Configure an Ingestion Step Using QuickStart
Before you begin
You need:
- Java SE JDK 8 or later
- MarkLogic Server (See Version Compatibility.)
- Chrome or Firefox for QuickStart
Procedure
- Navigate to the flow definition of the flow you want.
- In QuickStart's navigation bar, click Flows.
- In the Manage Flows table, search for the row containing the flow.
Tip: To make your search easier, you can sort the table by one of the columns.
- Click the flow's name.
- In the flow sequence, click the summary box of the ingestion step to configure.
The step detail panel is displayed below the flow sequence panel.
- Configure the ingestion.
Field Description Source Directory Path The location of your source files. Source Format The format of your source files: Text, JSON, XML, Binary, or Delimited Text. Default is JSON. Field Separator (Displayed if Source Format is Delimited Text.) The character used separate fields in a delimited text file. Target Format The format of the processed record: Text, JSON, XML, or Binary. Default is JSON. Target Permissions The comma-separated roles required to access the ingested data. Target URI Replacement A comma-separated list of replacements used to customize the URIs of the ingested records. The list is comprised of regular expression patterns and their replacement strings in the format
pattern,'string',pattern,'string',...
. The replacement strings must be enclosed in single quotes.For example, if the original URI is in the form "/foo/bar/filename", you can customize it to be "/mydir/filename" using the following comma-separated list:
/foo/bar,'/mydir'
Java's regular expression language is supported.
If Source File Type is set to
CSV
, the substitution is based on the absolute path of the parent folder; otherwise, the absolute path of the input file. For example, if the Windows path is c:\path\filename, the substitution is based on /c/path/filename.Target URI Preview The URI of an example ingested document. MLCP Command The command that you can copy and paste to a command line to ingest documents via MLCP, using your step settings as parameter values.