Building a PostgreSQL Executor Operator: A Comprehensive Guide
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Chapter 1: Understanding the Executor
The executor functions as a crucial link between the query plan and the storage engine. Its primary role involves retrieving data from the storage engine, executing relevant operations as dictated by the query plan, and ultimately delivering the final results of the query.
The executor can be categorized into two main processing models: the pull model and the push model.
Section 1.1: The Pull Model
Often referred to as the volcano model, this approach initiates execution from the top-level output node, progressively pulling data from lower nodes. This top-down execution method has several benefits and drawbacks.
Advantages:
- General Applicability: The pull model is versatile, capable of managing datasets of varying sizes.
- Control Flexibility: It allows for dynamic output control, such as the ability to limit results.
Disadvantages:
- Blocking Nodes: For operations like sorting, all data must be read first, complicating the sorting process based on available memory.
- Function Call Overhead: The numerous function calls during the data flow can hinder performance.
- Caching Issues: Frequent control statements and function calls may disrupt cache efficiency.
- Parallelism Challenges: This model does not lend itself well to parallel execution.
Section 1.2: The Push Model
The push model operates in the opposite manner, starting from the bottom-level nodes and continually generating data to send upwards, thus following a bottom-up execution path. This model is based on materialization, with each node processing all incoming data and then passing it on.
Advantages:
- Parallelism Friendly: It mitigates the issues of excessive function calls and cache switches, leading to better cache utilization.
Disadvantages:
- Increased Memory Usage: The push model often requires more memory due to its operational nature.
Section 1.3: The Vectorized Execution Engine
Beyond the pull and push models, the vectorized execution engine processes data in batches rather than individually, which minimizes function calls and boosts performance, particularly when combined with columnar storage and SIMD instructions.
Chapter 2: The Execution Process of the Executor
In this chapter, we will delve into how the executor interacts with upstream and downstream nodes, the role of internal operators, and the principles behind expressions and projections.
Section 2.1: Executor Relationships
Connecting the Executor to Operators:
The executor engages with operators through four key steps: ExecutorStart, ExecutorRun, ExecutorFinish, and ExecutorEnd. These hooks are essential for users looking to customize PostgreSQL extensions.
Query Plan Integration:
The executor associates with the query plan via a portal, which retains all execution-related information, including the query and plan trees, along with execution status.
Storage Layer Interaction:
The executor communicates with the storage layer through table access methods and scanning/modifying table operators.
Section 2.2: Expressions and Projections
In SQL, expressions extend beyond keywords like SELECT and FROM. They encompass any computation involving data, such as column manipulations.
Section 2.3: Principles of Expression Implementation
- ExprContext: This structure tracks the tuples required for evaluating each expression.
- ExprState: This is the primary node for expression evaluation, encompassing instructions for computation, storage for results, and specific handling for null values.
To illustrate, consider an expression tree for (a > 12 or (a + b > 30)) and a < b, where each part is mapped to an evaluation node, allowing for efficient execution through short-circuiting.
Chapter 3: Creating an Executor Operator
Suppose there is a requirement to introduce a data validation feature in the database, which verifies input data and raises errors or warnings for invalid entries. For instance, the execution plan could look like:
Copy -> Assert
Assert Cond: (i = 1)
-> Seq Scan
To implement an AssertOp operator, follow these steps:
- File Creation: Set up the header and implementation files, adding them to the makefile.
- State Initialization: Create a private state for the operator and define the necessary interfaces.
- Operator Setup: Initialize the operator state, set the execution function, and configure projection information and expressions.
- Execution Logic: Implement the logic for validating assertions, processing each downstream slot.
- Cleanup: Ensure all allocated resources and status information are properly cleared.
- Registration: Register the operator in the respective upstream mechanisms.
Summary:
This section has introduced the theoretical aspects of the executor, clarified its architecture, and provided a step-by-step guide to writing a basic executor operator.
This tutorial covers a comprehensive PostgreSQL course from 2022, offering insights into building and utilizing an executor operator.
In this video, Nickolay Ihalainen provides a detailed walkthrough on the installation and configuration of the PostgreSQL Operator.