Learning Apache Drill. Query and Analyze Distributed Data Sources with SQL

Spis treści książki

• Preface
  • Who Should Read This Book
  • Why We Wrote This Book
  • Navigating This Book
  • Online Resources
  • Conventions Used in This Book
  • Using Code Examples
  • OReilly Safari
  • How to Contact Us
  • Acknowledgments
  • Special Thanks from Charles
  • Special Thanks from Paul
• 1. Introduction to Apache Drill
  • What Is Apache Drill?
    • Drill Is Versatile
    • Drill Is Easy to Use
      • Drill does not require you to define a schema
    • A Word About Drills Performance
    • A Very Brief History of Big Data
      • Hadoop
    • Drill in the Big Data Ecosystem
    • Comparing Drill with Similar Tools
• 2. Installing and Running Drill
  • Preparing Your Machine for Drill
    • Special Configuration Instructions for Windows Installations
  • Installing Drill on Windows
    • Starting Drill on a Windows Machine
  • Installing Drill in Embedded Mode on macOS or Linux
    • Starting Drill on macOS or Linux in Embedded Mode
  • Installing Drill in Distributed Mode on macOS or Linux
    • Preparing Your Cluster for Drill
    • Starting Drill in Distributed Mode
  • Connecting to the Cluster
  • Conclusion
• 3. Overview of Apache Drill
  • The Apache Hadoop Ecosystem
    • Drill Is a Low-Latency Query Engine
    • Distributed Processing with HDFS
    • Elements of a Drill System
    • Drill Operation: The 30,000-Foot View
    • Drill Is a Query Engine, Not a Database
  • Drill Operation Overview
    • Drill Components
    • SQL Session State
    • Statement Preparation
      • Parsing and semantic analysis
      • Logical and physical plans
      • Distribution
    • Statement Execution
      • Data representation
    • Low-Latency Features
      • Long-lived Drillbits
      • Code generation
      • Network exchanges
  • Conclusion
• 4. Querying Delimited Data
  • Ways of Querying Data with Drill
    • Other Interfaces
  • Drill SQL Query Format
    • Choosing a Data Source
    • Defining a Workspace
    • Specifying a Default Data Source
    • Accessing Columns in a Query
    • Delimited Data with Column Headers
    • Table Functions
    • Querying Directories
      • Directory functions
  • Understanding Drill Data Types
  • Cleaning and Preparing Data Using String Manipulation Functions
    • Complex Data Conversion Functions
      • Reformatting numbers
  • Working with Dates and Times in Drill
    • Converting Strings to Dates
    • Reformatting Dates
    • Date Arithmetic and Manipulation
    • Date and Time Functions in Drill
  • Creating Views
  • Data Analysis Using Drill
    • Summarizing Data with Aggregate Functions
      • Other analytic functions: Window functions
      • Comparison of aggregate and window analytic functions
  • Common Problems in Querying Delimited Data
    • Spaces in Column Names
    • Illegal Characters in Column Headers
    • Reserved Words in Column Names
  • Conclusion
• 5. Analyzing Complex and Nested Data
  • Arrays and Maps
    • Arrays in Drill
    • Accessing Maps (KeyValue Pairs) in Drill
    • Querying Nested Data
      • Data types in JSON files
      • Formats of nested data
        • Querying record-oriented files
        • Using the FLATTEN() function to query split JSON files
        • Querying column-oriented JSON files with KVGEN()
  • Analyzing Log Files with Drill
    • Configuring Drill to Read HTTPD Web Server Logs
    • Querying Web Server Logs
      • Analyzing user agent strings
      • Analyzing URLs and query strings
    • Other Log Analysis with Drill
  • Conclusion
• 6. Connecting Drill to Data Sources
  • Querying Multiple Data Sources
    • Configuring a New Storage Plug-in
    • Connecting Drill to a Relational Database
      • Configuring Drill to query an RDBMS
        • Microsoft SQL Server
        • MySQL
        • Oracle
        • PostgreSQL
        • SQLite
      • Querying an RDBMS from Drill
      • Other uses of the drill JDBC storage plug-in
    • Querying Data in Hadoop from Drill
