Introduction to Greenplum Database
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Introduction to Greenplum Database
Greenplum Database is a massively parallel processing (MPP) database server based on PostgreSQL open-source technology. MPP (also known as a shared nothing architecture) refers to systems with two or more processors that cooperate to carry out an operation - each processor with its own memory, operating system and disks. Greenplum uses this high-performance system architecture to distribute the load of multi-terabyte data warehouses, and can use all of a system’s resources in parallel to process a query.
Greenplum Database is essentially several PostgreSQL database instances acting together as one cohesive database management system (DBMS). It is based on PostgreSQL 8.2.15, and in most cases is very similar to PostgreSQL with regard to SQL support, features, configuration options, and end-user functionality. Database users interact with Greenplum Database as they would a regular PostgreSQL DBMS.
The internals of PostgreSQL have been modified or supplemented to support the parallel structure of Greenplum Database. For example, the system catalog, query planner, optimizer, query executor, and transaction manager components have been modified and enhanced to be able to execute queries simultaneously across all of the parallel PostgreSQL database instances. The Greenplum interconnect (the networking layer) enables communication between the distinct PostgreSQL instances and allows the system to behave as one logical database.
Greenplum Database also includes features designed to optimize PostgreSQL for business intelligence (BI) workloads. For example, Greenplum has added parallel data loading (external tables), resource management, query optimizations, and storage enhancements, which are not found in standard PostgreSQL. Many features and optimizations developed by Greenplum make their way into the PostgreSQL community. For example, table partitioning is a feature first developed by Greenplum, and it is now in standard PostgreSQL.
The following topics introduce the Greenplum architecture, components, high availability and parallel data loading features, and management utilities.
About the Greenplum Architecture
Greenplum Database stores and processes large amounts of data by distributing the data and processing workload across several servers or hosts. Greenplum Database is an array of individual databases based upon PostgreSQL 8.2 working together to present a single database image. The master is the entry point to the Greenplum Database system. It is the database instance to which clients connect and submit SQL statements. The master coordinates its work with the other database instances in the system, called segments, which store and process the data.
The following topics describes the components that make up a Greenplum Database system and how they work together:
About the Greenplum Master
The master is the entry point to the Greenplum Database system. It is the database process that accepts client connections and processes SQL commands that system users issue.
Greenplum Database end-users interact with Greenplum Database (through the master) as they would with a typical PostgreSQL database. They connect to the database using client programs such as psql or application programming interfaces (APIs) such as JDBC or ODBC.
The master is where the global system catalog resides. The global system catalog is the set of system tables that contain metadata about the Greenplum Database system itself. The master does not contain any user data; data resides only on the segments. The master authenticates client connections, processes incoming SQL commands, distributes workload among segments, coordinates the results returned by each segment, and presents the final results to the client program.
About the Greenplum Segments
In Greenplum Database, the segments are where data is stored and the majority of query processing takes place. When a user connects to the database and issues a query, processes are created on each segment to handle the work of that query. For more information about query processes, see About Greenplum Query Processing.
User-defined tables and their indexes are distributed across the available segments in a Greenplum Database system; each segment contains a distinct portion of data. The database server processes that serve segment data run under the corresponding segment instances. Users interact with segments in a Greenplum Database system through the master.
In the recommended Greenplum Database hardware configuration, there is one active segment per effective CPU or CPU core. For example, if your segment hosts have two dual-core processors, you would have four primary segments per host.
About the Greenplum Interconnect
The interconnect is the networking layer of Greenplum Database. The interconnect refers to the inter-process communication between segments and the network infrastructure on which this communication relies. The Greenplum interconnect uses a standard Gigabit Ethernet switching fabric.
By default, the interconnect uses User Datagram Protocol (UDP) to send messages over the network. The Greenplum software performs packet verification beyond what is provided by UDP. This means the reliability is equivalent to Transmission Control Protocol (TCP), and the performance and scalability exceeds TCP. If the interconnect used TCP, Greenplum Database would have a scalability limit of 1000 segment instances. With UDP as the current default protocol for the interconnect, this limit is not applicable.
