1.
Introduction to SQL*Loader
Overview
SQL*Loader, often abbreviated as “sqlldr,” is
a command-line tool provided by Oracle that allows database administrators and
developers to import large volumes of data from flat files into Oracle database
tables. It is optimized for high-speed data loading and supports both
conventional and direct path loading methods.
Use Cases
- Data Migration: Transitioning
legacy data from old systems into Oracle.
- ETL Processes:
Extracting data from external sources and loading it into staging or data
warehouse tables.
- Data Integration:
Combining data from different sources for centralized analysis.
- Batch Processing:
Loading log files or transactional data on a scheduled basis.
- Rapid Prototyping:
Quickly importing sample data for development and testing.
Key
Benefits
- High-Speed Loading:
Especially with the direct path option, SQL*Loader can import data
rapidly.
- Flexible Data Formats:
Supports both delimited and fixed-width file formats.
- Data Transformation:
Allows basic transformation of data during the load process.
- Error Handling:
Provides mechanisms to log bad records and control the loading process.
- Parallelism: Can
use multiple processes to improve performance on large data sets.
2.
Understanding the SQL*Loader Control File
What is a
Control File?
The control file is the blueprint for SQLLoader.
It instructs SQLLoader on how to parse the input data, which tables to
load, and how to handle each field. Think of it as the “recipe” that dictates
how raw data is transformed into structured table data.
Components
of a Control File
- LOAD DATA Clause: Specifies
that this is a data load operation.
- INFILE Clause:
Identifies the external data file(s) to be loaded.
- INTO TABLE Clause:
Indicates the target table within the Oracle database.
- FIELDS Clause:
Details the delimiter, enclosure characters, and optionally, the data
types of the fields.
- Column Definitions: Maps
columns in the data file to columns in the target table, optionally with
formatting rules or conversion functions.
- Optional Directives: Such
as conditions for loading specific rows (using the WHEN clause) or setting
special formatting for dates and numbers.
Detailed
Example
Imagine you have an external file employees.txt with the following content:
1001,"John
Doe",50000,2023-01-10
1002,"Jane
Smith",60000,2023-02-15
A corresponding control file might look like
this:
LOAD DATA
INFILE 'employees.txt'
INTO TABLE
employees
FIELDS
TERMINATED BY ',' OPTIONALLY ENCLOSED BY '"'
(
emp_id,
emp_name,
emp_salary,
emp_join_date DATE "YYYY-MM-DD"
)
Here, each field is clearly mapped: the
employee ID, name, salary, and join date are loaded into the employees table. The date format is explicitly defined to match the format in the
file.
Tips for
Writing Effective Control Files
- Consistency:
Ensure the data file's structure exactly matches the control file’s
expectations.
- Error Logging:
Always specify a LOG file to capture errors during the load process.
- Testing: Run a small test load before processing
large files.
- Documentation:
Comment your control file to explain any nonstandard configurations.
3.
Specifying the Input File
Importance
of the Input File
The input file contains the raw data that
needs to be imported into the database. It can be a simple text file, CSV file,
or even a fixed-width file. The file must reside on the server where Oracle is
installed, as SQL*Loader accesses the file system directly.
File Types
and Formats
- Delimited Files:
Commonly CSV files, where fields are separated by commas (or other
delimiters such as tabs or semicolons). These are flexible and easy to
generate from most applications.
- Fixed-Width Files: Each
field occupies a fixed number of characters. These are often used when
data comes from legacy systems or mainframe environments.
Example for
Delimited Files
Consider a CSV file employees.txt with the following entries:
1001,"John
Doe",50000,2023-01-10
1002,"Jane
Smith",60000,2023-02-15
The control file should reference the file as
follows:
INFILE 'employees.txt'
Example for
Fixed-Width Files
A fixed-width data file might look like this:
100John
Doe 5000020230110
101Jane
Smith 6000020230215
Here, the columns are in fixed positions. In
the control file, you would specify positions for each field:
LOAD DATA
INFILE 'employees_fixed.txt'
INTO TABLE
employees
(
emp_id
POSITION(1:3),
emp_name
POSITION(4:20),
emp_salary
POSITION(21:26),
emp_join_dt
POSITION(27:34) DATE "YYYYMMDD"
)
4. Loading
Data into Nonempty Tables
Handling
Existing Data
When loading data into a table that already
contains records, SQL*Loader offers several options to control how the new data
is inserted. The choice depends on whether you want to preserve the existing
data or replace it entirely.
