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Contents → Related Documents Conventions Changes in This Release for Oracle Database VLDB and Partitioning Guide … Partitioning VLDB and Partitioning Partitioning As the Foundation for Information Lifecycle Management
VLDB and Partitioning → A very large database has no minimum absolute size. Although a VLDB is a database like smaller … databases, there are specific challenges in managing a VLDB. These challenges are related to the sheer … challenges surrounding backup and recovery for a VLDB. Storage is a key component of a very large … database. Storage Management
4.14 Oracle Database VLDB and Partitioning Guide → Note the following changes in Oracle Database VLDB and Partitioning Guide part number E41057: It
NO_PQ_CONCURRENT_UNION Hint → processing of UNION and UNION ALL operations. See Also: \"PQ_CONCURRENT_UNION Hint\" Oracle Database VLDB
PQ_CONCURRENT_UNION Hint → UNION and UNION ALL operations. See Also: \"NO_PQ_CONCURRENT_UNION Hint\" Oracle Database VLDB and Partitioning Guide for information about using this hint
ENABLE_PARALLEL_DML Hint → ALTER SESSION ENABLE PARALLEL DML statement. See Also: Oracle Database VLDB and Partitioning Guide
Changes in This Release for Oracle Database VLDB and Partitioning Guide → This chapter describes changes to Oracle Database VLDB and Partitioning Guide. Changes for Very
21.2.9 Consider Parallelizing Index Creation → creation. See Also: Oracle Database VLDB and Partitioning Guide for information about using parallel execution
Use the PARALLEL_SERVER_LIMIT directive attribute to specify the maximum percentage of the parallel… → degree of parallelism for a consumer group. See Also: Oracle Database VLDB and Partitioning Guide for
Oracle® Database → VLDB and Partitioning Guide 12 c Release 1 (12.1) E41057-12 July 2016 Oracle Database VLDB and
Changes for Very Large Databases and Partitioning in Oracle Database 12c Release 1 (188.8.131.52) → The following are changes in Very Large Databases and Partitioning for Oracle Database 12 c Release 1 (184.108.40.206). New Features
Changes for Very Large Databases and Partitioning in Oracle Database 12c Release 1 (220.127.116.11) → Automatic Big Table Caching Automatic big table caching enhances in-memory query capabilities of Oracle Database in both single instance and Oracle Real Application Clusters (Oracle RAC) environments using a temperature based algorithm with the big table cache. In Oracle RAC environments, this feature is supported only with parallel queries. In single instance environments, this feature is supported
20.2.2 Specify the Type of Table to Create → administration. Partitioned tables are discussed in Oracle Database VLDB and Partitioning Guide.
20.6.1 Reasons for Using the ALTER TABLE Statement → subpartitions at a time, such as split partition and merge partitions operations. See Oracle Database VLDB
FAST_START_PARALLEL_ROLLBACK → If a system fails when there are uncommitted parallel DML or DDL transactions, you can speed up transaction recovery during startup by using the FAST_START_PARALLEL_ROLLBACK parameter. This parameter controls the DOP used when recovering terminated transactions. Terminated transactions are transactions that are active before a system failure. By default, the DOP is chosen to be at most two times the
Degree of Parallelism (CREATE Part) → The DOP for the CREATE operation, and for the SELECT operation if it is parallelized, is specified by the PARALLEL clause of the CREATE statement, unless it is overridden by an ALTER SESSION FORCE PARALLEL DDL statement. If the PARALLEL clause does not specify the DOP, the default is the number of CPUs.
