Amazon Redshift

Database Developer Guide (API Version 2012-12-01)

Welcome
- Are You a First-Time Amazon Redshift User?
- Are You a Database Developer?
- Prerequisites
Amazon Redshift System Overview
- Data Warehouse System Architecture
- Performance
- Columnar Storage
- Internal Architecture and System Operation
- Workload Management
- Using Amazon Redshift with Other Services
Getting Started Using Databases
- Step 1: Create a Database
- Step 2: Create a Database User
  - Delete a Database User
- Step 3: Create a Database Table
  - Insert Data Rows into a Table
  - Select Data from a Table
- Step 4: Load Sample Data
- Step 5: Query the System Tables
  - Determine the Process ID of a Running Query
- Step 6: Cancel a Query
- Step 7: Clean Up Your Resources
Amazon Redshift Best Practices
- Best Practices for Designing Tables
- Best Practices for Loading Data
- Best Practices for Designing Queries
Tutorial: Tuning Table Design
- Step 1: Create a Test Data Set
- Step 2: Establish a Baseline
- Step 3: Select Sort Keys
- Step 4: Select Distribution Styles
- Step 5: Review Compression Encodings
- Step 6: Recreate the Test Data Set
- Step 7: Retest System Performance After Tuning
- Step 8: Evaluate the Results
- Step 9: Clean Up Your Resources
- Summary
Tutorial: Loading Data from Amazon S3
- Step 1: Launch a Cluster
- Step 2: Download the Data Files
- Step 3: Upload the Files to an Amazon S3 Bucket
- Step 4: Create the Sample Tables
- Step 5: Run the COPY Commands
- Step 6: Vacuum and Analyze the Database
- Step 7: Clean Up Your Resources
- Summary
Tutorial: Configuring WLM Queues to Improve Query Processing
- Section 1: Understanding the Default Queue Processing Behavior
- Section 2: Modifying the WLM Query Queue Configuration
- Section 3: Routing Queries to Queues Based on User Groups and Query Groups
- Section 4: Using wlm_query_slot_count to Temporarily Override Concurrency Level in a Queue
- Section 5: Cleaning Up Your Resources
Managing Database Security
- Amazon Redshift Security Overview
- Default Database User Privileges
- Superusers
- Users
- Groups
- Schemas
- Example for Controlling User and Group Access
Designing Tables
- Choosing a Column Compression Type
- Choosing a Data Distribution Style
- Choosing Sort Keys
  - Comparing Sort Styles
- Defining Constraints
- Analyzing Table Design
Using Amazon Redshift Spectrum to Query External Data
- Getting Started With Amazon Redshift Spectrum
- IAM Policies for Amazon Redshift Spectrum
- Creating Data Files for Queries in Amazon Redshift Spectrum
- Creating External Schemas
- Creating External Tables
- Improving Amazon Redshift Spectrum Query Performance
- Monitoring Metrics
- Troubleshooting Queries
Loading Data
- Using COPY to Load Data
- Updating with DML
- Updating and Inserting
- Performing a Deep Copy
- Analyzing Tables
  - ANALYZE Command History
  - Automatic Analysis
- Vacuuming Tables
  - Managing Vacuum Times
  - Vacuum Column Limit Exceeded Error
- Managing Concurrent Write Operations
Unloading Data
- Unloading Data to Amazon S3
- Unloading Encrypted Data Files
- Unloading Data in Delimited or Fixed-Width Format
- Reloading Unloaded Data
Creating User-Defined Functions
- UDF Security and Privileges
- Creating a Scalar SQL UDF
- Creating a Scalar Python UDF
- Naming UDFs
- Logging Errors and Warnings
Tuning Query Performance
- Query Processing
- Analyzing and Improving Queries
- Troubleshooting Queries
Implementing Workload Management
- Defining Query Queues
- WLM Query Queue Hopping
- Short Query Acceleration
- Modifying the WLM Configuration
- WLM Queue Assignment Rules
- Assigning Queries to Queues
- Dynamic and Static Properties
  - WLM Dynamic Memory Allocation
  - Dynamic WLM Example
- Query Monitoring Rules
- WLM System Tables and Views
SQL Reference
- Amazon Redshift SQL
  - SQL Functions Supported on the Leader Node
  - Amazon Redshift and PostgreSQL
- Using SQL
- SQL Commands
- SQL Functions Reference
- Reserved Words
System Tables Reference
- System Tables and Views
- Types of System Tables and Views
- Visibility of Data in System Tables and Views
- STL Tables for Logging
- STV Tables for Snapshot Data
- System Views
- System Catalog Tables
Configuration Reference
- Modifying the Server Configuration
- analyze_threshold_percent
- datestyle
- describe_field_name_in_uppercase
- enable_result_cache_for_session
- extra_float_digits
- max_cursor_result_set_size
- query_group
- search_path
- statement_timeout
- timezone
- wlm_query_slot_count
Sample Database
- CATEGORY Table
- DATE Table
- EVENT Table
- VENUE Table
- USERS Table
- LISTING Table
- SALES Table
Time Zone Names and Abbreviations
- Time Zone Names
- Time Zone Abbreviations
Document History

TO_TIMESTAMP Function

TO_TIMESTAMP converts a TIMESTAMP string to TIMESTAMPTZ.

Syntax


to_timestamp ('timestamp', 'format')

Arguments

timestamp: A string that represents a time stamp value in the format specified by format.
format: The format for the timestamp value. Formats that include a time zone (TZ, tz, or OF) are not supported as input. For valid time stamp formats, see Datetime Format Strings.

Return Type

TIMESTAMPTZ

Warning Javascript is disabled or is unavailable in your browser.

To use the AWS Documentation, Javascript must be enabled. Please refer to your browser's Help pages for instructions.

Document Conventions

« Previous Next »

© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.

On this page:

Syntax
Arguments
Return Type