The SYSCS_UTIL.UPSERT_DATA_FROM_FILE system procedure imports data to update an existing record or create a new record in your database. You can choose to import all or a subset of the columns from the input data into your database using the insertColumnList parameter.

This procedure has been deprecated; you can still use it in the current release, but Splice Machine strongly recommends using the more performant SYSCS_UTIL.MERGE_DATA_FROM_FILE system procedure instead.

After a successful import completes, a simple report displays, showing how many files were imported, and how many record imports succeeded or failed.

This procedure is one of several built-in system procedures provided by Splice Machine for importing data into your database. See our Best Practices: Ingestions chapter for help with selecting the right process for your situation.


               insertColumnList | null,
               columnDelimiter | null,
               characterDelimiter | null,
               timestampFormat | null,
               dateFormat | null,
               timeFormat | null,
               badRecordDirectory | null,
               oneLineRecords | null,
               charset | null


The following table summarizes the parameters used by SYSCS_UTIL.UPSERT_DATA_FROM_FILE and other Splice Machine data importation procedures. Each parameter name links to a more detailed description in our Ingestion Parameter Values.

Parameter Description Example Value
schemaName The name of the schema of the table into which to import. SPLICE
tableName The name of the table into which to import. playerTeams

The names, in single quotes, of the columns to import. If this is null, all columns are imported.

The individual column names in the insertColumnList do not need to be double-quoted, even if they contain special characters. However, if you do double-quote any column name, you must double-quote all of the column names.


Either a single file or a directory. If this is a single file, that file is imported; if this is a directory, all of the files in that directory are imported. You can import compressed or uncompressed files.

On a cluster, the files to be imported MUST be on S3, HDFS (or MapR-FS). If you're using our Database Service product, files can only be imported from S3.

See the Configuring an S3 Bucket for Splice Machine Access topic for information about accessing data on S3.



columnDelimiter The character used to separate columns, Specify null if using the comma (,) character as your delimiter. '|', '\t'
characterDelimiter The character used to delimit strings in the imported data. '"', ''''

The format of timestamps stored in the file. You can set this to null if there are no time columns in the file, or if the format of any timestamps in the file match the Java.sql.Timestamp default format, which is: "yyyy-MM-dd HH:mm:ss".

All of the timestamps in the file you are importing must use the same format.

'yyyy-MM-dd HH:mm:ss.SSZ'

dateFormat The format of datestamps stored in the file. You can set this to null if there are no date columns in the file, or if the format of any dates in the file match pattern: "yyyy-MM-dd". yyyy-MM-dd
timeFormat The format of time values stored in the file. You can set this to null if there are no time columns in the file, or if the format of any times in the file match pattern: "HH:mm:ss". HH:mm:ss
badRecordsAllowed The number of rejected (bad) records that are tolerated before the import fails. If this count of rejected records is reached, the import fails, and any successful record imports are rolled back. Specify 0 to indicate that no bad records are tolerated, and specify -1 to indicate that all bad records should be logged and allowed. 25

The directory in which bad record information is logged. Splice Machine logs information to the <import_file_name>.bad file in this directory; for example, bad records in an input file named foo.csv would be logged to a file named badRecordDirectory/foo.csv.bad.

On a cluster, this directory MUST be on S3, HDFS (or MapR-FS). If you're using our Database Service product, files can only be imported from S3.

oneLineRecords A Boolean value that specifies whether (true) each record in the import file is contained in one input line, or (false) if a record can span multiple lines. true
charset The character encoding of the import file. The default value is UTF-8. null


SYSCS_UTIL.UPSERT_DATA_FROM_FILE displays a summary of the import process results that looks like this:

rowsImported   |failedRows   |files   |dataSize   |failedLog
94             |0            |1       |4720       |NONE

This procedure also logs rejected record activity into .bad files in the badRecordDirectory directory; one file for each imported file.

Importing and Updating Records

What distinguishes SYSCS_UTIL.UPSERT_DATA_FROM_FILE from the similar  SYSCS_UTIL.IMPORT_DATA and  SYSCS_UTIL.SYSCS_MERGED_DATA_FROM_FILE procedures is how each works with these specific conditions:

  • You are importing only a subset of data from the input data into your table, either because the table contains less columns than does the input file, or because you’ve specified a subset of the columns in your insertColumnList parameter.
  • Inserting and updating data in a column with generated values.
  • Inserting and updating data in a column with default values.
  • Handling of missing values.

The Ingestion Parameters topic describes how each of these conditions is handled by the different system procedures.

Record Import Failure Reasons

When upserting data from a file, the input file you generate must contain:

  • the columns to be changed
  • all NON_NULL columns

Typical reasons for a row (record) import to fail include:

  • Improper data expected for a column.
  • Improper number of columns of data.
  • A primary key violation:  SYSCS_UTIL.UPSERT_DATA_FROM_FILE will only work correctly if the table into which you are inserting/updating has primary keys.

A few important notes:

  • Splice Machine advises you to run a full compaction (with the SYSCS_UTIL.SYSCS_PERFORM_MAJOR_COMPACTION_ON_TABLE system procedure) after importing large amounts of data into your database.

  • On a cluster, the files to be imported MUST be on S3, HDFS (or MapR-FS), as must the badRecordDirectory directory. If you’re using our Database Service product, files can only be imported from S3.

    In addition, the files must be readable by the hbase user, and the badRecordDirectory directory must be writable by the hbase user, either by setting the user explicity, or by opening up the permissions; for example:

    sudo -su hdfs hadoop fs -chmod 777 /badRecordDirectory


This section presents a couple simple examples.

The Best Practics: Importing Flat Files topic contains a more extensive set of examples.

Example 1: Updating our doc examples player data

This example shows the UPSERT_DATA call used to update the Players in our documentation examples database:

    'ID, Team, Name, Position, DisplayName, BirthDate',
    null, null, null, null, null, 0, null, true, null);
rowsImported        |failedRows          |files      |dataSize            |failedLog--------------------------------------------------------------------------------------
94                  |0                   |1          |4720                |NONE
1 row selected

Example 2: Importing strings with embedded special characters

This example imports a csv file that includes newline (Ctrl-M) characters in some of the input strings. We use the default double-quote as our character delimiter to import data such as the following:

1,This field is one line,Able
2,"This field has two lines
This is the second line of the field",Baker
3,This field is also just one line,Charlie

We then use the following call to import the data:

                                  '\t', null, null, null, null, 0, 'BAD', false, null );

We can also explicitly specify double quotes (or any other character) as our delimiter character for strings:

                                  '\t', '"', null, null, null, 0,'BAD', false, null);

See Best Practices: Importing Flat Files for more examples.

See Also