Creating Composite List-Range Partitioned Tables → Example 4-14 shows an accounts table that is list partitioned by region and subpartitioned using range by account balance, and row movement is enabled. Subpartitions for different list partitions could have different ranges specified. To learn how using a subpartition template can simplify the specification of a composite partitioned table, see \" Specifying Subpartition Templates to Describe Composite
Creating Reference-Partitioned Tables → To create a reference-partitioned table, you specify a PARTITION BY REFERENCE clause in the CREATE TABLE statement. This clause specifies the name of a referential constraint and this constraint becomes the partitioning referential constraint that is used as the basis for reference partitioning in the table. The referential constraint must be enabled and enforced. As with other partitioned tables,
Single-Level Partitioning → A table is defined by specifying one of the following data distribution methodologies, using one or more columns as the partitioning key: Range Partitioning Hash Partitioning List Partitioning For example, consider a table with a column of type NUMBER as the partitioning key and two partitions less_than_five_hundred and less_than_one_thousand. The less_than_one_thousand partition contains rows where
Creating a Composite Range-List Partitioned Table → Example 4-10 illustrates how range-list partitioning might be used. The example tracks sales data of products by quarters and within each quarter, groups it by specified states. A row is mapped to a partition by checking whether the value of the partitioning column for a row falls within a specific partition range. The row is then mapped to a subpartition within that partition by identifying the subpartition
Truncating Multiple Partitions → You can truncate multiple partitions from a range or list partitioned table with the TRUNCATE PARTITION clause of the ALTER TABLE statement. The corresponding partitions of local indexes are truncated in the operation. Global indexes must be rebuilt unless UPDATE INDEXES is specified.For example, the following SQL statement truncates multiple partitions in the range-partitioned sales table. ALTER
Exchanging a Hash Partitioned Table with a *-Hash Partition → In this example, you are exchanging a whole hash partitioned table, with all of its partitions, with the partition of a *-hash partitioned table and all of its hash subpartitions. The following example illustrates this concept for a range-hash partitioned table. First, create a hash partitioned table: CREATE TABLE t1 (i NUMBER, j NUMBER) PARTITION BY HASH(i) (PARTITION p1, PARTITION p2); Populate
Best Practice 1: Use ARCHIVELOG Mode → Archived redo logs are crucial for recovery when no data can be lost because they constitute a record of changes to the database. Oracle Database can be run in either of two modes: ARCHIVELOG Oracle Database archives the filled online redo log files before reusing them in the cycle. NOARCHIVELOG Oracle Database does not archive the filled online redo log files before reusing them in the cycle. Running
Extract, Transform, and Load → The ETL process uses several Oracle features and a combination of methods to load (re-load) data into a data warehouse. These features consist of: Transportable tablespaces Transportable tablespaces allow users to quickly move a tablespace across Oracle Databases. It is the most efficient way to move bulk data between databases. Oracle Database provides the ability to transport tablespaces across
Concurrent Execution of Union All → Set operators like UNION or UNION ALL consist of multiple queries (branches) combined to a single SQL statement. Traditionally, set operators are processed in a sequential manner. Individual branches can be processed in serial or parallel, but only one branch at a time, one branch after another. While this approach satisfies many use cases, there are situations where the processing of multiple branches
About Modifying List Partitions: Adding Values → List partitioning enables you to optionally add literal values from the defining value list. This section contains the following topics: Adding Values for a List Partition Adding Values for a List Subpartition
Partitioning Overview → Partitioning allows a table, index, or index-organized table to be subdivided into smaller pieces, where each piece of such a database object is called a partition. Each partition has its own name, and may optionally have its own storage characteristics. This section contains the following topics: Basics of Partitioning Partitioning Key Partitioned Tables Partitioned Index-Organized Tables System
Global Nonpartitioned Indexes → Global nonpartitioned indexes behave just like local nonpartitioned indexes. Figure 2-8 offers a graphical view of global nonpartitioned indexes. Figure 2-8 Global Nonpartitioned Index Description of \"Figure 2-8 Global Nonpartitioned Index\"
