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greenplum db 4.0 readme
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About Greenplum Database 4.0.0.0 Controlled Release (CR) 1
May 15, 2010
Welcome to Greenplum Database 4.0 CR
Greenplum Database is a massively parallel processing (MPP) database server
designed to support the next generation of data warehousing and large-scale analytics
processing. It allows a cluster of servers to operate as a single database super
computer — automatically partitioning data and parallelizing queries — to achieve
performance tens or hundreds times faster than traditional databases. It supports SQL
and MapReduce parallel processing and data volumes that range from hundreds of
Gigabytes, to tens to hundreds of Terabytes, to multiple Petabytes.
About Greenplum Database 4.0.0.0 Controlled Release (CR)
Greenplum Database 4.0.0.0 is a controlled release (CR), meaning it is not available to
a general audience (GA). Greenplum Database 4.0 CR will be made available to
certain Greenplum-approved customers, and is to be used with the understanding that
certain features and usages are still considered beta quality. Greenplum Database 4.0
CR has some known issues, which are documented in
“Known Issues in Greenplum
Database 4.0 CR” on page 12. Greenplum recommends that these scenarios be
avoided or to use the appropriate work-around where applicable. Greenplum Database
4.0 GA will be released when all major known issues are resolved and fully tested.
About Greenplum Database 4.0
Greenplum Database 4.0 major release which introduces a number of significant new
features, performance and stability enhancements, and enhancements to the product
architecture. Please refer to the following sections for more information about this
release:
• New Features in Greenplum Database 4.0
• Changed Features in Greenplum Database 4.0
• Resolved Issues in Greenplum Database 4.0
• Known Issues in Greenplum Database 4.0 CR
• Upgrading to Greenplum Database 4.0
• Greenplum Database Documentation
New Features in Greenplum Database 4.0
Greenplum Database 4.0 offers the following new features:
• Enhanced Workload Management with Dynamic Query Prioritization
• Self Healing Fault Tolerance Model with Differential Online Recovery
• Direct Dispatch Performance Optimization of Single Row Operation
• MPP Tablespace Support for Non-Uniform and SSD Segment Storage
• B-Tree and Bitmap Indexes on Column-Oriented and Append-Only Tables
• Health Monitoring Infrastructure with Email and SNMP Alerting
New Features in Greenplum Database 4.0 2
Greenplum Database 4.0.0.0 Release Notes
• Writable External Tables for Parallel Data Output
• Object-level 'Metadata Management' Tracking and Querying
• Enhanced Global Statistics Collection
• MapReduce Support for C Language Functions
Enhanced Workload Management with Dynamic Query
Prioritization
Prior releases of Greenplum Database have included a range of workload management
capabilities to allow database administrators (DBAs) to manage the resources
allocated to query workloads. The primary mechanism has been role-based resource
queues, which provide configurable query admission limits. By using resource queues
to set limits on incoming queries, DBAs can control the number and complexity of
active queries on the system at any given time, thereby protecting the system from
over allocation of resources. Prior to 4.0, DBAs had to explicitly enable resource
queues. In 4.0, resource queues are now always enabled.
In addition to resource queues, Greenplum Database 4.0 adds a dynamic query
prioritization infrastructure. Each query in the system has a priority value, which
determines the relative share of system resources provided to it. The priority of a
query is initially determined by the priority set on the resource queue through which it
enters. However, administrators also have the ability to adjust priority at runtime. This
feature allows DBAs to control processing resources and ensure that important
workloads can run with minimal interference from lower priority jobs.
Self Healing Fault Tolerance Model with Differential Online
Recovery
In Greenplum Database 4.0, data redundancy (mirroring) is now performed using
physical block replication. The primary and mirror segments are kept in sync at the
physical disk block level, and changes to the primary are automatically applied to the
mirror in a transactionally consistent manner. This new mirroring architecture offers a
number of improvements over prior releases:
• Automatic Failure Detection and Failover. Should a segment server become
unavailable, the system will automatically detect the failure and promote the
necessary mirror segments to maintain full read/write operation. There is no
longer a need to specify a fault action mode (read-only or continue).
• Fast Differential Recovery. Greenplum Database 4.0 keeps track of the changes
that are made while a segment is down. When a failed segment becomes available
again, only the modified disk blocks (as opposed to the entire contents) are copied
over from the mirror. This ensures the fastest possible recovery time.
• No Downtime for Segment Recovery. Segment recovery takes place in the
background while the system is fully online. The database is fully available and
can support read/write operations while recovery is in progress.
Important: Resource queues are required for all roles (users) in Greenplum Database
4.0. Any role not explicitly assigned to a resource queue will be assigned to the default
resource queue,
pg_default
.
