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The Publisher Query Language (PQL) Developer's Guide

PQL syntax and usage

PQL is a SQL-like language for querying for objects. The PQL syntax is similar to that of SQL, with a few differences described here. This section describes the PQL syntax, and how to use it to filter various object types.

The PQL syntax can be summarized as follows:

[WHERE <condition> {[AND | OR] <condition> ...}]
[ORDER BY <property> [ASC | DESC]]
[LIMIT {[<offset>,] <count>} | {<count> OFFSET <offset>}]

<condition> := <property> { = | != } <value>
<condition> := <property> { = | != } <bind variable>
<condition> := <property> IN <list>
<condition> := NOT <property> IN <list>
<condition> := <property> LIKE <wildcard%match>
<condition> := <property> IS NULL
<bind variable> := :<name>

Notes:

  • PQL keywords are not case sensitive.
  • Strings are escaped automatically when used in bind parameters. Otherwise:
    • For a string within single quotes (apostrophes), escape any additional apostrophe by writing it as a pair of single quotes.

      Example: "WHERE name = 'Company''s name'"

Keywords (case-insensitive)

  • WHERE - Expresses a set of zero or more conditions, optionally joined using AND or OR phrases. You can bundle AND or OR phrases with parentheses. Executing the query "" (empty string) returns everything.

    Examples: WHERE width = 728 ;   WHERE width = 728 AND height = 90 ;  WHERE (width = 728 AND height = 90) OR id IN (5008, 8745, 3487)

  • OR - Joins multiple conditions, only one of which must be true. If you want to check for any of several values for a single property, consider using an IN clause.

    Example: WHERE width = 728 OR height = 90

  • AND - Joins multiple conditions that must all be satisfied using the AND clause.

    Example: WHERE type = 'AGENCY' AND name IN ('CompanyNameA', 'CompanyNameB')

  • ORDER BY - Sorts the returned results in either ascending (ASC where 'A' is first) or descending (DESC where 'A' is last) order. If the direction is not specified, it defaults to ASC. If this clause is not included the default is ASC on the first field.

    Example: WHERE id IN (5008, 8745, 3487) ORDER BY id

  • LIMIT - The number of results to return. The LIMIT can also include an <offset>, which is how many rows from the start to offset your result set.

    Examples (both examples return the same result set): WHERE type = 'AGENCY' LIMIT 50 OFFSET 50 ;   WHERE type = 'AGENCY' LIMIT 50,50

  • OFFSET - The offset into the result set to begin returning values. Use this to page through results.

    Example (returns results 51-100): WHERE type = 'AGENCY' LIMIT 50 OFFSET 50.

  • <property> - One of the properties exposed by the object. Each object exposes different properties that you can filter by, using PQL; you usually cannot filter on all properties supported by an object, so check the list below to see which properties support PQL queries. For example, the creative properties you can filter by include id, name, width, and height.
  • <value> - String values should be quoted with a single (') quotation mark. Number values can be quoted or unquoted. Wildcards are not supported.
  • IN - Compares the value of a property to each item in a list; if any one matches, it is a positive match. The IN operator is equivalent to many = queries, one for each value, that are ORed together. The values are specified as a comma-separated list of values, enclosed in parentheses: (a, b, c). All of the values in the list are evaluated.

    Example: WHERE name IN ('CompanyNameA', 'CompanyNameB')

  • NOT IN - Compares the value of a property to each item in a list; if none match, it is a positive match. The NOT IN operator is equivalent to many != queries, one for each value, that are ORed together. The values are specified as a comma-separated list of values, enclosed in parentheses: (a, b, c). All of the values in the list are evaluated.

    Example: WHERE NOT name IN ('CompanyNameA', 'CompanyNameB')

  • LIKE - Enables you to query for objects using partial and wildcard string matching.

    Example: WHERE name LIKE 'startswith%'

  • IS NULL - Enables you to query for objects with an undefined property value. The classic example of this is querying for the root AdUnit by querying for an AdUnit with a null parent ID.

    Example: WHERE parentId IS NULL.

  • <bind variable> - You can use Value objects in place of hard-coded <value> values in your PQL query. A bind variable is referred to in PQL using a string name without spaces, starting with a : (colon).

