Inserting, Updating, and Deleting Data

This section provides information about manipulating data and concurrent access in Greenplum Database.

This topic includes the following subtopics:

• About Concurrency Control in Greenplum Database
• Inserting Rows
• Updating Existing Rows
• Deleting Rows
• Working With Transactions
• Vacuuming the Database

Parent topic: Greenplum Database Administrator Guide

About Concurrency Control in Greenplum Database

Greenplum Database and PostgreSQL do not use locks for concurrency control. They maintain data consistency using a multiversion model, Multiversion Concurrency Control (MVCC). MVCC achieves transaction isolation for each database session, and each query transaction sees a snapshot of data. This ensures the transaction sees consistent data that is not affected by other concurrent transactions.

Because MVCC does not use explicit locks for concurrency control, lock contention is minimized and Greenplum Database maintains reasonable performance in multiuser environments. Locks acquired for querying (reading) data do not conflict with locks acquired for writing data.

Greenplum Database provides multiple lock modes to control concurrent access to data in tables. Most Greenplum Database SQL commands automatically acquire the appropriate locks to ensure that referenced tables are not dropped or modified in incompatible ways while a command executes. For applications that cannot adapt easily to MVCC behavior, you can use the LOCK command to acquire explicit locks. However, proper use of MVCC generally provides better performance.

Lock Mode	Associated SQL Commands	Conflicts With
ACCESS SHARE	SELECT	ACCESS EXCLUSIVE
ROW SHARE	SELECT FOR SHARE, SELECT FOR UPDATE	EXCLUSIVE, ACCESS EXCLUSIVE
ROW EXCLUSIVE	INSERT, COPY, UPDATE, DELETE on non-partitioned tables, see Note.	SHARE, SHARE ROW EXCLUSIVE, EXCLUSIVE, ACCESS EXCLUSIVE
SHARE UPDATE EXCLUSIVE	VACUUM (without FULL), ANALYZE	SHARE UPDATE EXCLUSIVE, SHARE, SHARE ROW EXCLUSIVE, EXCLUSIVE, ACCESS EXCLUSIVE
SHARE	CREATE INDEX	ROW EXCLUSIVE, SHARE UPDATE EXCLUSIVE, SHARE ROW EXCLUSIVE, EXCLUSIVE, ACCESS EXCLUSIVE
SHARE ROW EXCLUSIVE		ROW EXCLUSIVE, SHARE UPDATE EXCLUSIVE, SHARE, SHARE ROW EXCLUSIVE, EXCLUSIVE, ACCESS EXCLUSIVE
EXCLUSIVE	SELECT FOR UPDATE DELETE, UPDATE on partitioned tables. See Note.	ROW SHARE, ROW EXCLUSIVE, SHARE UPDATE EXCLUSIVE, SHARE, SHARE ROW EXCLUSIVE, EXCLUSIVE, ACCESS EXCLUSIVE
ACCESS EXCLUSIVE	ALTER TABLE, DROP TABLE, TRUNCATE, REINDEX, CLUSTER, VACUUM FULL	ACCESS SHARE, ROW SHARE, ROW EXCLUSIVE, SHARE UPDATE EXCLUSIVE, SHARE, SHARE ROW EXCLUSIVE, EXCLUSIVE, ACCESS EXCLUSIVE

Note: Greenplum Database acquires an EXCLUSIVE lock for SELECT FOR UPDATE. PostgreSQL acquires a less restrictive ROW EXCLUSIVE lock.

For an UPDATE or DELETE command on a partitioned table, Greenplum Database acquires an EXCLUSIVE lock on the root partition table. On a non-partitioned table, Greenplum Database acquires a ROW EXCLUSIVE lock.

Inserting Rows

Use the INSERT command to create rows in a table. This command requires the table name and a value for each column in the table; you may optionally specify the column names in any order. If you do not specify column names, list the data values in the order of the columns in the table, separated by commas.

