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<h3 class="title-container">HAWQ Overview</h3>
<div class="content">
<!-- Python script replaces main content -->
<div id ="main"><div style="visibility:hidden; height:2px;">Pivotal Product Documentation : HAWQ Overview</div><div class="wiki-content group" id="main-content">
<p align="LEFT">This chapter describes all of the components that comprise a HAWQ system, and how they work together.</p><p align="LEFT"><style type="text/css">/*<![CDATA[*/
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<ul class="toc-indentation">
<li><a href="#HAWQOverview-AbouttheHAWQArchitecture">About the HAWQ Architecture</a></li>
<li><a href="#HAWQOverview-HAWQMaster">HAWQ Master</a>
<ul class="toc-indentation">
<li><a href="#HAWQOverview-HAWQSegment">HAWQ Segment</a></li>
<li><a href="#HAWQOverview-HAWQStorage">HAWQ Storage</a></li>
<li><a href="#HAWQOverview-HAWQInterconnect">HAWQ Interconnect</a></li>
</ul>
</li>
<li><a href="#HAWQOverview-RedundancyandFailoverinHAWQ">Redundancy and Failover in HAWQ</a>
<ul class="toc-indentation">
<li><a href="#HAWQOverview-AboutMasterMirroring">About Master Mirroring</a></li>
<li><a href="#HAWQOverview-AboutSegmentFailover">About Segment Failover</a></li>
<li><a href="#HAWQOverview-AboutInterconnectRedundancy">About Interconnect Redundancy</a></li>
</ul>
</li>
</ul>
</div></p><h2 id="HAWQOverview-AbouttheHAWQArchitecture">About the HAWQ Architecture</h2><p>HAWQ is designed as a MPP SQL processing engine optimized for analytics with full transaction support. HAWQ breaks complex queries into small tasks and distributes them to MPP query processing units for execution. The query planner, dynamic pipeline, leading edge interconnect, and the specific query executor optimization for distributed storage are designed to work seamlessly, to support highest level of performance and scalability.</p><p align="LEFT">HAWQ’s basic unit of parallelism is the segment instance. Multiple segment instances on commodity servers work together to form a single parallel query processing system. A query submitted to HAWQ is optimized, broken into smaller components, and dispatched to segments that work together to deliver a single result set. All relational operations—such as table scans, joins, aggregations, and sorts—simultaneously execute in parallel across the segments. Data from upstream components in the dynamic pipeline are transmitted to downstream components through the scalable User Datagram Protocol (UDP) interconnect.</p><p align="LEFT">Based on Hadoop’s distributed storage, HAWQ has no single point of failure and supports fully-automatic online recovery. System states are continuously monitored, therefore if a segment fails, it is automatically removed from the cluster. During this process, the system continues serving customer queries, and the segments can be added back to the system when necessary.</p><h2 id="HAWQOverview-HAWQMaster">HAWQ Master</h2><p align="LEFT">The HAWQ <em>master</em> is the entry point to the system. It is the database process that accepts client connections and processes the SQL commands issued.</p><p align="LEFT">End-users interact with HAWQ (through the master) as they would with a typical PostgreSQL database. They can connect to the database using client programs such as psql or application programming interfaces (APIs) such as JDBC or ODBC.</p><p align="LEFT">The master is where the <em>global system catalog</em> resides. The global system catalog is the set of system tables that contain metadata about the HAWQ system itself. The master does not contain any user data; data resides only on <em>HDFS</em>. 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.</p><h3 id="HAWQOverview-HAWQSegment">HAWQ Segment</h3><p align="LEFT">In HAWQ, the <em>segments</em> are the units which process the individual data modules simultaneously.</p><p align="LEFT">A segment differs from a master by being stateless and because it:</p><ul><li>Does not store the metadata for each database and table</li><li>Does not store data on the local file system.</li></ul><p align="LEFT">The master dispatches the SQL request to the segments along with the related metadata information to process. The metadata contains the HDFS url for the required table. The segment accesses the corresponding data using this URL.</p><h3 id="HAWQOverview-HAWQStorage">HAWQ Storage</h3><p align="LEFT">HAWQ stores all table data, except the system table, in HDFS. When a user creates a table, the metadata is stored on the master’s local file system and the table content is stored in HDFS.</p><h3 id="HAWQOverview-HAWQInterconnect">HAWQ Interconnect</h3><p align="LEFT">The <em>interconnect</em> is the networking layer of HAWQ. When a user connects to a database and issues a query, processes are created on each segment to handle the query. The <em>interconnect</em> refers to the inter-process communication between the segments, as well as the network infrastructure on which this communication relies. The interconnect uses standard Ethernet switching fabric.</p><p align="LEFT">By default, the interconnect uses UDP (User Datagram Protocol) to send messages over the network. The HAWQ software performs the additional 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 that of TCP. If the interconnect used TCP, HAWQ would have a scalability limit of 1000 segment instances. With UDP as the current default protocol for the interconnect, this limit is not applicable.</p><h2 id="HAWQOverview-RedundancyandFailoverinHAWQ">Redundancy and Failover in HAWQ</h2><p align="LEFT">HAWQ provides deployment options that protect the system from having a single point of failure. The following sections explain the redundancy components of HAWQ.</p><ul><li>About Master Mirroring</li><li>About Segment Failover</li><li>About Interconnect Redundancy</li></ul><h3 id="HAWQOverview-AboutMasterMirroring">About Master Mirroring</h3><p align="LEFT">You can optionally deploy a <em>backup</em> or <em>mirror</em> of the master instance on a separate host from the master node. A backup master host serves as a <em>warm standby</em> in the event that the primary master host becomes inoperable. The standby master is kept up to date by a transaction log replication process. The transaction log replication process runs on the standby master host and synchronizes the data between the primary and standby master hosts.</p><p align="LEFT">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.</p><h3 id="HAWQOverview-AboutSegmentFailover">About Segment Failover</h3><p align="LEFT">In HAWQ, the segments are stateless. This ensures faster recovery and better availability.</p><p align="LEFT">When a segment is down, the existing sessions are automatically reassigned to the remaining segments. If a new session is created during segment downtime, it succeeds on the remaining segments.</p><p align="LEFT">When the segments are operational again, the Fault Tolerance Service verifies their state, returning the segment number to normal. All the sessions are automatically reconfigured to use the full computing power.</p><h3 id="HAWQOverview-AboutInterconnectRedundancy">About Interconnect Redundancy</h3><p align="LEFT">The <em>interconnect</em> 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 deploying redundant Gigabit connections to the HAWQ host (master and segment) servers.</p>
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