File Formats

CSV

To read or write a CSV file, set File Format to CSV. The CSV format can be used in the following scenarios:

• Import files to a database or NoSQL.
• Export data from a database or NoSQL to files.

After selecting the CSV format, you can also configure the following optional sub-parameters:

1. Line Separator

2. Field Delimiter

3. Encoding Type

4. Use Quote Character

5. Use RE to Separate Fields

6. Use First Row as Header

7. File Size

JSON

1. JSON types supported by CDM: JSON object and JSON array
   • JSON object: A JSON file contains a single object or multiple objects separated/merged by rows.
     1. The following is a single JSON object:

        {
             "took" : 190,
             "timed_out" : false,
             "total" : 1000001,
             "max_score" : 1.0
         }

     2. The following are JSON objects separated by rows:

        {"took" : 188, "timed_out" : false, "total" : 1000003, "max_score" : 1.0 }
        {"took" : 189, "timed_out" : false, "total" : 1000004, "max_score" : 1.0 }

     3. The following are merged JSON objects:

        {
            "took": 190,
            "timed_out": false,
            "total": 1000001,
            "max_score": 1.0
         }
         {
            "took": 191,
            "timed_out": false,
            "total": 1000002,
            "max_score": 1.0
         }

   • JSON array: A JSON file is a JSON array consisting of multiple JSON objects.

     [{
           "took" : 190,
           "timed_out" : false,
           "total" : 1000001,
           "max_score" : 1.0
       },
       {
           "took" : 191,
           "timed_out" : false,
           "total" : 1000001,
           "max_score" : 1.0
       }]

2. JSON Reference Node

   Root node that records data. The data corresponding to the node is a JSON array. CDM extracts data from the array in the same mode. Use periods (.) to separate multi-layer nested JSON nodes.

3. Copying Data from a JSON File
   1. Example 1: Extract data from multiple objects that are separated or merged. A JSON file contains multiple JSON objects. The following gives an example:

       {
          "took": 190,
          "timed_out": false,
          "total": 1000001,
          "max_score": 1.0
       }
       {
          "took": 191,
          "timed_out": false,
          "total": 1000002,
          "max_score": 1.0
       }
       {
          "took": 192,
          "timed_out": false,
          "total": 1000003,
          "max_score": 1.0
       }

      To extract data from the JSON object and write data to the database in the following formats, set File Format to JSON and JSON Type to JSON object, and then map fields.

      took	timedOut	total	maxScore
      190	false	1000001	1.0
      191	false	1000002	1.0
      192	false	1000003	1.0

   2. Example 2: Extract data from the reference node. A JSON file contains a single JSON object, but the valid data is on a data node. The following gives an example:

      {
          "took": 190,
          "timed_out": false,
          "hits": {
              "total": 1000001,
              "max_score": 1.0,
              "hits": 
               [{
                  "_id": "650612",
                  "_source": {
                      "name": "tom",
                      "books": ["book1","book2","book3"]
                  }
               },
               {
                   "_id": "650616",
                   "_source": {
                       "name": "tom",
                       "books": ["book1","book2","book3"]
                   }
               },
             {
                   "_id": "650618",
                   "_source": {
                       "name": "tom",
                       "books": ["book1","book2","book3"]
                   }
               }]
           }
       }

      To write data to the database in the following formats, set File Format to JSON, JSON Type to JSON object, and JSON Reference Node to hits.hits, and then map fields.

      ID	SourceName	SourceBooks
      650612	tom	["book1","book2","book3"]
      650616	tom	["book1","book2","book3"]
      650618	tom	["book1","book2","book3"]

   3. Example 3: Extract data from the JSON array. A JSON file is a JSON array consisting of multiple JSON objects. The following gives an example:

      [{
            "took" : 190,
            "timed_out" : false,
            "total" : 1000001,
            "max_score" : 1.0
        },
        {
            "took" : 191,
            "timed_out" : false,
            "total" : 1000002,
            "max_score" : 1.0
        }]

      To write data to the database in the following formats, set File Format to JSON and JSON Type to JSON array, and then map fields.

      took	timedOut	total	maxScore
      190	false	1000001	1.0
      191	false	1000002	1.0

   4. Example 4: Configure a converter when parsing the JSON file. On the premise of example 2, to add the hits.max_score field to all records, that is, to write the data to the database in the following formats, perform the following operations:

      ID	SourceName	SourceBooks	MaxScore
      650612	tom	["book1","book2","book3"]	1.0
      650616	tom	["book1","book2","book3"]	1.0
      650618	tom	["book1","book2","book3"]	1.0

      Set File Format to JSON, JSON Type to JSON object, and JSON Reference Node to hits.hits, and then create a converter.

