General guidance for query execution in Query Service

This document details important details to know when writing queries in Adobe Experience Platform Query Service.

For detailed information on the SQL syntax used in Query Service, please read the SQL syntax documentation.

Query execution models

Adobe Experience Platform Query Service has two models of query execution: interactive and non-interactive. Interactive execution is used for query development and report generation in business intelligence tools, while non-interactive is used for larger jobs and operational queries as a part of a data processing workflow.

Interactive query execution

Queries can be executed interactively by submitting them through the Query Service UI or through a connected client. When running Query Service through a connected client, an active session runs between the client and Query Service until either the submitted query returns or times out.

Interactive query execution has the following limitations:

Parameter Limitation
Query timeout 10 minutes
Maximum rows returned 50,000
Maximum concurrent queries 5
NOTE

To override the maximum rows limitation, include LIMIT 0 in your query. The query timeout of 10 minutes still applies.

By default, the results of interactive queries are returned to the client and are not persisted. In order to persist the results as a dataset in Experience Platform, the query must use the CREATE TABLE AS SELECT syntax.

Non-interactive query execution

Queries submitted through the Query Service API are run non-interactively. Non-interactive execution means that Query Service receives the API call and executes the query in the order it is received. Non-interactive queries always result in either the generation of a new dataset in Experience Platform to receive the results, or the insertion of new rows into an existing dataset.

Accessing a specific field within an object

To access a field within an object in your query, you can use either dot notation (.) or bracket notation ([]). The following SQL statement uses dot notation to traverse the endUserIds object down to the mcid object.

SELECT endUserIds._experience.mcid
FROM {ANALYTICS_TABLE_NAME}
WHERE endUserIds._experience.mcid IS NOT NULL
AND TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}')
LIMIT 1
Property Description
{ANALYTICS_TABLE_NAME} The name of your analytics table.

The following SQL statement uses bracket notation to traverse the endUserIds object down to the mcid object.

SELECT endUserIds['_experience']['mcid']
FROM {ANALYTICS_TABLE_NAME}
WHERE endUserIds._experience.mcid IS NOT NULL
AND TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}')
LIMIT 1
Property Description
{ANALYTICS_TABLE_NAME} The name of your analytics table.
NOTE

Since each notation type returns the same results, the one you choose to use is up to your preference.

Both of the example queries above return a flattened object, rather than a single value:

              endUserIds._experience.mcid   
--------------------------------------------------------
 (48168239533518554367684086979667672499,"(ECID)",true)
(1 row)

The returned endUserIds._experience.mcid object contains the corresponding values for the following parameters:

  • id
  • namespace
  • primary

When the column is only declared down to the object, it returns the entire object as a string. To view only the ID, use:

SELECT endUserIds._experience.mcid.id
FROM {ANALYTICS_TABLE_NAME}
WHERE endUserIds._experience.mcid IS NOT NULL
AND TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}')
LIMIT 1
     endUserIds._experience.mcid.id 
----------------------------------------
 48168239533518554367684086979667672499
(1 row)

Quotes

Single quotes, double quotes, and back quotes have different usages within Query Service queries.

Single quotes

The single quote (') is used to create text strings. For example, it can be used in the SELECT statement to return a static text value in the result, and in the WHERE clause to evaluate the content of a column.

The following query declares a static text value ('datasetA') for a column:

SELECT 
  'datasetA',
  timestamp,
  web.webPageDetails.name
FROM {ANALYTICS_TABLE_NAME}
WHERE TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}')
LIMIT 10

The following query uses a single-quoted string ('homepage') in its WHERE clause to return events for a specific page.

SELECT 
  timestamp,
  endUserIds._experience.mcid.id
FROM {ANALYTICS_TABLE_NAME}
WHERE web.webPageDetails.name = 'homepage'
AND TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}')
LIMIT 10

Double quotes

The double quote (") is used to declare an identifier with spaces.

The following query uses double quotes to return values from specified columns when one column contains a space in its identifier:

SELECT
  no_space_column,
  "space column"
FROM
( SELECT 
    'column1' as no_space_column,
    'column2' as "space column"
)
NOTE

Double quotes cannot be used with dot notation field access.

Back quotes

The back quote ` is used to escape reserved column names only when using dot notation syntax. For example, since order is a reserved word in SQL, you must use back quotes to access the field commerce.order:

SELECT 
  commerce.`order`
FROM {ANALYTICS_TABLE_NAME}
WHERE TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}')
LIMIT 10

Back quotes are also used to access a field that starts with a number. For example, to access the field 30_day_value, you would need to use back quote notation.

SELECT
    commerce.`30_day_value`
FROM {ANALYTICS_TABLE_NAME}
WHERE TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}')
LIMIT 10

Back quotes are not needed if you are using bracket-notation.

