You can import Media Campaign, Paid Search Campaign, Site Campaign, User Audience Segment Map, Segment Mapping File or Dissent Lists from Salesforce DMP (Krux) into Treasure Data.
This data connector is in Beta. For more information, contact support@treasuredata.com. |
Basic knowledge of Treasure Data, including the Toolbelt and JavaScript SDK
S3 credential with access key id and secret access key.
Client name from Salesforce DMP
This integration has two parts:
Cookie-syncing between Salesforce DMP and Treasure Data CDP: Required to create a mapping between Salesforce DMP ID and Treasure Data ID's td_global_id & td_client_id
Data import from Salesforce DMP into Treasure Data CDP: There are various data feeds that can be brought in. For the purpose of data enrichment, the key file is the mapping between Segment IDs and their names.
You must first set up Treasure Data's JavaScript tag as documented in Getting Started with Website Tracking under "Setting up website tracking and install the Treasure Data JavaScript SDK".
Next, add the following piece of code into the website where Salesforce DMP's tag is already installed.
(function(window, document, td){
var kruxProperties = {};
for ( var k in window.localStorage ) {
if ( k.startsWith('<YOUR KRUX PREFIX HERE>') ) {
kruxProperties[k] = window.localStorage.getItem(k)
}
}
td.trackEvent('<TD TABLE NAME FOR TRACKING KRUX ID/TD ID map>', kruxProperties);
var successCb = function(tdGlobalId) {
// This is createImage in TDWrapper
var el = document.createElement('img');
el.src = '//beacon.krxd.net/usermatch.gif?partner=treasuredata&partner_uid=' + tdGlobalId;
el.width=1;
el.height=1;
el.style.display='none';
document.body.appendChild(el);
}
function isSafari() {
var ua = window.navigator.userAgent.toLowerCase();
return ua.indexOf('safari') !== -1 && ua.indexOf('chrome') === -1 && ua.indexOf('edge') === -1;
}
if ( isSafari() ) {
// TODO: Safari-specific handling due to ITP 2.1
} else {
td.fetchGlobalID(successCb, function(err) { console.log(err) });
}
})(window, document, td);
|
The preceding code sample does not include cookie-syncing for Safari browsers. Safari's Intelligent Tracking Prevention (ITP) feature makes 3rd party domain cookie-based visitor identification less reliable. We are actively planning a solution around this. |
Go to Integrations Hub > Catalog and search and select Salesforce DMP.
Select Create. You are creating an authenticated connection.
The following dialog opens.
Edit the client name, access key id and secret access key that you retrieved from Salesforce DMP.
Select Continue.
Name your new Salesforce DMP Connection. Select Done.
After creating the authenticated connection, you are automatically taken to the Authentications tab. Look for the connection you created and select New Source.
Specify the data that you want to import:
Segment Mapping File
User Audience Segment Map
Media Campaign, Paid Search Campaign, Site Campaign or Dissent Lists
For the Source, choose Segment Mapping File.
For the Source, choose User Audience Segment Map.
Parameters:
Import Date: Import data created from this date.
For the Source, choose Media Campaign, Paid Search Campaign, Site Campaign or Dissent Lists.
Parameters:
Start Date: Import data that has been created since this date.
End Date: Import data that has been created up to this date.
Incremental Loading: When importing data based on a schedule, the time window of the fetched data automatically shifts forward on each run. For example, if you specify the initial start date as January 1 and end date as January 10, the first run fetches data from January 1 to January 10, the second run fetches from January 11 to January 20, and so on.
You’ll see a preview of your data. To make changes, select Advanced Settings, otherwise select Next.
You can specify the following parameters:
Maximum retry times. Specifies the maximum retry times for each API call.
Type: number Default: 7 |
Initial retry interval millisecond. Specifies the wait time for the first retry.
Type: number Default: 1000 |
Maximum retry interval milliseconds. Specifies the maximum time between retries.
Type: number Default: 120000 |
Choose existing ones or create a new database and table.