      1. Click to add a field.
         Figure 2 Adding a field
         
      2. Click to create a converter for the new field.
         Figure 3 Creating a field converter
         
      3. Set Converter to Expression conversion, enter "1.0" in the Expression text box, and click Save.
         Figure 4 Configuring a field converter
         

Binary

If you want to copy files between file systems, you can select the binary format. The binary format delivers the optimal rate and performance in file transfer, and does not require field mapping.

• Directory structure for file transfer

  CDM can transfer a single file or all files in a directory at a time. After the files are transferred to the migration destination, the directory structure remains unchanged.

• Migrating incremental files

  When you use CDM to transfer files in binary format, configure Duplicate File Processing Method at the migration destination for incremental file migration. For details, see Incremental File Migration.

  During incremental file migration, set Duplicate File Processing Method to Skip. If new files exist at the migration source or a failure occurs during the migration, run the job again, so that the migrated files will not be migrated repeatedly.

• Write to Temporary File

  When migrating files in binary format, you can specify whether to write the files to a temporary file at the migration destination. If this parameter is specified, the file is written to a temporary file during file replication. After the file is successfully migrated, run the rename or move command to restore the file at the migration destination.

• Generate MD5 Hash Value

  An MD5 hash value is generated for each transferred file, and the value is recorded in a new .md5 file. You can specify the directory where the MD5 value is generated.

Common parameters

• Source File Processing Method

  After a file is copied successfully, CDM can perform operations on the source file, including renaming the file, deleting the file, and performing no operation on the file.

• Start Job by Marker File

  In automation scenarios, a scheduled task is configured on CDM to periodically read files from the migration source. However, files are being generated at the migration source. As a result, CDM reads data repeatedly or fails to read data from the migration source. You can specify the marker file for starting a job as ok.txt in the job parameters of the migration source. After the file is successfully generated at the migration source, the ok.txt file is generated in the file directory. In this way, CDM can read the complete file.

  In addition, you can set the suspension period. Within the suspension period, CDM periodically queries whether the marker file exists. If the file does not exist after the suspension period expires, the job fails.

  The marker file will not be migrated.

• Job Success Marker File

  After data is successfully migrated to a file system, an empty file is generated in the destination directory. You can specify the file name. Generally, this parameter is used together with Start Job by Marker File.

  Note that the file cannot be confused with the file to be transferred. For example, if the file to be transferred is finish.txt and the job success marker file is set to finish.txt, the two files will overwrite each other.

• Filter

  When using CDM to migrate files, you can specify a filter to filter files. Files can be filtered by wildcard character or time filter.

  • If you select Wildcard, CDM migrates only the paths or files that meet the filter condition.
  • If you select Time Filter, CDM migrates only the files modified after the specified time point.

  For example, the /table/ directory stores a large number of data table directories divided by day. DRIVING_BEHAVIOR_20180101 to DRIVING_BEHAVIOR_20180630 store all data of DRIVING_BEHAVIOR from January to June. To migrate only the table data of DRIVING_BEHAVIOR in March, set Source Directory/File to /table, Filter Type to Wildcard, and Path Filter to DRIVING_BEHAVIOR_201803*.

Solutions to File Format Problems

1. When data in a database is exported to a CSV file, if the data contains commas (,), the data in the exported CSV file is disordered.

   The following solutions are available:

   1. Specify a field delimiter.

      Use a character that does not exist in the database or a rare non-printable character as the field delimiter. For example, set Field Delimiter at the migration destination to %01. In this way, the exported field delimiter is \u0001. For details, see Table 1.

   2. Use the quote character.

      Set Use Quote Character to Yes at the migration destination. In this way, if the field in the database contains the field delimiter, CDM quotes the field using the quote character and write the field as a whole to the CSV file.

2. The data in the database contains line separators.

   Scenario: When you use CDM to export a table in the MySQL database (a field value contains the line separator \n) to a CSV file, and then use CDM to import the exported CSV file to MRS HBase, data in the exported CSV file is truncated.

   Solution: Specify a line separator.

   When you use CDM to export MySQL table data to a CSV file, set Line Separator at the migration destination to %01 (ensure that the value does not appear in the field value). In this way, the line separator in the exported CSV file is %01. Then use CDM to import the CSV file to MRS HBase. Set Line Separator at the migration source to %01. This avoids data truncation.