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Amazon QuickSight
User Guide

Data Source Limits

Data sources that you use with Amazon QuickSight must conform to the following limits.

File Limits

Any file you import into SPICE must be 1 GB or smaller, whether that file is local or coming from Amazon S3.

If you are retrieving multiple files from Amazon S3, the total size of the files specified in the manifest file cannot exceed 10 GB, and the total number of files specified in the manifest file cannot exceed 1000.

Files can have up to 200 columns, with up to 25400 characters per row. It does not matter how characters are distributed across the fields (except the field length limitation of 511 characters) as long as they do not exceed this total.

Table and Query Limits

Any table or query result set you import into SPICE must be 10 GB or smaller. If you want to retrieve data from a larger table, use predicates in a SQL query to reduce the size of the result set.

Field Limits

Data in any field of a data set you import into SPICE must be 511 characters or less.

Supported Data Types

Amazon QuickSight currently supports the following primitive data types:

  • Date. Dates must be in one of the Supported Date Formats.

  • Decimal. The decimal data type supports up to four decimal places to the right of the decimal point. Values that have a higher scale than this are truncated to the fourth decimal place when displayed in data preparation or analyses and when imported into SPICE. For example, 13.00049 is truncated to 13.0004.

    During data preparation, calculated fields that use decimal data with more than four decimal places use the full value to perform the calculation. If the result is again decimal data that uses more than four decimal places, the result is then truncated as described preceding. For more information, see Handling Decimal Values in Calculated Fields.

  • Integer

  • String

Make sure that any table or file that you use as a data source contains only fields that can be implicitly converted to these data types (for example, fields using geospatial data types). Amazon QuickSight skips any data rows that can't be converted.

The following table lists the source data types that are supported. Boolean data types are converted to integers in Amazon QuickSight.

Database Engine or Source Numeric Data Types String Data Types Datetime Data Types Boolean Data Types

Amazon Athena, Presto

  • bigint

  • decimal

  • double

  • integer

  • real

  • smallint

  • tinyint

  • char

  • varchar

  • date

  • timestamp

  • boolean

Amazon Aurora, MariaDB, and MySQL

  • bigint

  • decimal

  • double

  • int

  • integer

  • mediumint

  • numeric

  • smallint

  • tinyint

  • binary

  • blob

  • char

  • enum

  • set

  • text

  • varbinary

  • varchar

  • date

  • datetime

  • timestamp

  • year

PostgreSQL

  • bigint

  • decimal

  • double

  • integer

  • numeric

  • precision

  • real

  • smallint

  • char

  • character

  • text

  • varchar

  • varying character

  • date

  • timestamp

  • boolean

Apache Spark

  • bigint

  • decimal

  • double

  • integer

  • real

  • smallint

  • tinyint

  • varchar

  • date

  • timestamp

  • boolean

Snowflake

  • bigint

  • byteint

  • decimal

  • double

  • doubleprecision

  • float

  • float4

  • float8

  • int

  • integer

  • number

  • numeric

  • real

  • smallint

  • tinyint

  • char

  • character

  • string

  • text

  • varchar

  • date

  • datetime

  • time

  • timestamp

  • timestamp_*

  • boolean

SQL Server

  • bigint

  • bit

  • decimal

  • decimal

  • int

  • money

  • numeric

  • real

  • smallint

  • smallmoney

  • tinyint

  • char

  • nchar

  • nvarchar

  • text

  • varchar

  • date

  • datetime

  • datetime2

  • datetimeoffset

  • smalldatetime

  • bit

Unsupported Data Values

If a field contains values that don't conform with the data type that Amazon QuickSight assigns to the field, the rows containing those values are skipped. For example, given the following source data:

Copy
Sales ID Sales Date Sales Amount -------------------------------------- 001 10/14/2015 12.43 002 5/3/2012 25.00 003 Unknown 18.17 004 3/8/2009 86.02

Amazon QuickSight interprets Sales Date as a date field and drops the row containing a non-date value, so only the following rows are imported:

