Ways To Load Large Tables In Oracle

When it comes to loading large tables in Oracle, there are several options available:

 

1. SQLLoader: SQLLoader is a command-line tool that can be used to load data from external files into Oracle database tables. It is highly efficient and can handle large data volumes.
2. External Tables: External Tables allow you to access data in external files as if it were in a regular database table. This feature is similar to SQL*Loader but can be used within SQL statements.
3. Oracle Data Pump: Oracle Data Pump is a utility for importing and exporting data between Oracle databases. It can be used to load large tables by creating a data pump export file and then importing the data into the target table.
4. Direct Path Load: The Direct Path Load option is a feature of SQL*Loader and External Tables. It bypasses the SQL engine and writes data directly to the data files. This method can be faster than conventional loading but requires more temporary space.
5. Partitioning: Partitioning is a way to divide large tables into smaller, more manageable pieces. This can improve query performance and simplify data maintenance tasks such as backup and recovery.

The best option for loading large tables in Oracle depends on factors such as the size and complexity of the data, the available resources, and the specific requirements of the project. SQL*Loader and External Tables are generally the most efficient methods for loading large amounts of data, but other options may be more appropriate depending on the situation.

 
Direct path load and DBMS Parallel Execute are both high-performance methods for loading data into Oracle databases, but their speed will depend on various factors such as the size and complexity of the data, the number of processors and the amount of memory available on the system.

In general, direct path load is considered to be faster than DBMS Parallel Execute for loading large amounts of data, especially when the data is already in a flat file format. Direct path load bypasses the SQL engine and writes data directly to the data files, which can result in faster load times.

On the other hand, DBMS Parallel Execute can be faster than direct path load for complex operations that require complex transformation or data manipulation, such as merging data from multiple sources or performing calculations on large datasets. DBMS Parallel Execute allows for parallel processing, which can significantly reduce the time required for such operations.

It's worth noting that both methods have their own advantages and limitations, and the best option will depend on the specific requirements of the project. It's always a good idea to test both methods and measure their performance to determine which method is the most suitable for your particular use case.

When it comes to loading large amounts of data into an Oracle database, SQLLoader is often the tool of choice. SQLLoader is a powerful and flexible utility that can load data from a variety of sources, including flat files, external tables, and even other databases.

Let us take a closer look at how to use SQL*Loader to load huge tables in Oracle databases.

1. Preparing the Data

Before you can load data into an Oracle database using SQLLoader, you need to prepare the data in a format that SQLLoader can recognize. This usually involves creating a flat file that contains the data, with each row of data on a separate line and each column separated by a delimiter, such as a comma or a tab.

For example, here's a sample file that contains sales data:

101,2019-01-01,Widget A,100,10.99
102,2019-01-02,Widget B,200,19.99
103,2019-01-03,Widget C,300,29.99

The file contains five columns of data: an ID column, a date column, a product name column, a quantity column, and a price column.

2. Creating a Control File

Once you have prepared the data file, you need to create a control file that tells SQLLoader how to load the data into the database. The control file contains instructions on how to interpret the data file, such as the delimiter to use, the format of the data, and how to map the data columns in the database.

Here's an example of a control file that can be used to load the sales data from the sample files above:

LOAD DATA
INFILE 'sales_data.csv'
APPEND
INTO TABLE sales
FIELDS TERMINATED BY ','
(
  id,
  sale_date DATE "YYYY-MM-DD",
  product_name CHAR(20),
  quantity INTEGER,
  price FLOAT EXTERNAL
)

This control file specifies that the data is stored in a file called "sales_data.csv", that it should be appended to an existing table called "sales", and that the fields in the data file are separated by commas. It also maps each column in the data file to a column in the database, specifying the data type for each column.

3. Running SQLLoader

Once you have prepared the data file and the control file, you can run SQLLoader to load the data into the database. To do this, simply run the following command:

sqlldr username/password control=control_file.ctl log=log_file.log

This command tells SQL*Loader to use the specified control file to load data into the database, and to log any errors or warnings to a log file.

4. Conclusion

SQLLoader is a powerful tool that can help you load large amounts of data into Oracle databases quickly and efficiently. By preparing your data in a format that SQLLoader can recognize, creating a control file that tells SQLLoader how to interpret the data, and running SQLLoader to laod the data into the database, you can easily and reliably load huge tables in Oracle.