Create a new database and give your database a name. Complete similar steps for Create new table.
Select whether to append records to an existing table or replace your existing table.
If you want to set a different partition key seed rather than use the default key, you can specify one using the popup menu.
In the When tab, you can specify one-time transfer, or schedule an automated recurring transfer.
Parameters
Once now: set one time job.
Repeat…
Schedule: accepts these three options: @hourly, @daily and @monthly and custom cron.
Delay Transfer: add a delay of execution time.
TimeZone: supports extended timezone formats like ‘Asia/Tokyo’.
Name your Transfer and select Done to start.
After your transfer has run, you can see the results of your transfer in the Databases tab.
You can use the TD Console to configure your connection.
Install the newest TD Toolbelt.
The configuration file includes an in: section where you specify what comes into the connector from Salesforce DMP and an out: section where you specify what the connector puts out to the database in Treasure Data. For more details on available out modes, see the Appendix.
The following example shows how to specify import Media Campaign, without incremental scheduling.
in: type: krux_dmp access_key_id: xxxxxxxxxxx secret_access_key: xxxxxxxxxxx client_name: xxxxxxxxxxx target: mc start_date: 2019-01-17 end_date: 2019-01-27 incremental: falseout: mode: append |
The following example shows how to specify import Media Campaign, with incremental scheduling.
in: type: krux_dmp access_key_id: xxxxxxxxxxx secret_access_key: xxxxxxxxxxx client_name: xxxxxxxxxxx target: mc start_date: 2019-01-17 end_date: 2019-01-27 incremental: trueout: mode: append |
The following example shows how to specify import Paid Search Campaign, without incremental scheduling.
in: type: krux_dmp access_key_id: xxxxxxxxxxx secret_access_key: xxxxxxxxxxx client_name: xxxxxxxxxxx target: psc start_date: 2019-01-17 end_date: 2019-01-27 incremental: falseout: mode: append |
The following example shows how to specify import Paid Search Campaign, with incremental scheduling.
in: type: krux_dmp access_key_id: xxxxxxxxxxx secret_access_key: xxxxxxxxxxx client_name: xxxxxxxxxxx target: psc start_date: 2019-01-17 end_date: 2019-01-27 incremental: trueout: mode: append |
The following example shows how to specify import Site Campaign, without incremental scheduling.
in: type: krux_dmp access_key_id: xxxxxxxxxxx secret_access_key: xxxxxxxxxxx client_name: xxxxxxxxxxx target: sc start_date: 2019-01-17 end_date: 2019-01-27 incremental: falseout: mode: append |
The following example shows how to specify import Site Campaign, with incremental scheduling.
in: type: krux_dmp access_key_id: xxxxxxxxxxx secret_access_key: xxxxxxxxxxx client_name: xxxxxxxxxxx target: sc start_date: 2019-01-17 end_date: 2019-01-27 incremental: trueout: mode: append |
The following example shows how to specify import Dissent Lists, without incremental scheduling.
in: type: krux_dmp access_key_id: xxxxxxxxxxx secret_access_key: xxxxxxxxxxx client_name: xxxxxxxxxxx target: dl start_date: 2019-01-17 end_date: 2019-01-27 incremental: falseout: mode: append |
The following example shows how to specify import Dissent Lists, with incremental scheduling.
in: type: krux_dmp access_key_id: xxxxxxxxxxx secret_access_key: xxxxxxxxxxx client_name: xxxxxxxxxxx target: dl start_date: 2019-01-17 end_date: 2019-01-27 incremental: trueout: mode: append |
The following example shows how to specify import User Audience Segment Map.
in: type: krux_dmp access_key_id: xxxxxxxxxxx secret_access_key: xxxxxxxxxxx client_name: xxxxxxxxxxx target: uasm import_date: 2019-01-17out: mode: append |
The following example shows how to specify import Segment Mapping File.
in: type: krux_dmp access_key_id: xxxxxxxxxxx secret_access_key: xxxxxxxxxxx client_name: xxxxxxxxxxx target: smfout: mode: append |
You can preview data to be imported using the command td connector:preview.