Copy
Sales ID Sales Date Sales Amount -------------------------------------- 001 10/14/2015 12.43 002 5/3/2012 25.00 004 3/8/2009 86.02

Also, if a database field contains values that can't be interpreted by the JDBC driver for the source database engine, the uninterpretable values are replaced by null so that the rows can be imported. The only known occurrence of this issue is with MySQL date, datetime, and timestamp fields that have all-zero values, for example 0000-00-00 00:00:00. For example, given the following source data:

Copy
Sales ID Sales Date Sales Amount --------------------------------------------------- 001 2004-10-12 09:14:27 12.43 002 2012-04-07 12:59:03 25.00 003 0000-00-00 00:00:00 18.17 004 2015-09-30 01:41:19 86.02

The following data is imported:

Copy
Sales ID Sales Date Sales Amount --------------------------------------------------- 001 2004-10-12 09:14:27 12.43 002 2012-04-07 12:59:03 25.00 003 (null) 18.17 004 2015-09-30 01:41:19 86.02

Handling Date Time Zones

Amazon QuickSight uses UTC time for querying, filtering, and displaying date data.

When date data doesn't specify a time zone, Amazon QuickSight assumes UTC values. When date data does specify a time zone, Amazon QuickSight converts it to display in UTC time. For example, a date field with a time zone offset like 2015-11-01T03:00:00-08:00 is converted to UTC and displayed in Amazon QuickSight as 2015-11-01T15:30:00.

Supported Date Formats

Data in date fields must be in one of the following supported formats, depending on the data source type.

For file uploads, Amazon S3 sources, Athena and Salesforce, Amazon QuickSight supports the use of date and time formats (both 24 hr and am/pm) described in the Joda API documentation. See Class DateTimeFormat for a complete list of Joda date formats.

For relational database sources, including Amazon Redshift, Amazon RDS, PostgreSQL, MySQL, Aurora, MariaDB, and Microsoft SQL Server, Amazon QuickSight supports the following date and time formats (24 hr only):

Amazon QuickSight supports dates in the range from Jan 1, 1900 00:00:00 UTC to Dec 31, 2037 23:59:59 UTC

  1. dd/MM/yyyy HH:mm:ss, for example 31/12/2016 15:30:00.

  2. dd/MM/yyyy, for example 31/12/2016.

  3. dd/MMM/yyyy HH:mm:ss, for example 31/DEC/2016 15:30:00.

  4. dd/MMM/yyyy, for example 31/DEC/2016.

  5. dd-MMM-yyyy HH:mm:ss, for example 31-DEC-2016 15:30:00.

  6. dd-MMM-yyyy, for example 31-DEC-2016.

  7. dd-MM-yyyy HH:mm:ss, for example 31-12-2016 15:30:00.

  8. dd-MM-yyyy, for example 31-12-2016.

  9. MM/dd/yyyy HH:mm:ss, for example 12/31/2016 15:30:00.

  10. MM/dd/yyyy, for example 12/31/2016.

  11. MM-dd-yyyy HH:mm:ss, for example 12-31-2016 15:30:00.

  12. MM-dd-yyyy, for example 12-31-2016.

  13. MMM/dd/yyyy HH:mm:ss, for example DEC/31/2016 15:30:00.

  14. MMM/dd/yyyy, for example DEC/31/2016.

  15. MMM-dd-yyyy HH:mm:ss, for example DEC-31-2016 15:30:00.

  16. MMM-dd-yyyy, for example DEC-31-2016.

  17. yyyy/MM/dd HH:mm:ss, for example 2016/12/31 15:30:00.

  18. yyyy/MM/dd, for example 2016/12/31.

  19. yyyy/MMM/dd HH:mm:ss, for example 2016/DEC/31 15:30:00.

  20. yyyy/MMM/dd, for example 2016/DEC/31.

  21. yyyy-MM-dd HH:mm:ss, for example 2016-12-31 15:30:00.

  22. yyyy-MM-dd, for example 2016-12-31.

  23. yyyy-MMM-dd HH:mm:ss, for example 2016-DEC-31 15:30:00.

  24. yyyy-MMM-dd, for example 2016-DEC-31.