When it comes to loading large amounts of data into an Oracle database, direct path load can be a powerful option. Direct path load bypasses much of the Oracle buffer cache and performs the load operation directly on the database files, making it faster and more efficient than other load methods.

Let us understand how direct path load in Oracle is used to load data into a table.

• What is Direct Path Load?

Direct path load is a method of loading data into an Oracle database that bypasses the database buffer cache and writes data directly to the database files. This makes direct path load faster and more efficient than other load methods, as it reduces the amount of I/O required and minimizes the impact on the buffer cache.

Direct path load is ideal for loading large amounts of data into the database, such as when migrating data from a legacy system or loading data for data warehousing and business intelligence purposes.

• How to Use Direct Path Load

To use direct path load in Oracle, you can use the SQLLoader utility with the DIRECT parameter. Here's an example of how to load data into a table using direct path load:

Assume that you have a CSV file containing data that needs to be loaded into a table called "sales_data". The file contains five columns of data: an ID column, a date column, a product name column, a quantity column, and a price column.

Create a control file that tells SQLLoader how to load the data into the database. Here's an example of a control file that can be used to load the sales data from the sample file:

LOAD DATA
INFILE 'sales_data.csv'
APPEND
INTO TABLE sales_data
FIELDS TERMINATED BY ','
(
  id,
  sale_date DATE "YYYY-MM-DD",
  product_name CHAR(20),
  quantity INTEGER,
  price FLOAT EXTERNAL
)

This control file specifies that data is stored in a file called "sales_data.csv", that it should be appended to an existing table called "sales_data", and that the fields in the data file are separated by commas. It also maps each column in the data file to a column in the database, specifying the data type for each column.

Run SQLLoader with the DIRECT parameter to perform a direct path load. Here's an example of the command you would use:

sqlldr username/password control=control_file.ctl log=log_file.log direct=true

This command tells SQLLoader to use the specified control file to load data into the database, and to log any errors or warnings to a log file. The "direct=true" parameter specifies that a direct path load should be used.

Direct path load can be a powerful option for loading large amounts of data into an Oracle database quickly and effectively. By bypassing the buffer cache and writing data directly to the database files, direct path load can reduce the amount of I/O required and minimize the impact on the buffer cache. With SQLLoader, performing a direct path load is easy and can be done with just a few simple steps.

DBMS Parallel Execute is a powerful feature of Oracle Database that allows you to execute SQL statements in parallel.

Here are a few examples of how to use DBMS Parallel Execute in Oracle: 

• Execute a SELECT statement in parallel:

DECLARE
  l_sql VARCHAR2(1000) := 'SELECT * FROM my_table';
BEGIN
  dbms_parallel_execute.Run_task(l_sql);
END;/

 
This code will execute the SELECT statement in parallel across multiple threads, which can significantly speed up the query execution time.

• Execute a DML statement in parallel:

DECLARE
    l_sql VARCHAR2(1000) := 'UPDATE my_table SET column1 = :1 WHERE id = :2';
BEGIN
 dbms_parallel_execute.Run_task(l_sql, dbms_sql.native, 'parallel', 10, 1000)
    ;
END;
/ 

 

This code will update the "column1" field in the "my_table" table in parallel, using 10 threads and a batch size of 1000.

 

• Divide a large query into smaller chunks using DBMS Parallel Execute:

DECLARE
    l_sql VARCHAR2(1000) :=
    'SELECT * FROM my_table WHERE id BETWEEN :start_id AND :end_id';
BEGIN
    dbms_parallel_execute.Create_task('my_task');

    dbms_parallel_execute.Create_chunks_by_sql('my_task', l_sql, TRUE);

    dbms_parallel_execute.Run_task('my_task');
END;

/ 

This code will divide a large query into smaller chunks using DBMS Parallel Execute, then execute each chunk in parallel across multiple threads.

Overall, DBMS Parallel Execute is a powerful tool for improving the performance of SQL statements in Oracle Database. By leveraging parallel processing, you can execute queries and updates faster and more efficiently, especially when dealing with large datasets.


Thank you for reading this article please feel free to leave me some feedback or to suggest any future topics. I'll be looking forward to hearing from you – Swadhin Ray  (Sloba)
 
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