About Redundancy and Failover in Greenplum Database
You can deploy Greenplum Database without a single point of failure. This topic explains the redundancy components of Greenplum Database.
About Segment Mirroring
When you deploy your Greenplum Database system, you can optionally configure mirror segments. Mirror segments allow database queries to fail over to a backup segment if the primary segment becomes unavailable. To configure mirroring, you must have enough hosts in your Greenplum Database system so the secondary (mirror) segment always resides on a different host than its primary segment. Figure 2 shows how table data is distributed across segments when mirroring is configured.
Segment Failover and Recovery
When mirroring is enabled in a Greenplum Database system, the system will automatically fail over to the mirror copy if a primary copy becomes unavailable. A Greenplum Database system can remain operational if a segment instance or host goes down as long as all the data is available on the remaining active segments.
If the master cannot connect to a segment instance, it marks that segment instance as down in the Greenplum Database system catalog and brings up the mirror segment in its place. A failed segment instance will remain out of operation until an administrator takes steps to bring that segment back online. An administrator can recover a failed segment while the system is up and running. The recovery process copies over only the changes that were missed while the segment was out of operation.
If you do not have mirroring enabled, the system will automatically shut down if a segment instance becomes invalid. You must recover all failed segments before operations can continue.
About Master Mirroring
You can also optionally deploy a backup or mirror of the master instance on a separate host from the master node. A backup master host serves as a warm standby in the event that the primary master host becomes unoperational. The standby master is kept up to date by a transaction log replication process, which runs on the standby master host and synchronizes the data between the primary and standby master hosts.
If the primary master fails, the log replication process stops, and the standby master can be activated in its place. Upon activation of the standby master, the replicated logs are used to reconstruct the state of the master host at the time of the last successfully committed transaction. The activated standby master effectively becomes the Greenplum Database master, accepting client connections on the master port (which must be set to the same port number on the master host and the backup master host).
Since the master does not contain any user data, only the system catalog tables need to be synchronized between the primary and backup copies. When these tables are updated, changes are automatically copied over to the standby master to ensure synchronization with the primary master.
About Interconnect Redundancy
The interconnect refers to the inter-process communication between the segments and the network infrastructure on which this communication relies. You can achieve a highly available interconnect by deploying dual Gigabit Ethernet switches on your network and redundant Gigabit connections to the Greenplum Database host (master and segment) servers.
About Parallel Data Loading
In a large scale, multi-terabyte data warehouse, large amounts of data must be loaded within a relatively small maintenance window. Greenplum supports fast, parallel data loading with its external tables feature. Administrators can also load external tables in single row error isolation mode to filter bad rows into a separate error table while continuing to load properly formatted rows. Administrators can specify an error threshold for a load operation to control how many improperly formatted rows cause Greenplum to abort the load operation.
By using external tables in conjunction with Greenplum Database’s parallel file server (gpfdist), administrators can achieve maximum parallelism and load bandwidth from their Greenplum Database system.
About Management and Monitoring
Administrators manage a Greenplum Database system using command-line utilities located in $GPHOME/bin. Greenplum provides utilities for the following administration tasks:
- Installing Greenplum Database on an Array
- Initializing a Greenplum Database System
- Starting and Stopping Greenplum Database
- Adding or Removing a Host
- Expanding the Array and Redistributing Tables among New Segments
- Managing Recovery for Failed Segment Instances
- Managing Failover and Recovery for a Failed Master Instance
- Backing Up and Restoring a Database (in Parallel)
- Loading Data in Parallel
- System State Reporting
Greenplum provides an optional system monitoring and management tool that administrators can install and enable with Greenplum Database. Greenplum Command Center uses data collection agents on each segment host to collect and store Greenplum system metrics in a dedicated database. Segment data collection agents send their data to the Greenplum master at regular intervals (typically every 15 seconds). Users can query the Command Center database to see query and system metrics. Greenplum Command Center has a graphical web-based user interface for viewing system metrics, which administrators can install separately from Greenplum Database. For more information, see the Greenplum Command Center documentation.