New Features in Greenplum Database 4.0 3
Greenplum Database 4.0.0.0 Release Notes
• Improved Write Performance for AO Tables. Write transactions for
compressed append-only tables are only processed once at the primary segments,
and segment mirroring ensures that all modified disk blocks are synchronized to
the mirrors.
In prior releases, Greenplum Database used logical database replication to maintain a
mirror copy of a segment instance. This meant that a statement issued to Greenplum
Database, such as an
INSERT
, was run on a primary segment first and then again on its
corresponding mirror segment. While this was an effective technique for data
redundancy, the new physical block replication infrastructure has a number of
functional and performance advantages. This new infrastructure will also be the basis
for future Greenplum Database high-availability and replication features.
Direct Dispatch Performance Optimization of Single Row Operation
Greenplum Database 4.0 introduces a performance enhancement to the query planning
and dispatch process for small queries that only access data on a single segment (for
example, a single-row
INSERT
,
UPDATE
,
DELETE
or
SELECT
statement). In queries
such as these, the query plan is not dispatched to all segments, but is targeted to the
segment that contains the affected row(s). This direct dispatch approach for this type
of query dramatically reduces the response time and resource utilization of small
queries.
MPP Tablespace Support for Non-Uniform and SSD Segment
Storage
Greenplum Database 4.0 introduces support for tablespaces. Tablespaces allow
database administrators to have multiple file systems per machine and decide how to
best use their physical storage to store database objects. Tablespaces are useful for a
number of reasons, such as allowing different storage types for frequently versus
infrequently used database objects, or controlling storage capacity and I/O
performance on certain database objects. For example, highly utilized tables can be
placed on file systems that use high performance solid-state drives (SSD), while the
remaining tables utilize standard hard drives. This is an advanced feature for
Greenplum system administrators who need greater control and flexibility over their
database storage.
B-Tree and Bitmap Indexes on Column-Oriented and Append-Only
Tables
In Greenplum Database 4.0, support for non-unique indexes has been added for
append-only storage tables, including tables using compression and/or
column-oriented storage. Indexes can greatly improve performance on compressed
append-only tables for queries that return a targeted set of rows, as the optimizer now
has the option to use an index access method rather than a full table scan when
appropriate. For compressed data, an index access method means only the necessary
rows are uncompressed.
Health Monitoring Infrastructure with Email and SNMP Alerting
Greenplum Database can now be configured to send email notifications to a system
administrator whenever certain events occur, such as fatal server errors, segment
failures, or system restarts.
New Features in Greenplum Database 4.0 4
Greenplum Database 4.0.0.0 Release Notes
Greenplum Database 4.0 also introduces support for SNMP. The Greenplum SNMP
agent,
gpsnmpd
, can be configured to run on your Greenplum master host. This agent
supports the standard relational database application management information base
(
RDBMS-MIB.txt
) and can be polled by a network monitoring program, such as HP
OpenView or Nagios. Greenplum Database can also be configured to send an SNMP
notification to your network monitoring program when certain alert events occur (such
as a segment failure). Greenplum Database supplies a custom management
information base (
GPDB-MIB.txt
) to enable SNMP notifications for certain
Greenplum Database events.
Writable External Tables for Parallel Data Output
Greenplum Database 4.0 now supports writable external tables, allowing users to
perform high-speed parallel data output from a Greenplum Database instance to a file
system, and ETL server, or other applications or databases. Writable external tables
can be used in conjunction with Greenplum MapReduce to output job results to any
external target. Writable external tables utilize the same Scatter-Gather Streaming
infrastructure that is used when loading data.
Object-level 'Metadata Management' Tracking and Querying
Greenplum Database 4.0 now tracks metadata management information in its system
catalogs about the objects stored in a database, such as tables, views, indexes and so
on, as well as global objects such as roles and tablespaces. This allows administrators
to examine information about an object, such as when it was created or what was the
last operation performed. The system views pg_stat_operations and
pg_stat_partition_operations can be used to look up actions performed on an object,
such as a table. For example, you can use these views to see when a table was last
vacuumed and analyzed.
Enhanced Global Statistics Collection
The
ANALYZE
command in Greenplum Database 4.0 now collects global database
statistics from all active segments in the system, thereby providing the most accurate
(and consistent) statistics for query planning and optimization. Previous versions of
Greenplum Database would select a single segment to use as the basis for statistical
data analysis, which did not always represent the true statistical variance of the data.
Existing customers will be able to see the benefit of improved statistics collection the
first time they run
ANALYZE
on a table after upgrading to 4.0. No other additional
configuration is necessary.
MapReduce Support for C Language Functions
Greenplum MapReduce allows programmers who are familiar with the MapReduce
programming paradigm to write map and reduce functions and submit them to the
Greenplum Database parallel data flow engine for processing. Prior releases of
Greenplum MapReduce provided language support for Perl and Python. In 4.0,
developers can also use C functions. Both user-defined C functions and built-in
database functions are supported.
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