    Example (Creates a query and enters two variables in place of hard-coded id and status property values):

    // Create two mapped parameters: id and status
    String_ValueMapEntry[] values = new String_ValueMapEntry[2];
    values[0] = new String_ValueMapEntry("id", new NumberValue(null, "123"));
    values[1] = new String_ValueMapEntry("status", new TextValue(null, "APPROVED"));
    
    // Create our statement and map our bind variables
    Statement statement = new Statement();
    statement.setQuery("WHERE id = :id AND status = :status LIMIT 500");
    statement.setValues(values);
  • DateTime fields - You can filter by date and time by assigning a DateTime value to a bind variable, or by using a string formatted according to ISO 8601.
    // Create two mapped parameters: id and status
    String_ValueMapEntry[] values = new String_ValueMapEntry[1];
    values[0] = new String_ValueMapEntry("startDateTime", new DateTimeValue(null, dateTime));
    
    // Create our statement and map our bind variables
    Statement statement = new Statement();
    statement.setQuery("WHERE endDateTime < '2012-01-01T00:00:00' AND startDateTime > :startDateTime LIMIT 500");
    statement.setValues(values);

Fetching match tables with PQL

Match tables provide a lookup mechanism for the raw values contained within data transfer files, allowing you to match ad serving information (such as ad unit or line item) to pre-assigned values stored in the database.

If you're running reports through the ReportService or with Data Transfer reports, you might want to supplement your report data with additional fields. For example, with a report that has the dimension LINE_ITEM_ID or with a data transfer event that has the field LineItemId, you can create a match table that includes each line item's start date, end date, type, status, and other useful attributes.

There are several ways to accomplish this matching functionality:

  1. An efficient approach is to use any of the available PublisherQueryLanguageService tables.
  2. If your client library supports it, you can use a built-in utility function to access PQL tables, like the Python example below.
  3. If there is no PQL table for the entity you need, you can go through that entity's service directly, such as the OrderService.

Python


  1. Set up a report query

    Start by creating a report job, specifying your report parameters such as dimensions, columns, and date range.

    # Set the start and end dates of the report to run (past 8 days).
    end_date = date.today()
    start_date = end_date - timedelta(days=8)
    
    # Create report job.
    report_job = {
        'reportQuery': {
            'dimensions': ['LINE_ITEM_ID', 'LINE_ITEM_NAME'],
            'columns': ['AD_SERVER_IMPRESSIONS', 'AD_SERVER_CLICKS',
                        'AD_SERVER_CTR', 'AD_SERVER_CPM_AND_CPC_REVENUE',
                        'AD_SERVER_WITHOUT_CPD_AVERAGE_ECPM'],
            'dateRangeType': 'CUSTOM_DATE',
            'startDate': start_date,
            'endDate': end_date
        }
    }
        
  2. Download the report
    # Initialize a DataDownloader.
    report_downloader = client.GetDataDownloader(version='v201708')
    
    try:
      # Run the report and wait for it to finish.
      report_job_id = report_downloader.WaitForReport(report_job)
    except errors.DfpReportError, e:
      print 'Failed to generate report. Error was: %s' % e
    
    with tempfile.NamedTemporaryFile(
        suffix='.csv.gz', mode='wb', delete=False) as report_file:
      # Download report data.
      report_downloader.DownloadReportToFile(
          report_job_id, 'CSV_DUMP', report_file)
        
  3. Download data from the Line_Item PQL table

    To match your report with additional line item data, you can use the Line_Item PQL table.

    # Create a PQL query to fetch the line item data
    line_items_pql_query = ('SELECT Id, LineItemType, Status FROM LineItem')
    
    # Download the response from PQL select statement
    line_items = report_downloader.DownloadPqlResultToList(line_items_pql_query)
        
  4. Join report data with line item data

    This example uses the pandas library since it makes working with tabular data much easier. Here, it's used to join the report data with the PQL data to make a match table.

    # Use pandas to join the two csv files into a match table
    report = pandas.read_csv(report_file.name)
    line_items = pandas.DataFrame(data=line_items[1:], columns=line_items[0])
    merged_result = pandas.merge(report, line_items,
                                 left_on='Dimension.LINE_ITEM_ID', right_on='id')
    merged_result.to_csv('~/complete_line_items_report.csv', index=False)
        

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