 SELECT
  commerce['order']
 FROM {ANALYTICS_TABLE_NAME}
 WHERE TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}')
 LIMIT 10

Viewing table information

After connecting to Query Service, you can see all your available tables on Platform by using either the \d or SHOW TABLES commands.

Standard table view

The \d command shows the standard PostgreSQL view for listing tables. An example of this command’s output can be seen below:

             List of relations
 Schema |       Name      | Type  |  Owner   
--------+-----------------+-------+----------
 public | luma_midvalues  | table | postgres
 public | luma_postvalues | table | postgres
(2 rows)

Detailed table view

SHOW TABLES command is a custom command that provides more detailed information about the tables. An example of this command’s output can be seen below:

       name      |        dataSetId         |     dataSet    | description | resolved 
-----------------+--------------------------+----------------+-------------+----------
 luma_midvalues  | 5bac030c29bb8d12fa992e58 | Luma midValues |             | false
 luma_postvalues | 5c86b896b3c162151785b43c | Luma midValues |             | false
(2 rows)

Schema information

To view more detailed information about the schemas within the table, you can use the \d {TABLE_NAME} command, where {TABLE_NAME} is the name of the table whose schema information you want to view.

The following example shows the schema information for the luma_midvalues table, which would be seen by using \d luma_midvalues:

                         Table "public.luma_midvalues"
      Column       |             Type            | Collation | Nullable | Default 
-------------------+-----------------------------+-----------+----------+---------
 timestamp         | timestamp                   |           |          | 
 _id               | text                        |           |          | 
 productlistitems  | anyarray                    |           |          | 
 commerce          | luma_midvalues_commerce     |           |          | 
 receivedtimestamp | timestamp                   |           |          | 
 enduserids        | luma_midvalues_enduserids   |           |          | 
 datasource        | datasource                  |           |          | 
 web               | luma_midvalues_web          |           |          | 
 placecontext      | luma_midvalues_placecontext |           |          | 
 identitymap       | anymap                      |           |          | 
 marketing         | marketing                   |           |          | 
 environment       | luma_midvalues_environment  |           |          | 
 _experience       | luma_midvalues__experience  |           |          | 
 device            | device                      |           |          | 
 search            | search                      |           |          | 

Additionally, you can get further information about a particular column by appending the name of the column to the table name. This would be written in the format \d {TABLE_NAME}_{COLUMN}.

The following example shows additional information for the web column, and would be invoked by using the following command: \d luma_midvalues_web:

                 Composite type "public.luma_midvalues_web"
     Column     |               Type                | Collation | Nullable | Default 
----------------+-----------------------------------+-----------+----------+---------
 webpagedetails | luma_midvalues_web_webpagedetails |           |          | 
 webreferrer    | web_webreferrer                   |           |          | 

Joining datasets

You can join multiple datasets together to include data from other datasets in your query.

The following example would join the following two datasets (your_analytics_table and custom_operating_system_lookup) and creates a SELECT statement for the top 50 operating systems by number of page views.

Query

SELECT 
  b.operatingsystem AS OperatingSystem,
  SUM(a.web.webPageDetails.pageviews.value) AS PageViews
FROM your_analytics_table a 
     JOIN custom_operating_system_lookup b 
      ON a._experience.analytics.environment.operatingsystemID = b.operatingsystemid 
WHERE TIMESTAMP >= TO_TIMESTAMP('2018-01-01') AND TIMESTAMP <= TO_TIMESTAMP('2018-12-31')
GROUP BY OperatingSystem 
ORDER BY PageViews DESC
LIMIT 50;

Results

OperatingSystem PageViews
Windows 7 2781979.0
Windows XP 1669824.0
Windows 8 420024.0
Adobe AIR 315032.0
Windows Vista 173566.0
Mobile iOS 6.1.3 119069.0
Linux 56516.0
OSX 10.6.8 53652.0
Android 4.0.4 46167.0
Android 4.0.3 31852.0
Windows Server 2003 and XP x64 Edition 28883.0
Android 4.1.1 24336.0
Android 2.3.6 15735.0
OSX 10.6 13357.0
Windows Phone 7.5 11054.0
Android 4.3 9221.0

Deduplication

Query Service supports data deduplication, or the removal of duplicate rows from data. For more information on deduplication, please read the Query Service deduplication guide.

Next steps

By reading this document, you have been introduced to some important considerations when writing queries using Query Service. For more information on how to use the SQL syntax to write your own queries, please read the SQL syntax documentation.

For more samples of queries that can be used within Query Service, please read the guides on Adobe Analytics sample queries, Adobe Target sample queries, or ExperienceEvent sample queries.

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