Options
- APPEND: Adds new rows to the table without
removing existing data.
- REPLACE: Deletes the current table data and then
loads new data. This is useful when you need a complete refresh.
- TRUNCATE: Similar to REPLACE but uses the TRUNCATE
command to quickly remove existing data.
- INSERT (Default): Fails
if the table is not empty; this is used for strictly controlled
environments where duplicate data is not allowed.
Detailed
Example
If you want to add new customer records to an
existing table without losing any data, you might use:
LOAD DATA
INFILE 'customers.txt'
APPEND
INTO TABLE
customers
FIELDS
TERMINATED BY ','
(
customer_id,
customer_name,
contact_number,
join_date DATE "MM/DD/YYYY"
)
On the other hand, if you need to replace all
data in the customers table with
fresh data from a new file, you can use:
LOAD DATA
INFILE 'customers_new.txt'
REPLACE
INTO TABLE
customers
FIELDS
TERMINATED BY ','
(
customer_id,
customer_name,
contact_number,
join_date DATE "MM/DD/YYYY"
)
Best
Practices
- Backup Data:
Always back up existing data before performing a REPLACE or TRUNCATE load.
- Transaction Control:
Consider the implications of loading large datasets into live tables and
plan for downtime if necessary.
- Error Handling:
Utilize SQL*Loader’s error logging to capture and review any problematic
records.
5.
Specifying the Table to Load
Mapping
Data to Tables
The INTO TABLE clause specifies the target table for the data. It’s important to
ensure that the data file’s columns match the table’s columns in both order and
data type.
Using
Conditions
SQL*Loader allows you to use a WHEN clause to
load only rows that meet certain criteria. This is particularly useful when the
data file contains records for multiple tables.
Example
without Conditions
INTO TABLE
products
FIELDS
TERMINATED BY ','
(
product_id,
product_name,
price
)
Example
with Conditions
If you only want to load orders of a specific
type:
INTO TABLE
orders
WHEN
(order_type = 'online')
FIELDS
TERMINATED BY ','
(
order_id,
order_date DATE "MM/DD/YYYY",
order_total
)
Tips
- Data Integrity:
Verify that the data types in the control file match the target table’s
schema.
- Conditional Loading: Use
conditions to filter data, which can simplify post-load data cleanup.
6.
Describing Fixed-Width Columns
What Are
Fixed-Width Columns?
Fixed-width columns refer to data fields that
have a set number of characters. This is common in data coming from legacy
systems, where each column occupies a fixed space.
Specifying
Positions
In the control file, the POSITION keyword is used to indicate where each field begins and ends.
Detailed
Example
Suppose you have a fixed-width file employees_fixed.txt with the following content:
100John
Smith 5000020230110
101Jane
Smith 6000020230215
The control file would be:
LOAD DATA
INFILE 'employees_fixed.txt'
INTO TABLE
employees
(
emp_id
POSITION(1:3),
emp_name
POSITION(4:20),
emp_salary
POSITION(21:26),
emp_join_dt
POSITION(27:34) DATE "YYYYMMDD"
)
Best
Practices
- Accurate Positioning:
Double-check the character positions to ensure that fields are extracted
correctly.
- Test with Samples: Run
SQL*Loader on a small sample of data before processing large files.
- Handling Padding:
Consider whether spaces or zeros are used as padding, and adjust your
extraction rules accordingly.
7. Using
SQL*Loader Data Types
Overview of
Supported Data Types
SQL*Loader supports a variety of data types to
match the structure of your target table. Common data types include:
- CHAR: For character data.
- DATE: For date values, which can be formatted
using masks.
- INTEGER EXTERNAL: For
numeric data stored as text.
- DECIMAL EXTERNAL: For
decimal numbers represented in the file.
- FLOAT EXTERNAL: For
floating point numbers.