$ td connector:preview load.yml |
You use td connector:issue to execute the job.
You must specify the database and table where you want to store the data before you execute the load job. Ex td_sample_db, td_sample_table
$ td connector:issue load.yml \ --database td_sample_db \ --table td_sample_table \ --time-column date_time_column |
It is recommended to specify --time-column option, because Treasure Data’s storage is partitioned by time. If the option is not given, the data connector selects the first long or timestamp column as the partitioning time. The type of the column, specified by --time-column, must be either of long or timestamp type (use Preview results to check for the available column name and type. Generally, most data types have a last_modified_date column).
If your data doesn’t have a time column, you can add the column by using the add_time filter option. See details at add_time filter plugin.
td connector:issue assumes you have already created a database (sample_db) and a table (sample_table). If the database or the table do not exist in TD, td connector:issue will fail. Therefore, you must create the database and table manually or use --auto-create-table with td connector:issue to automatically create the database and table.
$ td connector:issue load.yml \ --database td_sample_db \ --table td_sample_table \ --time-column date_time_column \ --auto-create-table |
From the command line, submit the load job. Processing might take a couple of hours depending on the data size.
You can schedule periodic data connector execution for periodic Media Campaign, Paid Search Campaign, Site Campaign import. We configure our scheduler carefully to ensure high availability. By using this feature, you no longer need a cron daemon on your local data center.
Scheduled execution supports configuration parameters that control the behavior of the data connector during its periodic attempts to fetch data from Salesforce DMP:
incremental This configuration is used to control the load mode, which governs how the data connector fetches data from Salesforce DMP based on one of the native timestamp fields associated with each object.
columns This configuration is used to define a custom schema for data to be imported into Treasure Data. You can define only columns that you are interested in here but make sure they exist in the object that you are fetching. Otherwise, these columns aren’t available in the result.
last_record This configuration is used to control the last record from the previous load job. It requires the object include a key for the column name and a value for the column’s value. The key needs to match the Salesforce DMP Data column name.
See How Incremental Loading works for details and examples.
A new schedule can be created using the td connector:create command. The name of the schedule, cron-style schedule, the database and table where their data will be stored, and the data connector configuration file are required.
The `cron` parameter accepts these options: `@hourly`, `@daily` and `@monthly`.
By default, schedule is setup in UTC timezone. You can set the schedule in a timezone using -t or --timezone option. The `--timezone` option only supports extended timezone formats like 'Asia/Tokyo', 'America/Los_Angeles' etc. Timezone abbreviations like PST, CST are *not* supported and may lead to unexpected schedules. |
$ td connector:create \
daily_import \
"10 0 * * *" \
td_sample_db \
td_sample_table \
load.yml
|
It’s also recommended to specify the --time-column option, since Treasure Data’s storage is partitioned by time.
$ td connector:create \
daily_import \
"10 0 * * *" \
td_sample_db \
td_sample_table \
load.yml \
--time-column created_at |
You can see the list of scheduled entries by entering the command td connector:list.
$ td connector:list
+--------------+------------+----------+-------+--------------+-----------------+--------------------------------------------+
| Name | Cron | Timezone | Delay | Database | Table | Config |
+--------------+------------+----------+-------+--------------+-----------------+--------------------------------------------+
| daily_import | 10 0 * * * | UTC | 0 | td_sample_db | td_sample_table | {"in"=>{"type"=>"krux_dmp", |
+--------------+------------+----------+-------+--------------+-----------------+--------------------------------------------+ |
td connector:show shows the execution setting of a schedule entry.
% td connector:show daily_import Name : daily_import Cron : 10 0 * * * Timezone : UTC Delay : 0 Database : td_sample_db Table : td_sample_table Config ---in: type: krux_dmp access_key_id: xxxxxxxxxxx secret_access_key: xxxxxxxxxxx client_name: xxxxxxxxxxx target: mc start_date: 2019-01-17 end_date: 2019-01-27 incremental: true |
td connector:history shows the execution history of a schedule entry. To investigate the results of each individual execution, use td job <jobid>.
