networks and provides three basic security services, all of which use the public key technology. SSL ensures the security of service communication through the network by establishing a secure connection between the client and server and then sending data through this connection. |
convergence ratio |
Downlink to uplink bandwidth ratio of a switch. A high convergence ratio indicates a highly converged traffic environment and severe packet loss. |
TCP |
Transmission Control Protocol (TCP) sends and receives data through the IP protocol. It splits data into packets for sending, and checks and reassembles received package to obtain original information. TCP is a connection-oriented, reliable protocol that ensures information correctness in transmission. |
trace |
A way of logging to record information about the way a program is executed. This information is typically used by programmers for debugging purposes. System administrators and technical support can diagnose common problems by using software monitoring tools and based on this information. |
full backup |
Backup of the entire database cluster. |
full synchronization |
A data synchronization mechanism specified in the GaussDB(DWS) HA solution. Used to synchronize all data from the primary server to a standby server. |
Log File |
A file to which a computer system writes a record of its activities. |
transaction |
A logical unit of work performed within a DBMS against a database. A transaction consists of a limited database operation sequence, and must have ACID features. |
data |
A representation of facts or directives for manual or automatic communication, explanation, or processing. Data includes constants, variables, arrays, and strings. |
data redistribution |
A process whereby a data table is redistributed among nodes after users change the data distribution mode. |
data distribution |
A mode in which table data is split and stored on each database instance in a distributed system. Table data can be distributed in hash, replication, or random mode. In hash mode, a hash value is calculated based on the value of a specified column in a tuple, and then the target storage location of the tuple is determined based on the mapping between nodes and hash values. In replication mode, tuples are replicated to all nodes. In random mode, data is randomly distributed to the nodes. |
data partitioning |
A division of a logical database or its constituent elements into multiple parts (partitions) whose data does not overlap based on specified ranges. Data is mapped to storage locations based on the value ranges of specific columns in a tuple. |
Database Name |
A collection of data that is stored together and can be accessed, managed, and updated. Data in a view in the database can be classified into the following types: numerals, full text, digits, and images. |
DB instance |
A database instance consists of a process in GaussDB(DWS) and files controlled by the process. GaussDB(DWS) installs multiple database instances on one physical node. GTM, CM, CN, and DN installed on cluster nodes are all database instances. A database instance is also called a logical node. |
database HA |
GaussDB(DWS) provides a highly reliable HA solution. Every logical node in GaussDB(DWS) is identified as a primary or standby node. Only one GaussDB(DWS) node is identified as primary at a time. When the HA system is deployed for the first time, the primary server synchronizes all data from each standby server (full synchronization). The HA system then synchronizes only data that is new or has been modified from each standby server (incremental synchronization). When the HA system is running, the primary server can receive data read and write operation requests and the standby servers only synchronize logs. |
database file |
A binary file that stores user data and the data inside the database system. |
data flow operator |
An operator that exchanges data among query fragments. By their input/output relationships, data flows can be categorized into Gather flows, Broadcast flows, and Redistribution flows. Gather combines multiple query fragments of data into one. Broadcast forwards the data of one query fragment to multiple query fragments. Redistribution reorganizes the data of multiple query fragments and then redistributes the reorganized data to multiple query fragments. |
data dictionary |
A reserved table within a database which is used to store information about the database itself. The information includes database design information, stored procedure information, user rights, user statistics, database process information, database increase statistics, and database performance statistics. |
deadlock |
Unresolved contention for the use of resources. |
index |
An ordered data structure in the database management system. An index accelerates querying and the updating of data in database tables. |
statistics |
Information that is automatically collected by databases, including table-level information (number of tuples and number of pages) and column-level information (column value range distribution histogram). Statistics in databases are used to estimate the cost of execution plans to find the plan with the lowest cost. |
stop word |
In computing, stop words are words which are filtered out before or after processing of natural language data (text), saving storage space and improving search efficiency. |
U – Z |
|
vacuum |
