Bulk Loading

Bulk loading rows instead of inserting them one at a time can dramatically increase the throughput of an ETL program. Bulk loading works by loading data from a temporary file into the database. The actual process of bulk loading is unfortunately different for each RDBMS. Because of this, a user-defined function must be created that uses the functionality provided by a particular RDBMS to bulk load the data from a file. The following is a list of example functions showing how bulk loading can be performed for some of the more commonly used RDBMSs.

Currently, three classes in pygrametl use bulk loading: BulkDimension, CachedBulkDimension, and BulkFactTable. Thus a function that can bulk load data from a file into the specific RDBMS used for the data warehouse, must be passed to each of these classes constructors. The function must have the following signature:

func(name, attributes, fieldsep, rowsep, nullval, filehandle):

Required signature of a function bulk loading data from a file into an RDBMS in pygrametl.

  • name – The name of the table in the data warehouse.

  • attributes – A list containing the sequence of attributes in the table.

  • fieldsep – The string used to separate fields in the temporary file.

  • rowsep – The string used to separate rows in the temporary file.

  • nullval – If the class was passed a string to substitute None values with, then it will be passed, if not then None is passed.

  • filehandle – Either the name of the file or the file object itself, depending upon the value of member usefilename on the class.


For PostgreSQL the copy_from method from psycopg2 can be used:

# psycopg2
def pgbulkloader(name, attributes, fieldsep, rowsep, nullval, filehandle):
    global connection
    cursor = connection.cursor()
    cursor.copy_from(file=filehandle, table=name, sep=fieldsep, null=nullval,

If Jython is used the copyIn method in JDBC’s CopyManager class can be used:

def pgcopybulkloader(name, attributes, fieldsep, rowsep, nullval, filehandle):
    global pgconnection
    copymgr = pgconnection.getCopyAPI()
    sql = "COPY %s(%s) FROM STDIN WITH DELIMITER '%s'" % \
          (name, ', '.join(attributes), fieldsep)
    copymgr.copyIn(sql, filehandle)


For MySQL the LOAD DATA INFILE functionality provided by MySQL SQL dialect can be used.

# MySQLdb
def mysqlbulkloader(name, attributes, fieldsep, rowsep, nullval, filehandle):
    global connection
    cursor = connection.cursor()
            (filehandle, name, fieldsep, rowsep, ', '.join(attributes))


Oracle supports two methods for bulk loading from text files, SQL Loader and External Tables. The following example uses SQL Loader as it does not require the creation of an additional table, which is problematic to do in a bulk loading function as the data types of each column must be specified.

SQL Loader is part of Oracle’s client package. SQL Loader requires all configuration and data files to have specific suffixes, so a file must be created with the suffix .dat and passed to any bulk loading table as tempdest.

with tempfile.NamedTemporaryFile(suffix=".dat") as dat_handle:

The bulk loading function shown below constructs a control file with the .ctl suffix using the functions arguments. The SQL Loader is then executed (sqlldr must in the system path) and passed the constructed .ctl file.

# cx_Oracle or JDBC
def oraclebulkloader(name, attributes, fieldsep, rowsep, nullval, filehandle):

    # The configuration file used by SQL Loader must use the suffix .ctf
    with tempfile.NamedTemporaryFile(suffix=".ctl") as ctl_handle:

        # The attributes to be loaded must be qouted using double quotes
        unqouted_atts = str(tuple(attributes)).replace("'", "")
        ctl_contents = """
            LOAD DATA INFILE '%s' "str %r"
            APPEND INTO TABLE %s
            """ % (filehandle.name, rowsep, name, fieldsep, unqouted_atts)

        # Strips the multi line string of unnecessary indention, and ensures
        # that the contents are written to the file by flushing it
        ctl_contents = textwrap.dedent(ctl_handle).lstrip()

        # Bulk loads the data using Oracle's SQL Loader. As a new connection
        # is created, the same username, passowrd, etc. must be given again
        os.system("sqlldr username/password@ip:port/sid control=" +

Microsoft SQL Server

For Microsoft SQL Server the BULK INSERT functionality provided by Transact-SQL can be used.

There are a number of things to be aware of when using pygrametl with SQL Server. If the file used for bulk loading is located on a machine running Microsoft Windows, the file must be copied before bulk loading, as the locks placed on the file by the OS and pygrametl, prevent SQL Server from opening it directly. Copying the file can be done e.g. using shutil.copyfile.

By default, BULK INSERT ignores column names, so the number and order of columns must match the table you are inserting into. This can be overcome by adding a format file. In this case, we create a non-XML format file.

A simple example of bulk loading in SQL Server along with the creation of a format file can be seen below:

def sqlserverbulkloader(name, attributes, fieldsep, rowsep, nullval, filehandle):
    global msconn
    cursor = msconn.cursor()

    # Copy the tempdest
    shutil.copyfile(filehandle, r'd:\dw\tmpfilecopy')

    # Create format file
    fmt = open(r'd:\dw\format.fmt', 'w+')
    # 12.0 corresponds to the version of the bcp utility being used by SQL Server.
    # For more information, see the above link on non-XML format files.
    fmt.write("12.0\r\n%d\r\n" % len(attributes))
    count = 0
    sep = "\\t"
    for a in attributes:
        count += 1
        if count == len(attributes): sep = "\\n"
        # For information regarding the format values,
        # see the above link on non-XML format files.
        fmt.write('%d SQLCHAR 0 8000 "%s" %d %s "Latin1_General_100_CI_AS_SC"\r\n' % (count, sep, count, a))

            (name, r'd:\dw\tmpfilecopy', r'd:\dw\format.fmt', fieldsep, rowsep,)