For example, to specify the column names and the values to insert:

INSERT INTO products (name, price, product_no) VALUES ('Cheese', 9.99, 1);

To specify only the values to insert:

INSERT INTO products VALUES (1, 'Cheese', 9.99);

Usually, the data values are literals (constants), but you can also use scalar expressions. For example:

INSERT INTO films SELECT * FROM tmp_films WHERE date_prod < 
'2016-05-07';

You can insert multiple rows in a single command. For example:

INSERT INTO products (product_no, name, price) VALUES
    (1, 'Cheese', 9.99),
    (2, 'Bread', 1.99),
    (3, 'Milk', 2.99);

To insert data into a partitioned table, you specify the root partitioned table, the table created with the CREATE TABLE command. You also can specify a leaf child table of the partitioned table in an INSERT command. An error is returned if the data is not valid for the specified leaf child table. Specifying a child table that is not a leaf child table in the INSERT command is not supported.

To insert large amounts of data, use external tables or the COPY command. These load mechanisms are more efficient than INSERT for inserting large quantities of rows. See Loading and Unloading Data for more information about bulk data loading.

The storage model of append-optimized tables is optimized for bulk data loading. Greenplum does not recommend single row INSERT statements for append-optimized tables. For append-optimized tables, Greenplum Database supports a maximum of 127 concurrent INSERT transactions into a single append-optimized table.

Updating Existing Rows

The UPDATE command updates rows in a table. You can update all rows, a subset of all rows, or individual rows in a table. You can update each column separately without affecting other columns.

To perform an update, you need:

• The name of the table and columns to update
• The new values of the columns
• One or more conditions specifying the row or rows to be updated.

For example, the following command updates all products that have a price of 5 to have a price of 10:

UPDATE products SET price = 10 WHERE price = 5;

Using UPDATE in Greenplum Database has the following restrictions:

• While GPORCA supports updates to Greenplum distribution key columns, the Postgres planner does not.
• If mirrors are enabled, you cannot use STABLE or VOLATILE functions in an UPDATE statement.
• Greenplum Database does not support the RETURNING clause.
• Greenplum Database partitioning columns cannot be updated.

Deleting Rows

The DELETE command deletes rows from a table. Specify a WHERE clause to delete rows that match certain criteria. If you do not specify a WHERE clause, all rows in the table are deleted. The result is a valid, but empty, table. For example, to remove all rows from the products table that have a price of 10:

DELETE FROM products WHERE price = 10;

To delete all rows from a table:

DELETE FROM products; 

Using DELETE in Greenplum Database has similar restrictions to using UPDATE:

• If mirrors are enabled, you cannot use STABLE or VOLATILE functions in an UPDATE statement.
• The RETURNING clause is not supported in Greenplum Database.

Truncating a Table

Use the TRUNCATE command to quickly remove all rows in a table. For example:

TRUNCATE mytable;

This command empties a table of all rows in one operation. Note that TRUNCATE does not scan the table, therefore it does not process inherited child tables or ON DELETE rewrite rules. The command truncates only rows in the named table.

Working With Transactions

Transactions allow you to bundle multiple SQL statements in one all-or-nothing operation.

The following are the Greenplum Database SQL transaction commands:

• BEGIN or START TRANSACTIONstarts a transaction block.
• END or COMMIT commits the results of a transaction.
• ROLLBACK abandons a transaction without making any changes.
• SAVEPOINT marks a place in a transaction and enables partial rollback. You can roll back commands executed after a savepoint while maintaining commands executed before the savepoint.
• ROLLBACK TO SAVEPOINTrolls back a transaction to a savepoint.
• RELEASE SAVEPOINTdestroys a savepoint within a transaction.