Partition Pruning → Partition pruning is an essential performance feature for data warehouses. In partition pruning, the optimizer analyzes FROM and WHERE clauses in SQL statements to eliminate unneeded partitions when building the partition access list. This functionality enables Oracle Database to perform operations only on those partitions that are relevant to the SQL statement. This section contains the following
Incremental Data Loading in Parallel → Parallel DML combined with the updatable join views facility provides an efficient solution for refreshing the tables of a data warehouse system. To refresh tables is to update them with the differential data generated from the OLTP production system. In the following example, assume a refresh of a table named customers that has columns c_key, c_name, and c_addr. The differential data contains either
Creating List-Partitioned Index-Organized Tables → The other option for partitioning index-organized tables is to use the list method. In the following example, the sales index-organized table is partitioned by the list method. Example 4-24 uses the example tablespace, which is part of the sample schemas in your seed database. Normally you would specify different tablespace storage for different partitions. Example 4-24 Creating a list-partitioned
Default Parallelism → If the PARALLEL clause is specified but no degree of parallelism is listed, the object gets the default DOP. Default parallelism uses a formula to determine the DOP based on the system configuration, as in the following: For a single instance, DOP = PARALLEL_THREADS_PER_CPU x CPU_COUNT For an Oracle RAC configuration, DOP = PARALLEL_THREADS_PER_CPU x CPU_COUNT x INSTANCE_COUNT By default, INSTANCE_COUNT
About Dropping Partitioned Tables → Oracle Database processes a DROP TABLE statement for a partitioned table in the same way that it processes the statement for a nonpartitioned table. One exception is when you use the PURGE keyword. To avoid running into resource constraints, the DROP TABLE... PURGE statement for a partitioned table drops the table in multiple transactions, where each transaction drops a subset of the partitions or
Specifying Partitioning When Creating Index-Organized Tables → For index-organized tables, you can use the range, list, or hash partitioning method. The semantics for creating partitioned index-organized tables is similar to that for regular tables with these differences: When you create the table, you specify the ORGANIZATION INDEX clause, and INCLUDING and OVERFLOW clauses as necessary. The PARTITION clause can have OVERFLOW subclauses that allow you to specify
Bigfile Tablespaces → Oracle Database enables the creation of bigfile tablespaces. A bigfile tablespace consists of a single data or temporary file which can be up to 128 TB. The use of bigfile tablespaces can significantly reduce the number of data files for your database. Oracle Database supports parallel RMAN backup and restore on single data files. See Also: Oracle Database Backup and Recovery User's Guide Consequently,
About Merging Partitions and Subpartitions → Use the ALTER TABLE MERGE PARTITION statement to merge the contents of two partitions into one partition. The two original partitions are dropped, as are any corresponding local indexes. You cannot use this statement for a hash partitioned table or for hash subpartitions of a composite *-hash partitioned table. You cannot merge partitions for a reference-partitioned table. Instead, a merge operation
Balancing the Workload to Optimize Performance → To optimize performance, all parallel execution servers should have equal workloads. For SQL statements run in parallel by block range or by parallel execution servers, the workload is dynamically divided among the parallel execution servers. This minimizes workload skewing, which occurs when some parallel execution servers perform significantly more work than the other processes. For the relatively
Parameters Establishing Resource Limits for Parallel Operations → You can set initialization parameters to determine resource limits. The parameters that establish resource limits are discussed in the following topics: PARALLEL_FORCE_LOCAL PARALLEL_MAX_SERVERS PARALLEL_MIN_PERCENT PARALLEL_MIN_SERVERS PARALLEL_MIN_TIME_THRESHOLD PARALLEL_SERVERS_TARGET SHARED_POOL_SIZE Additional Memory Requirements for Message Buffers Monitor Memory Usage After Processing Begins
Introduction to Partitioning → Partitioning addresses key issues in supporting very large tables and indexes by decomposing them into smaller and more manageable pieces called partitions, which are entirely transparent to an application. SQL queries and Data Manipulation Language (DML) statements do not need to be modified to access partitioned tables. However, after partitions are defined, data definition language (DDL) statements
About Parallel DML Operations → Parallel DML ( PARALLEL INSERT, UPDATE, DELETE, and MERGE ) uses parallel execution mechanisms to speed up or scale up large DML operations against large database tables and indexes. Note: Although DML generally includes queries, in this chapter the term DML refers only to INSERT, UPDATE, MERGE, and DELETE operations. This section discusses the following parallel DML topics: When to Use Parallel DML