% td connector:history daily_import +--------+---------+---------+--------------+-----------------+----------+---------------------------+----------+ | JobID | Status | Records | Database | Table | Priority | Started | Duration | +--------+---------+---------+--------------+-----------------+----------+---------------------------+----------+ | 578066 | success | 10000 | td_sample_db | td_sample_table | 0 | 2019-03-28 00:10:05 +0000 | 160 | | 577968 | success | 10000 | td_sample_db | td_sample_table | 0 | 2019-03-27 00:10:07 +0000 | 161 | | 577914 | success | 10000 | td_sample_db | td_sample_table | 0 | 2019-03-26 00:10:03 +0000 | 152 | | 577872 | success | 10000 | td_sample_db | td_sample_table | 0 | 2019-03-25 00:10:04 +0000 | 163 | | 577810 | success | 10000 | td_sample_db | td_sample_table | 0 | 2019-03-24 00:10:04 +0000 | 164 | | 577766 | success | 10000 | td_sample_db | td_sample_table | 0 | 2019-03-23 00:10:04 +0000 | 155 | | 577710 | success | 10000 | td_sample_db | td_sample_table | 0 | 2019-03-22 00:10:05 +0000 | 156 | | 577610 | success | 10000 | td_sample_db | td_sample_table | 0 | 2019-03-21 00:10:04 +0000 | 157 | +--------+---------+---------+--------------+-----------------+----------+---------------------------+----------+ 8 rows in set |
td connector:delete removes the schedule.
$ td connector:delete daily_import |
You can specify file import mode in the out section of the load.yml file.
The out: section controls how data is imported into a Treasure Data table.
For example, you may choose to append data or replace data in an existing table in Treasure Data.
Output modes are ways to modify the data as the data is placed in Treasure Data.
Append (default): Records are appended to the target table.
Replace (available In td 0.11.10 and later): Replaces data in the target table. Any manual schema changes made to the target table remain intact.
Examples:
in: ... out: mode: append |
in: ... out: mode: replace |
Incremental loading uses the last imported date of files to load records monotonically, inserting or updating files after the most recent execution.
At the first execution, this connector loads all files matching the Filename Regex and Modified After. If incremental : true is set, the latest modified DateTime will be saved as new Modified After value.
Example:
Import folder contains files:
+--------------+--------------------------+
| Filename | Last update |
+--------------+--------------------------+
| File0001.csv | 2019-05-04T10:00:00.123Z |
| File0011.csv | 2019-05-05T10:00:00.123Z |
| File0012.csv | 2019-05-06T10:00:00.123Z |
| File0013.csv | 2019-05-07T10:00:00.123Z |
| File0014.csv | 2019-05-08T10:00:00.123Z |
|
Filename Regex: File001.*.csv
Modified After: 2019-05-01T10:00:00.00Z
Then the files: File0011.csv, File0012.csv, File0013.csv and File0014.csv are imported as they match the Filename Regex, and all having the last update > 2019-05-01T10:00:00.00Z.
After the job finished, new Modified After = 2019-05-08T10:00:00.123Z is saved.
At the next execution, only files having last update > 2019-05-08T10:00:00.123Z are imported.
Example:
Import folder has newly updated and added files:
+--------------+--------------------------+
| Filename | Last update |
+--------------+--------------------------+
| File0001.csv | 2019-05-04T10:00:00.123Z |
| File0011.csv | 2019-05-05T10:00:00.123Z |
| File0012.csv | 2019-05-06T10:00:00.123Z |
| File0013.csv | 2019-05-09T10:00:00.123Z |
| File0014.csv | 2019-05-08T10:00:00.123Z |
| File0015.csv | 2019-05-09T10:00:00.123Z |
|
Filename Regex: File001.*.csv
Modified After: 2019-05-08T10:00:00.123Z
Then only files: File0013.csv and File0015.csv are imported.