Transaction Isolation Levels

Greenplum Database accepts the standard SQL transaction levels as follows:

• read uncommitted and read committed behave like the standard read committed
• repeatable read is disallowed. If the behavior of repeatable read is required, use serializable.
• serializable behaves in a manner similar to SQL standard serializable

The following information describes the behavior of the Greenplum transaction levels:

• read committed/read uncommitted — Provides fast, simple, partial transaction isolation. With read committed and read uncommitted transaction isolation, SELECT, UPDATE, and DELETE transactions operate on a snapshot of the database taken when the query started.

A SELECT query:

• Sees data committed before the query starts.
• Sees updates executed within the transaction.
• Does not see uncommitted data outside the transaction.
• Can possibly see changes that concurrent transactions made if the concurrent transaction is committed after the initial read in its own transaction.

Successive SELECT queries in the same transaction can see different data if other concurrent transactions commit changes before the queries start. UPDATE and DELETE commands find only rows committed before the commands started.

Read committed or read uncommitted transaction isolation allows concurrent transactions to modify or lock a row before UPDATE or DELETE finds the row. Read committed or read uncommitted transaction isolation may be inadequate for applications that perform complex queries and updates and require a consistent view of the database.

• serializable — Provides strict transaction isolation in which transactions execute as if they run one after another rather than concurrently. Applications on the serializable level must be designed to retry transactions in case of serialization failures. In Greenplum Database, SERIALIZABLE prevents dirty reads, non-repeatable reads, and phantom reads without expensive locking, but there are other interactions that can occur between some SERIALIZABLE transactions in Greenplum Database that prevent them from being truly serializable. Transactions that run concurrently should be examined to identify interactions that are not prevented by disallowing concurrent updates of the same data. Problems identified can be prevented by using explicit table locks or by requiring the conflicting transactions to update a dummy row introduced to represent the conflict.

A SELECT query:

• Sees a snapshot of the data as of the start of the transaction (not as of the start of the current query within the transaction).

• Sees only data committed before the query starts.

• Sees updates executed within the transaction.

• Does not see uncommitted data outside the transaction.

• Does not see changes that concurrent transactions made.

  Successive SELECT commands within a single transaction always see the same data.

  UPDATE, DELETE, SELECT FOR UPDATE, and SELECT FOR SHARE commands find only rows committed before the command started. If a concurrent transaction has already updated, deleted, or locked a target row when the row is found, the serializable or repeatable read transaction waits for the concurrent transaction to update the row, delete the row, or roll back.

  If the concurrent transaction updates or deletes the row, the serializable or repeatable read transaction rolls back. If the concurrent transaction rolls back, then the serializable or repeatable read transaction updates or deletes the row.

The default transaction isolation level in Greenplum Database is read committed. To change the isolation level for a transaction, declare the isolation level when you BEGIN the transaction or use the SET TRANSACTION command after the transaction starts.

Vacuuming the Database

Deleted or updated data rows occupy physical space on disk even though new transactions cannot see them. Periodically running the VACUUM command removes these expired rows. For example:

VACUUM mytable;

The VACUUM command collects table-level statistics such as the number of rows and pages. Vacuum all tables after loading data, including append-optimized tables. For information about recommended routine vacuum operations, see Routine Vacuum and Analyze.

Important: The VACUUM, VACUUM FULL, and VACUUM ANALYZE commands should be used to maintain the data in a Greenplum database especially if updates and deletes are frequently performed on your database data. See the VACUUM command in the Greenplum Database Reference Guide for information about using the command.

Configuring the Free Space Map

Expired rows are held in the free space map. The free space map must be sized large enough to hold all expired rows in your database. If not, a regular VACUUM command cannot reclaim space occupied by expired rows that overflow the free space map.

VACUUM FULL reclaims all expired row space, but it is an expensive operation and can take an unacceptably long time to finish on large, distributed Greenplum Database tables. If the free space map overflows, you can recreate the table with a CREATE TABLE ASstatement and drop the old table. Using VACUUM FULL is discouraged.

Size the free space map with the following server configuration parameters:

• max_fsm_pages
• max_fsm_relations