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<h3 class="title-container">HAWQ Query Processing</h3>
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<div id ="main"><div style="visibility:hidden; height:2px;">Pivotal Product Documentation : HAWQ Query Processing</div><div class="wiki-content group" id="main-content">
<p align="LEFT">You can issue queries to HAWQ similarly to any database management system (DBMS). You can connect to the database instance on the HAWQ master host by using a client application such as psql and submitting SQL statements.</p><p align="LEFT">HAWQ offers the new ORCA query optimizer. This chapter describes how query planning works with the new query optimizer.</p><p align="LEFT"><style type="text/css">/*<![CDATA[*/
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<ul class="toc-indentation">
<li><a href="#HAWQQueryProcessing-QueryPlanningandDispatch">Query Planning and Dispatch</a>
<ul class="toc-indentation">
<li><a href="#HAWQQueryProcessing-PlanningandDispatch">Planning and Dispatch</a></li>
<li><a href="#HAWQQueryProcessing-ORCA">ORCA</a></li>
</ul>
</li>
<li><a href="#HAWQQueryProcessing-HAWQQueryPlans">HAWQ Query Plans</a></li>
<li><a href="#HAWQQueryProcessing-ParallelQueryExecution">Parallel Query Execution</a></li>
</ul>
</div></p><h2 id="HAWQQueryProcessing-QueryPlanningandDispatch">Query Planning and Dispatch</h2><p align="LEFT">This section describes the following:</p><ul><li>Planning and Dispatch</li><li>ORCA</li></ul><h3 id="HAWQQueryProcessing-PlanningandDispatch">Planning and Dispatch</h3><p align="LEFT">The master receives, parses, and optimizes the query. The resulting query plan is either <em>parallel</em> or <em>targeted</em>. The master dispatches parallel query plans to all segments, as shown in Figure 2.1. The master dispatches targeted query plans to a single segment, as shown in Figure 2.2.</p><p align="LEFT">Each segment is responsible for executing local database operations on its own set of data.</p><p align="LEFT"><img class="confluence-embedded-image" data-image-src="attachments/66453588/66781200.jpg" height="410" src="attachments/66453588/66781200.jpg" width="621"/></p><p align="LEFT" style="text-align: center;">Figure 2.1: Dispatching Parallel Query Plans</p><p align="LEFT"> </p><p align="LEFT"> </p><p align="LEFT"> <img class="confluence-embedded-image" data-image-src="attachments/66453588/66781199.jpg" src="attachments/66453588/66781199.jpg"/></p><p style="text-align: center;">Figure 2.2: Dispatching Targeted Query Plans</p><p>Certain queries may access only data on a single segment, such as single-row INSERT, UPDATE, DELETE, or SELECT operations, or queries that filter on the table distribution key column(s). In queries such as these, the query plan is not dispatched to all segments, but is targeted at the segment that contains the affected or relevant row(s).</p><h3 id="HAWQQueryProcessing-ORCA">ORCA</h3><p align="LEFT">ORCA is the new query optimizer built into HAWQ 1.1.1.0. It extends the planning and optimization capabilities of HAWQ. ORCA is extensible, verifiable, and achieves better optimization using multi-core architectures. ORCA also improves performance tuning.</p><p align="LEFT">The following flow chart shows how ORCA fits into the query planning architecture:</p><p align="LEFT"><img class="confluence-embedded-image" data-image-src="attachments/66453588/66781198.png" src="attachments/66453588/66781198.png"/></p><p align="LEFT">You can inspect the log to determine whether ORCA or the existing planner produced the plan. If you see the log message, "Optimizer produced plan", then ORCA generated the plan for your query. If the existing planner generated the plan, the log message reads "Planner produced plan". To turn off logging, see optimizer_log.</p><h2 id="HAWQQueryProcessing-HAWQQueryPlans">HAWQ Query Plans</h2><p align="LEFT">A <em>query plan</em> is the set of operations HAWQ will perform to produce the answer to a query. Each <em>node</em> or step in the plan represents a database operation such as a table scan, join, aggregation, or sort. Plans are read and executed from bottom to top.</p><p align="LEFT">In addition to common database operations such as tables scans, joins, and so on, HAWQ has an additional operation type called <em>motion</em>. A motion operation involves moving tuples between the segments during query processing. Note that not every query requires a motion. For example, a targeted query plan does not require data to move across the interconnect.</p><p align="LEFT">To achieve maximum parallelism during query execution, HAWQ divides the work of the query plan into <em>slices</em>. A slice is a portion of the plan that segments can work on independently. A query plan is sliced wherever a motion operation occurs in the plan, with one slice on each side of the motion.</p><p align="LEFT">For example, consider the following simple query involving a join between two tables:</p><pre>SELECT customer, amount</pre><pre>FROM sales JOIN customer USING (cust_id)</pre><pre>WHERE dateCol = '04-30-2008';</pre><p align="LEFT">The following figure shows the query plan. Each segment receives a copy of the query plan and works on it in parallel.</p><p align="LEFT"><img class="confluence-embedded-image" data-image-src="attachments/66453588/66781197.jpg" src="attachments/66453588/66781197.jpg"/></p><p align="LEFT">The query plan for this example has a redistribute motion that moves tuples between the segments to complete the join. The redistribute motion is necessary because the customer table is distributed across the segments by <em>cust_id</em>, but the sales table is distributed across the segments by <em>sale_id</em>. To perform the join, the sales tuples must be redistributed by <em>cust_id</em>. The plan is sliced on either side of the redistribute motion, creating slice 1 and slice 2.This query plan has another type of motion operation called a gather motion. A gather motion is when the segments send results back up to the master for presentation to the client. Because a query plan is always sliced wherever a motion occurs, this plan also has an implicit slice at the very top of the plan (slice 3). Not all query plans involve a gather motion. For example, a <em>CREATE TABLE x AS SELECT...</em> statement would not have a gather motion because tuples are sent to the newly created table, not to the master.</p><h2 id="HAWQQueryProcessing-ParallelQueryExecution">Parallel Query Execution</h2><p align="LEFT">HAWQ creates a number of database processes to handle the work of a query. On the master, the query worker process is called the <em>query dispatcher</em> (QD). The QD is responsible for creating and dispatching the query plan. It also accumulates and presents the final results. On the segments, a query worker process is called a <em>query executor</em> (QE). A QE is responsible for completing its portion of work and communicating its intermediate results to the other worker processes.</p><p align="LEFT">There is at least one worker process assigned to each <em>slice</em> of the query plan. A worker process works on its assigned portion of the query plan independently. During query execution, each segment will have a number of processes working on the query in parallel.</p><p align="LEFT">Related processes that are working on the same slice of the query plan but on different segments are called <em>gangs</em>. As a portion of work is completed, tuples flow up the query plan from one gang of processes to the next. This inter-process communication between the segments is referred to as the <em>interconnect</em> component of HAWQ. The following figure shows the query worker processes on the master and two segment instances for the query plan in slice_plan.jpg</p><p align="LEFT"><img class="confluence-embedded-image" data-image-src="attachments/66453588/66781196.jpg" src="attachments/66453588/66781196.jpg"/></p>
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