    • Connecting to and Querying HBase from Drill
      • Querying data from HBase
    • Querying Hive Data from Drill
      • Connecting Drill to Hive
        • Connecting to Hive with a remote metastore
    • Connecting to and Querying Streaming Data with Drill and Kafka
      • Querying streaming data
      • Improving the performance of Kafka queries
    • Connecting to and Querying Kudu
    • Connecting to and Querying MongoDB from Drill
    • Connecting Drill to Cloud Storage
      • Querying data on Amazon S3
        • Getting access credentials for S3
      • Querying Minio datastores from drill
      • Connecting to other cloud storage services
    • Querying Time Series Data from Drill and OpenTSDB
      • Special considerations for time series data
  • Conclusion
• 7. Connecting to Drill
  • Understanding Drills Interfaces
    • JDBC and Drill
    • ODBC and Drill
      • Installing the ODBC driver
        • Configuring ODBC on Linux or macOS
        • Configuring ODBC on Windows
    • Drills REST Interface
  • Connecting to Drill with Python
    • Using drillpy to Query Drill
    • Connecting to Drill Using pydrill
      • Other functionality of pydrill
    • Other Ways of Connecting to Drill from Python
  • Connecting to Drill Using R
    • Querying Drill from R Using sergeant
      • Accessing other functionality in R
  • Connecting to Drill Using Java
  • Querying Drill with PHP
    • Using the Connector
    • Querying Drill from PHP
    • Interacting with Drill from PHP
  • Querying Drill Using Node.js
  • Using Drill as a Data Source in BI Tools
    • Exploring Data with Apache Zeppelin and Drill
      • Configuring Zeppelin to query Drill
      • Querying Drill from a Zeppelin notebook
      • Adding interactivity in Zeppelin
    • Exploring Data with Apache Superset
      • Configuring Superset to work with Drill
      • Building a demonstration visualization using Drill and Superset
  • Conclusion
• 8. Data Engineering with Drill
  • Schema-on-Read
    • The SQL Relational Model
    • Data Life Cycle: Data Exploration to Production
    • Schema Inference
  • Data Source Inference
    • Storage Plug-ins
    • Storage Configurations
    • Workspaces
    • Querying Directories
    • Default Schema
  • File Type Inference
    • Format Plug-ins and Format Configuration
    • Format Inference
    • File Format Variations
  • Schema Inference Overview
  • Distributed File Scans
    • Schema Inference for Delimited Data
      • CSV with header
      • Explicit projection
      • TypeOf functions
      • Casts to specify types
    • CSV Summary
      • CSV without a header row
      • Explicit projection
    • Schema Inference for JSON
      • JSON column names
      • JSON scalar types
    • Ambiguous Numeric Schemas
      • Mixed string and number types
      • Missing values
      • Leading null values
      • Null versus missing values in JSON output
  • Aligning Schemas Across Files
  • JSON Objects
    • JSON Lists in Drill
    • JSON Summary
  • Using Drill with the Parquet File Format
    • Schema Evolution in Parquet
  • Partitioning Data Directories
    • Defining a Table Workspace
  • Working with Queries in Production
    • Capturing Schema Mapping in Views
    • Running Challenging Queries in Scripts
  • Conclusion
• 9. Deploying Drill in Production
  • Installing Drill
    • Prerequisites
    • Production Installation
      • Creating a Site Directory
    • Configuring ZooKeeper
      • Advanced ZooKeeper configuration
    • Configuring Memory
    • Configuring Logging
    • Testing the Installation
    • Distributing Drill Binaries and Configuration
      • Installing clush
      • Distributing Drill files
    • Starting the Drill Cluster
  • Configuring Storage
    • Working with Apache Hadoop HDFS
      • Simple HDFS integration
      • Full HDFS integration
    • Working with Amazon S3
      • Access keys with Hadoop
      • Standalone Drill
      • Distributing the configuration