Example of
Data Type Specification
Consider the salary field, which might be
represented as a decimal number:
salary DECIMAL
EXTERNAL TERMINATED BY WHITESPACE
This tells SQL*Loader to treat the salary as a
decimal value, even if it’s stored as text in the data file.
Transformation
and Conversion
SQL*Loader also allows you to perform simple
data transformations. For example, if the data file uses a different date
format, you can convert it during the load:
hire_date DATE
"DD-MON-YYYY"
Tips for
Data Types
- Match Exactly: Ensure
that the data types specified in the control file exactly match the table
schema.
- Use Conversion Masks: When
working with dates or numbers, always provide the appropriate format mask.
- Validate Data: After
loading, validate a sample of the data to ensure it’s been correctly
interpreted.
8.
Describing Delimited Columns
Understanding
Delimited Data
Delimited files are perhaps the most common
type of input file. They separate fields using a specific character such as a
comma, tab, or pipe. This format is widely used because of its simplicity and
ease of generation from many applications.
Specifying
Delimiters
In the control file, the FIELDS
TERMINATED BY clause tells SQL*Loader how to identify
individual fields. You can also specify if the fields might be enclosed in
quotes, which is useful if your data contains the delimiter as part of the
field value.
Example
For a CSV file, the control file might
include:
FIELDS
TERMINATED BY ',' OPTIONALLY ENCLOSED BY '"'
And the data file might contain:
1001,"John
Doe",50000
1002,"Jane
Smith",60000
Handling
Special Cases
- Embedded Delimiters: If
your data values themselves contain commas, the option to enclose fields
with quotes prevents misinterpretation.
- Missing Values:
SQL*Loader provides ways to handle missing or null values gracefully.
9.
Understanding the SQL*Loader Command
Running
SQL*Loader
SQL*Loader is invoked from the command prompt.
Its command-line syntax provides several parameters to control its behavior.
Basic
Syntax
bash
sqlldr
userid=your_user/your_password control=your_control_file.ctl log=your_log_file.log
Key
Parameters
- userid: Specifies the database connection
details.
- control: Points to the control file that contains
the load instructions.
- log: Defines a log file to capture details of
the load operation.
- bad: Optionally, a file that records records
that could not be loaded.
- direct: Specifies whether to use direct path
loading.
Example
Command
bash
sqlldr
userid=scott/tiger control=load_employees.ctl log=load_employees.log
This command initiates SQL*Loader to load data
according to the rules specified in load_employees.ctl and writes operational details to load_employees.log.
Best
Practices
- Log Files:
Always create a log file to review errors or warnings.
- Environment Variables:
Ensure your Oracle environment variables (e.g., ORACLE_HOME) are correctly
set.
- Testing: Start with a small file and then scale
up once you’ve verified the process.
10. Loading
Methods in SQL*Loader
SQL*Loader offers two main loading methods,
each suited to different scenarios:
a.
Conventional Path Load
Description:
- The conventional path load method processes data using standard SQL
INSERT statements.
- It honors triggers, constraints, and indexes, which means the data
undergoes all the usual checks.
- It is ideal when data integrity and business logic enforced by
triggers are critical.
Pros:
- Maintains data integrity by enforcing all constraints and triggers.
- Easier to use for small to medium loads.
Cons:
- Slower for very large datasets due to the overhead of the SQL
layer.
b. Direct
Path Load
Description:
- Direct path load bypasses much of the SQL processing layer and
writes data directly into data blocks.
- It is significantly faster than conventional path loads, making it
suitable for very large volumes of data.
- Some constraints and triggers are ignored during direct path
loading, so care must be taken to validate data after the load.
Pros:
- Very fast data loading.
- Reduced logging and minimal CPU overhead.
Cons:
- Doesn’t trigger all constraints and business rules.
- May require additional steps to re-enable indexes and triggers
post-load.
Example to Use Direct Path:
bash
sqlldr
userid=scott/tiger control=load_employees.ctl log=load_employees.log direct=true
Choosing
the Right Method
- Small Loads: Use
conventional path if data integrity rules must be enforced.
- Large Loads: Use
direct path to speed up the process, but validate data after loading.
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