A thread that is periodically started up by a database to clear junk tuples. Multiple Vacuum threads can be started concurrently by setting a parameter. |
verbose |
The VERBOSE option specifies the information to be displayed. |
WAL |
Write-ahead logging (WAL) is a standard method for logging a transaction. Corresponding logs must be written into a permanent device before a data file (carrier for a table and index) is modified. |
WAL Receiver |
A thread created by the standby server during database duplication. The thread is used to receive data and commands from the primary server and to tell the primary server that the data and commands have been acknowledged. Only one WAL receiver thread can run on one standby server. |
WAL Sender |
A thread created on the primary server when the primary server has received a connection request from a standby server during database replication. This thread is used to send data and commands to standby servers and to receive responses from the standby servers. Multiple WAL Sender threads may run on one primary server. Each WAL Sender thread corresponds to a connection request initiated by a standby server. |
WAL Writer |
A thread for writing redo logs that are created when a database is started. This thread is used to write logs in the memory to a permanent device, such as a disk. |
WLM |
The WorkLoad Manager (WLM) is a module for controlling and allocating system resources in GaussDB(DWS). |
Xlog |
A transaction log. A logical node can have only one Xlog file. |
xDR |
X detailed record. It refers to detailed records on the user and signaling plans and can be categorized into charging data records (CDRs), user flow data records (UFDRs), transaction detail records (TDRs), and data records (SDRs). |
network backup |
Network backup provides a comprehensive and flexible data protection solution to MS Windows, UNIX, and Linux platforms. Network backup can back up, archive, and restore files, folders, directories, volumes, and partitions on a computer. |
physical node |
A physical machine or device. |
system catalog |
A table storing meta information about the database. The meta information includes user tables, indexes, columns, functions, and the data types in a database. |
pushdown |
GaussDB(DWS) is a distributed database, where CN can send a query plan to multiple DNs for parallel execution. This CN behavior is called pushdown. It achieves better query performance than extracting data to CN for query. |
compression |
Data compression, source coding, or bit-rate reduction involves encoding information that uses fewer bits than the original representation. Compression can be either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by identifying and removing unnecessary or unimportant information. The process of reducing the size of a data file is commonly referred as data compression, although its formal name is source coding (coding done at the source of the data, before it is stored or transmitted). |
consistency |
One of the ACID features of database transactions. Consistency is a database status. In such a status, data in the database must comply with integrity constraints. |
metadata |
Data that provides information about other data. Metadata describes the source, size, format, or other characteristics of data. In database columns, metadata explains the content of a data warehouse. |
atomicity |
One of the ACID features of database transactions. Atomicity means that a transaction is composed of an indivisible unit of work. All operations performed in a transaction must either be committed or uncommitted. If an error occurs during transaction execution, the transaction is rolled back to the state when it was not committed. |
online scale-out |
Online scale-out means that data can be saved to the database and query services are not interrupted during redistribution in GaussDB(DWS). |
dirty page |
A page that has been modified and is not written to a permanent device. |
incremental backup |
Incremental backup stores all files changed since the last valid backup. |
incremental synchronization |
A data synchronization mechanism in the GaussDB(DWS) HA solution. Only data modified since the last synchronization is synchronized to the standby server. |
Host |
A node that receives data read and write operations in the GaussDB(DWS) HA system and works with all standby servers. At any time, only one node in the HA system is identified as the primary server. |
thesaurus |
Standardized words or phrases that express document themes and are used for indexing and retrieval. |
dump file |
A specific type of the trace file. A dump is typically a one-time output of diagnostic data in response to an event, whereas a trace tends to be continuous output of diagnostic data. |
resource pool |
Resource pools used for allocating resources in GaussDB(DWS). By binding a user to a resource pool, you can limit the priority of the jobs executed by the user and resources available to the jobs. |
tenant |
A database service user who runs services using allocated computing (CPU, memory, and I/O) and storage resources. Service level agreements (SLAs) are met through resource management and isolation. |
minimum restoration point |
A method used by GaussDB(DWS) to ensure data consistency. During startup, GaussDB(DWS) checks consistency between the latest WAL logs and the minimum restoration point. If the record location of the minimum restoration point is greater than that of the latest WAL logs, the database fails to start. |
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