The CSV connector converts comma-separated values (CSV) files into XML and generates CSV files from XML.
XML is the primary format that CData Arc uses to manipulate data within a flow. Therefore, it is useful to convert CSV files into XML as a staging step for further processing in the flow, or to convert XML to a CSV file after the XML has been manipulated. Both of these operations can be accomplished with the CSV connector.
This section contains all of the configurable connector properties.
Settings related to the connector Id and description.
- Connector Id The static, unique identifier for the connector.
- Connector Type Displays the connector name and a description of what it does.
- Connector Description An optional field to provide a free-form description of the connector and its role in the flow.
Settings related to the core operation of the connector.
- Column headers present Whether the CSV file contains a row of headers providing names or context to the values in the file.
- Record Name The name of elements representing a row in the CSV file when converting to XML. You can use the following macros:
%ConnectorID%, %FilenameNoExt%, %RegexFilename:%, and %Header:%.
See Converting CSV to XML for more details.
Settings not included in the previous categories.
- Local File Scheme A scheme for assigning filenames to messages that are output by the connector. You can use macros in your filenames dynamically to include information such as identifiers and timestamps. For more information, see Macros.
- Processing Delay The amount of time (in seconds) by which the processing of files placed in the Input folder is delayed. This is a legacy setting. Best practice is to use a File connector to manage local file systems instead of this setting.
- Save to Sent Folder Check this to copy files processed by the connector to the Sent folder for the connector.
- Sent Folder Scheme Instructs the connector to group messages in the Sent folder according to the selected interval. For example, the Weekly option instructs the connector to create a new subfolder each week and store all messages for the week in that folder. The blank setting tells the connector to save all messages directly in the Sent folder. For connectors that process many messages, using subfolders helps keep messsages organized and improves performance.
- Log Level The verbosity of logs generated by the connector. When you request support, set this to Debug.
- Log Subfolder Scheme Instructs the connector to group files in the Logs folder according to the selected interval. For example, the Weekly option instructs the connector to create a new subfolder each week and store all logs for the week in that folder. The blank setting tells the connector to save all logs directly in the Logs folder. For connectors that process many transactions, using subfolders helps keep logs organized and improves performance.
- Log Messages Check this to have the log entry for a processed file include a copy of the file itself. If you disable this, you might not be able to download a copy of the file from the Input or Output tabs.
Miscellaneous settings are for specific use cases.
- Other Settings Enables you to configure hidden connector settings in a semicolon-separated list (for example,
setting1=value1;setting2=value2). Normal connector use cases and functionality should not require the use of these settings.
Settings related to the automatic processing of files by the connector.
- Send Whether messages arriving at the connector are automatically processed.
Settings related to the allocation of resources to the connector.
- Max Workers The maximum number of worker threads consumed from the threadpool to process files on this connector. If set, this overrides the default setting on the Settings > Automation page.
- Max Files The maximum number of files sent by each thread assigned to the connector. If set, this overrides the default setting on the Settings > Automation page.
サービスレベルでは、フロー内のコネクタが送受信すると予想される処理量を設定し、その量が満たされると予想される時間枠を設定できます。CData Arc は、サービスレベルが満たされていない場合にユーザーに警告するE メールを送信し、SLA を At Risk（危険） としてマークします。これは、サービスレベルがすぐに満たされない場合に Violated（違反） としてマークされることを意味します。これにより、ユーザーはサービスレベルが満たされていない理由を特定し、適切な措置を講じることができます。At Risk の期間内にサービスレベルが満たされなかった場合、SLA はViolated としてマークされ、ユーザーに再度通知されます。
- コネクタに個別の送信アクションと受信アクションがある場合は、ラジオボタンを使用してSLA に関連する方向を指定します。
- デフォルトでは、SLA は毎日有効です。これを変更するには、毎日のチェックをOFF にし、希望する曜日のチェックをON にします。
- 期間終了前にステータスを’At Risk’ に設定するタイミングを使用して、SLA がAt Risk としてマークされるようにします。
- デフォルトでは、通知はSLA が違反のステータスになるまで送信されません。これを変更するには、‘At Risk’ 通知を送信のチェックをON にします。
次の例は、月曜日から金曜日まで毎日1000ファイルを受信すると予想されるコネクタに対して構成されたSLA を示しています。1000ファイルが受信されていない場合、期間終了の1時間前にAt Risk 通知が送信されます。
Converting CSV to XML
When a CSV file is transformed into XML, the resulting XML has the following structure:
Each row (record) in the original file becomes a child of the root element Items. The name of all record elements is determined by the Record Name option set in Connector Settings. Each record element then has child elements corresponding to the values in each row of the input file.
Some CSV files include a line of header information that provides context to the values in the file. When the First line is header information setting is enabled, this header line is parsed, and the parsed headers are used as the element names for the value elements (the children of the record elements). Otherwise, the value elements are given generic names such as field_0, field_1, and so on.
Converting XML to CSV
To convert XML to a CSV file, the input XML must have a ‘flat’ structure. This means that, disregarding the Items root element, the depth of the XML structure is two. For example:
The XML is interpreted as follows:
- Children of the root element are treated as records (rows) in the resulting file
- Children of each record element are treated as the values in each row
If the First line is header information option is enabled, a header row is inserted into the resulting CSV file with the names of each value element to provide context to the values. In the example above, this header row would consist of title, year, and runtime.