      • Defining the Amazon S3 storage configuration
      • Troubleshooting
  • Admission Control
  • Additional Configuration
    • User-Defined Functions and Custom Plug-ins
    • Security
    • Logging Levels
    • Controlling CPU Usage
  • Monitoring
    • Monitoring the Drill Process
    • Monitoring JMX Metrics
    • Monitoring Queries
  • Other Deployment Options
    • MapR Installer
    • Drill-on-YARN
    • Docker
  • Conclusion
• 10. Setting Up Your Development Environment
  • Installing Maven
  • Creating the Drill Build Environment
    • Setting Up Git and Getting the Source Code
    • Building Drill from Source
  • Installing the IDE
  • Conclusion
• 11. Writing Drill User-Defined Functions
  • Use Case: Finding and Filtering Valid Credit Card Numbers
  • How User-Defined Functions Work in Drill
  • Structure of a Simple Drill UDF
    • The pom.xml File
      • Including dependencies
    • The Function File
      • Defining input parameters
      • Setting the output value
      • Accessing data in holder objects
    • The Simple Function API
    • Putting It All Together
  • Building and Installing Your UDF
    • Statically Installing a UDF
    • Dynamically Installing a UDF
  • Complex Functions: UDFs That Return Maps or Arrays
    • Example: Extracting User Agent Metadata
    • The ComplexWriter
  • Writing Aggregate User-Defined Functions
    • The Aggregate Function API
    • Example Aggregate UDF: Kendalls Rank Correlation Coefficient
  • Conclusion
• 12. Writing a Format Plug-in
  • The Example Regex Format Plug-in
  • Creating the Easy Format Plug-in
    • Creating the Maven pom.xml File
    • Creating the Plug-in Package
    • Drill Module Configuration
    • Format Plug-in Configuration
    • Cautions Before Getting Started
  • Creating the Regex Plug-in Configuration Class
    • Copyright Headers and Code Format
    • Testing the Configuration
    • Fixing Configuration Problems
    • Troubleshooting
  • Creating the Format Plug-in Class
    • Creating a Test File
    • Configuring RAT
    • Efficient Debugging
    • Creating the Unit Test
    • How Drill Finds Your Plug-in
  • The Record Reader
    • Testing the Reader Shell
    • Logging
    • Error Handling
    • Setup
    • Regex Parsing
    • Defining Column Names
    • Projection
    • Column Projection Accounting
    • Project None
    • Project All
    • Project Some
    • Opening the File
    • Record Batches
    • Drills Columnar Structure
    • Defining Vectors
    • Reading Data
    • Loading Data into Vectors
    • Releasing Resources
  • Testing the Reader
    • Testing the Wildcard Case
    • Testing Explicit Projection
    • Testing Empty Projection
    • Scaling Up
  • Additional Details
    • File Chunks
    • Default Format Configuration
    • Next Steps
    • Production Build
    • Contributing to Drill: The Pull Request
    • Maintaining Your Branch
    • Create a Plug-In Project
  • Conclusion
• 13. Unique Uses of Drill
  • Finding Photos Taken Within a Geographic Region
  • Drilling Excel Files
    • The pom.xml File
    • The Excel Custom Record Reader
    • Using the Excel Format Plug-in
  • Network Packet Analysis (PCAP) with Drill
    • Examples of Queries Using PCAP Data Files
      • Automating the process using an aggregate function
  • Analyzing Twitter Data with Drill
  • Using Drill in a Machine Learning Pipeline
    • Making Predictions Within Drill
    • Building and Serializing a Model
    • Writing the UDF Wrapper
    • Making Predictions Using the UDF
  • Conclusion
• A. List of Drill Functions
  • Aggregate and Window Functions
    • Window Functions
  • Cryptological and Hashing Functions
  • Data Conversion Functions
  • Geospatial Functions
  • Math and Trigonometric Functions
  • Networking Functions
  • Null Handling Functions
  • String Manipulation Functions
  • Approximate String Matching Functions
    • Phonetic Functions
    • String Distance Functions
• B. Drill Formatting Strings
• Index

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