CSV Transformation: Using the XML Map Connector
Many data transformation flows use the CSV connector in conjunction with the XML Map Connector.
Often, data enters an Arc flow in CSV format and should exit the flow in some other format (for example, a database insert, an EDI file, or an insert into a CRM or ERP data source), or vice versa. Arc uses a single streamlined approach to these data transformation requirements:
- Model the input format as XML
- Model the output format as XML
- Use the XML Map connector to map between the input XML and the output XML
Therefore, the CSV connector is commonly adjacent to an XML Map connector in the flow:
- When CSV files are the input to the flow, the CSV connector converts a CSV file to XML and then passes that XML off to the XML Map connector to be transformed
- When CSV files are the output from the flow, the CSV connector receives XML from the XML Map connector and converts it into a CSV file
The CSV connector includes an Upload Test File feature to simplify the process of mapping the XML that represents a CSV file.
Upload Test File
An XML Map connector requires a sample XML structure for both the mapping input/source and the mapping output/destination. The Upload Test File feature makes it easy to use the CSV connector to generate a Source or Destination XML template.
Navigate to the Input tab of the CSV connector, click the More button, and choose Upload Test File. Browse to a local CSV file to instruct the connector to generate an internal XML model of this sample file.
Then, when an XML Map connector is connected to this CSV connector in the flow (and the flow changes are saved), the XML Map connector detects this internal XML model and uses it as a source file (if the CSV connector is before the XML Map connector in the flow) or a destination file (if the CSV connector is after the XML Map connector in the flow).
Note: The structure of this test file should be representative of future files. In other words, all of the CSV files processed by the CSV connector (and then the XML Map connector) should have the same columns as your test file. You might need to set up multiple CSV connectors and multiple XML Map connectors to handle distinct CSV structures.
Using macros in file naming strategies can enhance organizational efficiency and contextual understanding of data. By incorporating macros into filenames, you can dynamically include relevant information such as identifiers, timestamps, and header information, providing valuable context to each file. This helps ensure that filenames reflect details important to your organization.
CData Arc supports these macros, which all use the following syntax:
|Evaluates to the ConnectorID of the connector.
|Evaluates to the file extension of the file currently being processed by the connector.
|Evaluates to the filename (extension included) of the file currently being processed by the connector.
|Evaluates to the filename (without the extension) of the file currently being processed by the connector.
|Applies a RegEx pattern to the filename of the file currently being processed by the connector.
|Evaluates to the value of a targeted header (
headername) on the current message being processed by the connector.
|Evaluates to the current datetime of the system in long-handed format (for example, Wednesday, January 24, 2024).
|Evaluates to the current datetime of the system in a yyyy-MM-dd format (for example, 2024-01-24).
|Evaluates to the current datetime of the system in the specified format (
format). See サンプル日付フォーマット for the available datetime formats
|Evaluates to the value of the specified vault item.
Some macros, such as %Ext% and %ShortDate%, do not require an argument, but others do. All macros that take an argument use the following syntax:
Here are some examples of the macros that take an argument:
- %Header:headername%: Where
headernameis the name of a header on a message.
- %Header:mycustomheader% resolves to the value of the
mycustomheaderheader set on the input message.
- %Header:ponum% resolves to the value of the
ponumheader set on the input message.
- %RegexFilename:pattern%: Where
patternis a regex pattern. For example,
%RegexFilename:^([\w][A-Za-z]+)%matches and resolves to the first word in the filename and is case insensitive (
- %Vault:vaultitem%: Where
vaultitemis the name of an item in the vault. For example,
%Vault:companyname%resolves to the value of the
companynameitem stored in the vault.
- %DateFormat:format%: Where
formatis an accepted date format (see サンプル日付フォーマット for details). For example,
%DateFormat:yyyy-MM-dd-HH-mm-ss-fff%resolves to the date and timestamp on the file.
You can also create more sophisticated macros, as shown in the following examples:
- Combining multiple macros in one filename:
- Including text outside of the macro:
- Including text within the macro:
In addition to the Operations provided with Arc, connectors can provide operations that extend functionality into ArcScript.
These connector operations can be called just like any other ArcScript operation, except for two details:
- They must be called through the
- They must include an auth token.
For example, calling a connector operation using both of these rules might look something like this:
<arc:set attr="in.myInput" value="myvalue" />
<arc:call op="connector.rsc/opName" authtoken="admin:1j9P8v8b9K0x6g5R5t7k" in="in" out="out">
<!-- handle output from the op here -->
Operations specific to the functionality of the CSV connector are listed below.
Loops over every record in a specified CSV file or string. See Special Formatters for more details.
- file: The path to the CSV file.
- data: If the CSV data exists as a string rather than stored in a CSV file, use this parameter instead of file.
- columns: The comma-separated list of columns to include in the output (if unspecified, all columns are included).
- requireheader: By default, the first row of data is interpreted as column headers; pass false to this parameter to use generic column names (for example, c1, c2, c3).
Any script in a csvListRecords operation executes multiple times: once for each record/row in the input CSV file/data. Within the operation, individual CSV values are accessible using the csv formatter. This formatter takes a column name as a parameter, and outputs the value in that column for the current record.
For example, imagine the CSV input data contains a set of items purchased in an order, and the name of the item is held in the ItemName column. The following script generates XML containing each ItemName value in an Item element: