Index
A
- adaptive algorithm 8.2.6
- adding ILM policies
- for Automatic Data Optimization 5.2.2.3
- adding index partitions 4.4.1.9
- adding multiple partitions 4.4.1.10
- adding partitions
- composite hash-partitioned tables 4.4.1.5
- composite list-partitioned tables 4.4.1.6
- composite range-partitioned tables 4.4.1.7
- hash-partitioned tables 4.4.1.2
- interval-partitioned tables 4.4.1.4
- list-partitioned tables 4.4.1.3
- partitioned tables 4.4.1
- range-partitioned tables 4.4.1.1
- reference-partitioned tables 4.4.1.8
- ADD PARTITION clause 4.4.1.1
- ADD SUBPARTITION clause 4.4.1.5.2, 4.4.1.6.2, 4.4.1.7.2
- ALTER INDEX statement
- partition attributes 3.3.8
- ALTER SESSION statement
- ALTER TABLE statement
- applications
- asynchronous communication
- parallel execution servers 8.1.4.5
- asynchronous global index maintenance
- for dropping and truncating partitions 4.3.2
- asynchronous I/O 8.6.3.3.4
- Automatic big table caching
- about 8.3.2
- Automatic Data Optimization
- adding ILM policies 5.2.2.3
- and heat map 5.2
- DBMS_ILM_ADMIN package 5.2.2.8
- DBMS_ILM package 5.2.2.8
- deleting ILM policies 5.2.2.4
- disabling ILM policies 5.2.2.4
- ILM ADO parameters 5.2.2.7
- limitations 5.2.3
- managing ILM policies 5.2.2.1
- managing with Oracle Enterprise Manager 5.5
- monitoring DBA and ILM policy views 5.2.2.9
- row-level compression tiering 5.2.2.6
- segment-level compression tiering 5.2.2.5
- views for ILM policies 5.2.2.9
- Automatic Data Optimization (ADO)
- for Information Lifecycle Management strategy 5.2.2
- automatic list partitioning
- creating tables using 4.1.4.3
C
- COALESCE PARTITION clause 4.4.2.1
- collections
- collection tables
- performing PMOs on partitions 4.1.17.1
- composite hash-hash partitioning 2.3.2.7
- composite hash-list partitioning 2.3.2.8
- composite hash partitioned tables
- creating 4.2.1
- composite hash-partitioned tables
- adding partitions 4.4.1.5
- composite hash-range partitioning 2.3.2.9
- composite interval partitioning
- creating tables using 4.2.2
- composite list-hash partitioning 2.3.2.5
- performance considerations 3.5.4.4
- composite list-list partitioning 2.3.2.6
- performance considerations 3.5.4.5
- composite list-partitioned tables
- adding partitions 4.4.1.6
- composite list partitioning
- creating tables using 4.2.3
- composite list-range partitioning 2.3.2.4
- performance considerations 3.5.4.6
- composite partitioned tables
- creating 4.2
- composite partitioning 2.3.2
- composite range-* partitioned tables
- creating 4.2.4
- composite range-hash partitioning 2.3.2.2
- performance considerations 3.5.4.1
- composite range-interval partitioning
- creating tables using 4.2.2
- composite range-list partitioned tables
- creating 4.2.4.2.1
- composite range-list partitioning 2.3.2.3
- performance considerations 3.5.4.2
- composite range-partitioned tables
- adding partitions 4.4.1.7
- composite range-range partitioning 2.3.2.1
- performance considerations 3.5.4.3
- compression
- partitioning 3.4
- compression table
- partitioning 3.4
- concurrent execution of union all 8.5.3.14
- constraints
- parallel create table 8.5.2.8
- consumer operations 8.1.4.2
- CREATE INDEX statement
- CREATE TABLE AS SELECT statement
- decision support system 8.5.2.2
- CREATE TABLE statement
- creating hash partitioned tables
- examples 4.1.3.1
- creating indexes on partitioned tables
- restrictions 2.5.5
- creating interval partitions
- INTERVAL clause of CREATE TABLE 4.1.2
- creating partitions 4.1
- creating segments on demand
- maintenance procedures 4.1.14.3
- critical consumer group
- specifying for parallel statement queuing 8.4.1.5
D
- data
- parallel DML restrictions and integrity rules 8.5.3.10
- databases
- database writer process (DBWn)
- tuning 8.8.4.6
- data loading
- incremental in parallel 8.8.7
- data manipulation language
- data segment compression
- data warehouses
- about 6.1
- advanced partition pruning 6.3.1.2
- ARCHIVELOG mode for recovery 9.4.1
- backing up and recovering 9.1
- backing up and recovering characteristics 9.1.1
- backing up tables on individual basis 9.4.7
- backup and recovery 9.3
- basic partition pruning 6.3.1.1
- block change tracking for backups 9.4.3
- data compression and partitioning 6.4.4
- differences with online transaction processing backups 9.1.1
- extract, transform, and load for backup and recovery 9.4.6.1
- extract, transform, and load strategy 9.4.6.2
- flashback database and guaranteed restore points 9.4.6.5
- incremental backups 9.4.6.3
- incremental backup strategy 9.4.6.4
- leverage read-only tablespaces for backups 9.4.5
- manageability 6.4
- manageability with partition exchange load 6.4.1
- materialized views and partitioning 6.3.4
- more complex queries 6.2.4
- more users querying the system 6.2.3
- NOLOGGING mode for backup and recovery 9.4.6
- partitioned tables 3.5.1
- partitioning 6
- partitioning and removing data from tables 6.4.3
- partitioning for large databases 6.2.1
- partitioning for large tables 6.2.2
- partitioning for scalability 6.2
- partitioning materialized views 6.3.4.1
- partition pruning 6.3.1
- recovery methodology 9.4
- recovery point object (RPO) 9.3.2
- recovery time object (RTO) 9.3.1
- refreshing table data 8.5.3.1.1
- RMAN for backup and recovery 9.4.2
- RMAN multi-section backups 9.4.4
- DB_BLOCK_SIZE initialization parameter
- parallel query 8.6.3.3.2
- DB_CACHE_SIZE initialization parameter
- parallel query 8.6.3.3.1
- DB_FILE_MULTIBLOCK_READ_COUNT initialization parameter
- parallel query 8.6.3.3.3
- DBMS_HEAT_MAP package
- subprograms for Heat MAP 5.2.1.3
- DBMS_ILM_ADMIN package
- Automatic Data Optimization 5.2.2.8
- DBMS_ILM package
- Automatic Data Optimization 5.2.2.8
- decision support system (DSS)
- default partitions 4.1.4.2
- default subpartition 4.2.4.2.2
- deferred segments
- partitioning 4.1.14.1
- degree of parallelism
- adaptive parallelism 8.2.6
- automatic 8.2.3
- between query operations 8.1.4.2
- controlling with initialization parameters and hints 8.2.5
- determining for auto DOP 8.2.4
- in-memory parallel execution 8.3
- manually specifying 8.2.1
- parallel execution servers 8.2
- specifying a limit for a consumer group 8.4.1.4
- DELETE statement
- parallel DELETE statement 8.5.3.3
- deleting ILM policies
- for Automatic Data Optimization 5.2.2.4
- direct-path INSERT
- restrictions 8.5.3.9
- DISABLE_PARALLEL_DML SQL hint 8.5.3.2
- DISABLE ROW MOVEMENT clause 4.1
- disabling ILM policies
- for Automatic Data Optimization 5.2.2.4
- DISK_ASYNCH_IO initialization parameter
- parallel query 8.6.3.3.4
- distributed transactions
- parallel DML restrictions 8.5.3.12
- DML_LOCKS
- parallel DML 8.6.3.2.3.3
- DROP PARTITION clause 4.4.3.1
- dropping multiple partitions 4.4.3.4
- dropping partitioned tables 4.5
- dropping partitions
- asynchronous global index maintenance 4.3.2
- DSS database
- partitioning indexes 3.3.7
E
- ENABLE_PARALLEL_DML SQL hint 8.5.3.2
- ENABLE ROW MOVEMENT clause 4.1, 4.1.1.2
- equipartitioning
- EXCHANGE PARTITION clause 4.4.4.8, 4.4.4.9, 4.4.4.10, 4.4.4.11
- EXCHANGE SUBPARTITION clause 4.4.4.7
- exchanging partitions
- extents
- parallel DDL statements 8.5.2.6
- extract, transform, and load
- data warehouses 9.4.6.1
F
G
H
- hardware-based mirroring
- very large databases (VLDBs) 10.1.1
- hardware-based striping
- very large databases (VLDBs) 10.2.1
- hash-partitioned tables
- adding partitions 4.4.1.2
- hash partitioning 2.3.1.2
- hash partitions
- splitting 4.4.12.4
- heap-organized partitioned tables
- table compression 4.1.12
- HEAT_MAP initialization parameter
- Heat Map
- ALL, DBA, USER, and V$ views 5.2.1.2
- and automatic data optimization 5.2
- disabling 5.2.1.1
- enabling 5.2.1.1
- for Information Lifecycle Management strategy 5.2.1
- limitations 5.2.3
- managing with DBMS_HEAT_MAP subprograms 5.2.1.3
- managing with Oracle Enterprise Manager 5.5
- viewing tracking information 5.2.1.2
- heat map and automatic data optimization
- implementing an ILM strategy 5.2
- hints
- parallel statement queuing 8.4.3
- Hybrid Columnar Compression
- example 3.4.2
- hybrid partitioned tables
I
- I/O
- ILM
- See: Information Lifecycle Management
- ILM policies
- for Automatic Data Optimization 5.2.2.1
- implementing an ILM system
- In-Database Archiving
- indexes
- advanced compression with partitioning 3.3.6
- creating in parallel 8.8.5
- global partitioned 6.3.3.3
- global partitioned indexes 3.3.2
- managing partitions 3.3.2.2
- local indexes 3.3.1
- local partitioned 6.3.3.1
- manageability with partitioning 6.4.2
- nonpartitioned 6.3.3.2
- parallel creation 8.8.5
- parallel DDL storage 8.5.2.6
- parallel local 8.8.5
- partitioned 6.3.3
- partitioning 3.3
- partitioning guidelines 3.3.7
- partitions 1.1
- updating automatically 4.3.1
- updating global indexes 4.3.1
- when to partition 2.1.3.2
- index-organized tables
- index partitions
- adding 4.4.1.9
- Information Lifecycle Management
- about 5.1
- and HEAT_MAP initialization parameter 5.2.1
- application transparency 5.1.1
- assigning classes to storage tiers 5.1.2.2.1
- auditing 5.1.2.4.4
- benefits of an online archive 5.1.1.3
- controlling access to data 5.1.2.3.1
- creating data access 5.1.2.3
- creating migration policies 5.1.2.3
- creating storage tiers 5.1.2.2
- data retention 5.1.2.4.1
- defining compliance policies 5.1.2.4
- defining data classes 5.1.2.1
- enforceable compliance policies 5.1.1
- enforcing compliance policies 5.1.2.4
- expiration 5.1.2.4.5
- fine-grained 5.1.1
- heat map and automatic data optimization 5.2
- immutability 5.1.2.4.2
- implemented with Automatic Data Optimization 5.2.2
- implementing a system manually with partitioning 5.4
- implementing using Oracle Database 5.1.2
- implementing with Heat Map 5.2.1
- introduction 5
- lifecycle of data 5.1.2.1.2
- limitations 5.2.3
- low-cost storage 5.1.1
- moving data using partitioning 5.1.2.3.2
- Oracle Database, and 5.1.1
- partitioning 5.1.2.1.1
- partitioning, and 1.3
- privacy 5.1.2.4.3
- regulatory requirements 5.1.1.2
- striping 10.2.3
- structured and unstructured data 5.1.1.1
- time-based information 5
- initialization parameters
- MEMORY_MAX_TARGET 8.6.3.2
- MEMORY_TARGET 8.6.3.2
- PARALLEL_EXECUTION_MESSAGE_SIZE 8.6.3.2.1, 8.6.3.2.2
- PARALLEL_FORCE_LOCAL 8.6.3.1.1
- PARALLEL_MAX_SERVERS 8.6.3.1.2
- PARALLEL_MIN_PERCENT 8.6.3.1.3
- PARALLEL_MIN_SERVERS 8.1.5, 8.6.3.1.4
- PARALLEL_MIN_TIME_THRESHOLD 8.6.3.1.5
- PARALLEL_SERVERS_TARGET 8.6.3.1.6
- SHARED_POOL_SIZE 8.6.3.1.7
- INSERT statement
- parallelizing INSERT SELECT 8.5.3.4
- instance groups
- integrity rules
- parallel DML restrictions 8.5.3.10
- interval-hash partitioning
- interval-list partitioning
- interval partitioned tables
- dropping partitions 4.4.3.2
- interval-partitioned tables
- interval partitioning
- interval-range partitioning
- creating tables using 4.2.2.3
- interval-reference partitioned tables
- creating 4.1.6
L
M
- maintenance operations
- maintenance operations on partitions
- filtering 4.3.4
- manageability
- data warehouses 6.4
- managing data validity
- Temporal Validity 5.3.2
- managing data visibility
- In-Database Archiving 5.3.1
- managing ILM policies
- for Automatic Data Optimization 5.2.2.1
- memory
- configure at 2 levels 8.6.3.2
- MEMORY_MAX_TARGET initialization parameter 8.6.3.2
- MEMORY_TARGET initialization parameter 8.6.3.2
- MERGE PARTITION clause 4.4.5
- MERGE statement
- parallel MERGE statement 8.5.3.3
- MERGE SUBPARTITION clause 4.4.5
- merging multiple partitions 4.4.5.7
- MINIMUM EXTENT parameter 8.5.2.6
- mirroring with Oracle ASM
- very large databases (VLDBs) 10.1.2
- MODIFY DEFAULT ATTRIBUTES clause 4.4.6.2.1
- using for partitioned tables 4.4.6.1.1
- MODIFY DEFAULT ATTRIBUTES FOR PARTITION clause 4.4.6.1.2
- of ALTER TABLE statement 4.4.6.1.3
- modifying
- partitioning 4.4.8
- MODIFY PARTITION clause 4.4.6.2.1, 4.4.6.2.2, 4.4.9, 4.4.10.2.2
- MODIFY SUBPARTITION clause 4.4.6.2.3
- monitoring
- MOVE PARTITION clause 4.4.6.2, 4.4.9
- MOVE SUBPARTITION clause 4.4.6.2, 4.4.9.2
- multi-column list partitioning
- creating tables using 4.1.4.4
- multiple archiver processes 8.8.4.5
- multiple block sizes
- restrictions on partitioning 4.1.16
- multiple parallelizers 8.1.7
- multiple partitions
N
- NO_STATEMENT_QUEUING
- parallel statement queuing hint 8.4.3
- NOLOGGING clause 8.8.4.7
- NOLOGGING mode
- nonpartitioned indexes 6.3.3.2
- nonpartitioned tables
- changing to partitioned tables 4.6
- non-partitioned tables
- converting to partitioned tables 4.6.2
- nonprefixed indexes 2.5.2, 3.3.1.2
- global partitioned indexes 3.3.2.1
- nonprefixed indexes_importance 3.3.4
O
- object types
- of ALTER TABLE statement 4.4.6.1.2
- OLTP database
- Online Transaction Processing (OLTP)
- operating system statistics
- monitoring for parallel processing 8.7.4
- operations
- partition-wise 3.2
- optimization
- optimizations
- parallel SQL 8.1.4.1
- ORA_ARCHIVE_STATE
- In-Database Archiving 5.3.1
- Oracle Automatic Storage Management settings
- very large databases (VLDBs) 10.4
- Oracle Database File System
- very large databases (VLDBs) 10.2.6
- Oracle Database Resource Manager
- managing parallel statement queue 8.4.1
- Oracle Real Application Clusters
- instance groups 8.1.8
P
- PARALLEL_DEGREE_POLICY initialization parameter
- PARALLEL_EXECUTION_MESSAGE_SIZE initialization parameter 8.6.3.2.1, 8.6.3.2.2
- PARALLEL_FORCE_LOCAL initialization parameter 8.6.3.1.1
- PARALLEL_MAX_SERVERS initialization parameter 8.6.3.1.2
- parallel execution 8.6.3.1.2
- PARALLEL_MIN_PERCENT initialization parameter 8.6.3.1.3
- PARALLEL_MIN_SERVERS initialization parameter 8.1.5, 8.6.3.1.4
- PARALLEL_MIN_TIME_THRESHOLD initialization parameter 8.6.3.1.5
- PARALLEL_SERVERS_TARGET initialization parameter 8.6.3.1.6
- PARALLEL clause 8.8.6.1
- parallel DDL statements 8.5.2
- parallel delete 8.5.3.3
- parallel DELETE statement 8.5.3.3
- parallel DML
- considerations for parallel execution 8.8.4
- parallel DML and DDL statements
- functions 8.5.4.2
- parallel DML operations 8.5.3
- parallel execution
- about 8, 8.1, 8.1.4
- adaptive parallelism 8.2.6
- bandwidth 8.1.1
- benefits 8.1.1
- considerations for parallel DML 8.8.4
- CPU utilization 8.1.1
- CREATE TABLE AS SELECT statement 8.8.2
- DB_BLOCK_SIZE initialization parameter 8.6.3.3.2
- DB_CACHE_SIZE initialization parameter 8.6.3.3.1
- DB_FILE_MULTIBLOCK_READ_COUNT initialization parameter 8.6.3.3.3
- default parameter settings 8.6.1
- DISK_ASYNCH_IO initialization parameter 8.6.3.3.4
- forcing for a session 8.6.2
- full table scans 8.1.2
- functions 8.5.4
- fundamental hardware requirements 8.1.3
- I/O 8.1.1
- I/O parameters 8.6.3.3
- index creation 8.8.5
- initializing parameters 8.6
- in-memory 8.3
- inter-operator parallelism 8.1.4.2
- intra-operator parallelism 8.1.4.2
- massively parallel systems 8.1.1
- new features ,
- Oracle RAC 8.1.8
- parallel load 8.5.5
- parallel propagation 8.5.5
- parallel recovery 8.5.5
- parallel replication 8.5.5
- parameters for establishing resource limits 8.6.3.1
- resource parameters 8.6.3.2
- symmetric multiprocessors 8.1.1
- TAPE_ASYNCH_IO initialization parameter 8.6.3.3.4
- tips for tuning 8.8
- tuning general parameters 8.6.3
- tuning parameters 8.6
- using 8
- when not to use 8.1.2
- parallel execution strategy
- implementing 8.8.1
- PARALLEL hint
- UPDATE, MERGE, and DELETE 8.5.3.3
- parallelism
- parallelization
- parallel partition-wise joins
- performance considerations 6.3.2.4
- parallel processing
- parallel queries 8.5.1
- parallel query
- parallel server resources
- limiting for a consumer group 8.4.1.2
- parallel servers
- asynchronous communication 8.1.4.5
- parallel SQL
- parallel statement queue
- about 8.4
- grouping parallel statements 8.4.2
- hints 8.4.3
- limiting parallel server resources 8.4.1.2
- managing for consumer groups 8.4.1
- managing the order of dequeuing 8.4.1.1
- managing with Oracle Database Resource Manager 8.4.1
- NO_STATEMENT_QUEUING hint 8.4.3
- PARALLEL_DEGREE_POLICY 8.4
- sample scenario for managing parallel statements 8.4.1.6
- setting order of parallel statements 8.4.1
- specifying a critical consumer group 8.4.1.5
- specifying a DOP limit for a consumer group 8.4.1.4
- specifying a timeout for a consumer group 8.4.1.3
- STATEMENT_QUEUING hint 8.4.3
- using BEGIN_SQL_BLOCK to group statements 8.4.2
- parallel update 8.5.3.3
- parallel UPDATE statement 8.5.3.3
- parameters
- Automatic Data Optimization 5.2.2.7
- partial indexes
- on partitioned tables 2.5.6
- partial partition-wise joins 6.3.2.2
- PARTITION_START
- partition pruning 3.1.3
- PARTITION_STOP
- partition pruning 3.1.3
- Partition Advisor
- manageability 2.4.1.2
- partition bound
- range-partitioned tables 4.1.1.1
- PARTITION BY HASH clause 4.1.3
- PARTITION BY LIST clause 4.1.4
- PARTITION BY RANGE clause 4.1.1
- for composite-partitioned tables 4.2
- PARTITION BY REFERENCE clause 4.1.5
- PARTITION clause
- partitioned external tables
- creating 4.1.9
- partitioned indexes
- about 2.5
- adding partitions 4.4.1.9
- administration 4
- composite partitions 2.5.7
- creating hash-partitioned global 4.1.3.2
- creating local index on composite partitioned table 4.2.4.1.3
- creating local index on hash partitioned table 4.1.3.1
- creating range partitions 4.1.1.3
- dropping partitions 4.4.3.3
- key compression 4.1.13
- maintenance operations 4.3, 4.4
- maintenance operations that can be performed 4.3
- modifying partition default attributes 4.4.6.1.3
- modifying real attributes of partitions 4.4.6.2.4
- moving partitions 4.4.9.3
- Online Transaction Processing (OLTP) 7.2.1
- rebuilding index partitions 4.4.10
- renaming index partitions/subpartitions 4.4.11.3
- secondary indexes on index-organized tables 4.1.15.1
- splitting partitions 4.4.12.7
- views 4.8
- which type to use 2.5.1
- partitioned tables
- adding partitions 4.4.1
- adding subpartitions 4.4.1.5.2, 4.4.1.6.2, 4.4.1.7.2
- administration 4
- coalescing partitions 4.4.2
- converting to from non-partitioned tables 4.6.2
- creating automatic list partitions 4.1.4.3
- creating composite 4.2
- creating composite interval 4.2.2
- creating composite list 4.2.3
- creating hash partitions 4.1.3
- creating interval-hash partitions 4.2.2.1
- creating interval-list partitions 4.2.2.2
- creating interval partitions 4.1.2
- creating interval-range partitions 4.2.2.3
- creating list-hash partitions 4.2.3.1
- creating list-list partitions 4.2.3.2
- creating list partitions 4.1.4
- creating list-range partitions 4.2.3.3
- creating multi-column list partitions 4.1.4.4
- creating range-hash partitions 4.2.4.1
- creating range-list partitions 4.2.4.2
- creating range partitions 4.1.1, 4.1.1.3
- creating range-range partitions 4.2.4.3
- creating reference partitions 4.1.5
- data warehouses 3.5.1
- DISABLE ROW MOVEMENT 4.1
- dropping 4.5
- dropping partitions 4.4.3
- ENABLE ROW MOVEMENT 4.1
- exchanging partitions and subpartitions 4.4.4
- exchanging partitions of a referenced-partition table 4.4.4.4
- exchanging partitions with a cascade option 4.4.4.12
- exchanging subpartitions 4.4.4.7, 4.4.4.9, 4.4.4.11
- filtering maintenance operations 4.3.4
- FOR EXCHANGE WITH 4.4.4.1
- global indexes 7.3.2
- incremental statistics and partition exchange operations 4.4.4
- index-organized tables 4.1, 4.1.15.1, 4.1.15.2, 4.1.15.3
- in-memory column store 4.1.7
- INTERVAL clause of CREATE TABLE 4.1.2
- interval-reference 4.1.6
- local indexes 7.3.1
- maintenance operations 4.4
- maintenance operations that can be performed 4.3
- maintenance operations with global indexes 7.3.2
- maintenance operations with local indexes 7.3.1
- marking indexes UNUSABLE 4.4.12
- merging partitions 4.4.5
- modifying default attributes 4.4.6.1
- modifying real attributes of partitions 4.4.6.2
- modifying real attributes of subpartitions 4.4.6.2.3
- moving partitions 4.4.9
- moving subpartitions 4.4.9.2
- multicolumn partitioning keys 4.1.10
- partition bound 4.1.1.1
- partitioning columns 4.1.1.1
- partitioning keys 4.1.1.1
- read-only status 4.1.8
- rebuilding index partitions 4.4.10
- redefining partitions online 4.6.1
- renaming partitions 4.4.11
- renaming subpartitions 4.4.11.2
- splitting partitions 4.4.12
- truncating partitions 4.4.13
- truncating partitions with the cascade option 4.4.13.4
- truncating subpartitions 4.4.13.3
- updating global indexes automatically 4.3.1
- views 4.8
- partition exchange load
- manageability 6.4.1
- partition granules 8.1.4.3.2
- partitioning
- about 1.1
- administration of indexes 4
- administration of tables 4
- advanced index compression 3.3.6
- advantages 1.1
- availability 2.2.3, 3
- basics 2.1.1
- benefits 2.2
- bitmap indexes 3.4.1
- collections in XMLType and object data 2.1.11
- composite 2.3.2
- composite list-hash 2.3.2.5
- composite list-list 2.3.2.6
- composite list-range 2.3.2.4
- composite range-hash 2.3.2.2
- composite range-list 2.3.2.3
- composite range-range 2.3.2.1
- concepts 2
- creating a partitioned index 4.1
- creating a partitioned table 4.1
- creating indexes on partitioned tables 2.5.5
- databases, and 1.4
- data segment compression 3.4, 3.4.1
- data segment compression example 3.4.2
- data warehouses 6
- data warehouses and scalability 6.2
- default partition 4.1.4.2
- default subpartition 4.2.4.2.2
- deferred segments 4.1.14.1
- EXCHANGE PARTITION clause 4.4.4.2
- exchanging a hash partitioned table 4.4.4.6
- exchanging a range partitioned table 4.4.4.10
- exchanging interval partitions 4.4.4.3
- extensions 2.4
- global hash partitioned indexes 2.5.3.2
- global indexes 3.3.2
- global nonpartitioned indexes 2.5.4
- global partitioned indexes 2.5.3
- global range partitioned indexes 2.5.3.1
- guidelines for indexes 3.3.7
- hash 2.3.1.2
- Hybrid Columnar Compression example 3.4.2
- indexes 2.1.3.2, 2.5, 3.3
- index-organized tables 2.1.4, 4.1, 4.1.15.1, 4.1.15.2, 4.1.15.3
- Information Lifecycle Management 2.1.6
- Information Lifecycle Management, and 1.3
- interval 2.4.1.1, 2.4.1.2
- interval-hash 4.2.2.1
- interval-list 4.2.2.2
- interval-range 4.2.2.3
- key 2.1.2
- key extensions 2.4.2
- list 2.3.1.3, 4.4.7.1, 4.4.7.2
- list-hash 4.2.3.1
- list-list 4.2.3.2
- list-range 4.2.3.3
- LOB data 2.1.8
- local indexes 3.3.1
- local partitioned indexes 2.5.2
- maintaining partitions 4.4
- maintenance procedures for segment creation 4.1.14.3
- manageability 2.2.2, 3
- manageability extensions 2.4.1
- manageability with indexes 6.4.2
- managing partitions 3.3.2.2
- modifying attributes 4.4.6
- modifying list partitions 4.4.7
- modifying the strategy 4.4.8
- new features ,
- nonprefixed indexes 3.3.1.2, 3.3.2.1, 3.3.4
- Online Transaction Processing (OLTP) 7
- overview 2, 2.1
- partial indexes on partitioned tables 2.5.6
- Partition Advisor 2.4.1.2
- partitioned indexes on composite partitions 2.5.7
- partition-wise joins 2.2.1.2
- performance 2.2.1, 3, 3.5
- performance considerations 3.5
- performance considerations for composite 3.5.4
- performance considerations for composite list-hash 3.5.4.4
- performance considerations for composite list-list 3.5.4.5
- performance considerations for composite list-range 3.5.4.6
- performance considerations for composite range-hash 3.5.4.1
- performance considerations for composite range-list 3.5.4.2
- performance considerations for composite range-range 3.5.4.3
- performance considerations for hash 3.5.2
- performance considerations for interval 3.5.5
- performance considerations for list 3.5.3
- performance considerations for range 3.5.6
- performance considerations for virtual columns 3.5.7
- placement with striping 10.2.4
- prefixed indexes 3.3.1.1, 3.3.2.1
- pruning 2.2.1.1, 3.1
- range 2.3.1.1
- range-hash 4.2.4.1
- range-list 4.2.4.2
- range-range 4.2.4.3
- reference 2.4.2.1
- removing data from tables 6.4.3
- restrictions for multiple block sizes 4.1.16
- segments 4.1.14
- single-level 2.3.1
- strategies 2.3, 3.5
- subpartition templates 4.2.5
- system 2.1.5, 2.4, 2.4.1, 2.4.2
- tables 2.1.3, 2.1.3.1
- truncating segments 4.1.14.2
- type of index to use 2.5.1
- very large databases (VLDBs), and 1.2
- virtual columns 2.4.2.2
- partitioning and data compression
- data warehouses 6.4.4
- partitioning and materialized views
- data warehouses 6.3.4
- partitioning columns
- range-partitioned tables 4.1.1.1
- partitioning keys
- range-partitioned tables 4.1.1.1
- partitioning materialized views
- data warehouses 6.3.4.1
- partitioning of XMLIndex
- binary XML tables 4.1.17.2
- partition maintenance operations 7.3.1, 7.3.2
- partition pruning
- about 3.1
- benefits 3.1.1
- collection tables 3.1.7.3
- data type conversions 3.1.7.1
- dynamic 3.1.5
- dynamic with bind variables 3.1.5.1
- dynamic with nested loop joins 3.1.5.4
- dynamic with star transformation 3.1.5.3
- dynamic with subqueries 3.1.5.2
- function calls 3.1.7.2
- identifying 3.1.3
- information for pruning 3.1.2
- PARTITION_START 3.1.3
- PARTITION_STOP 3.1.3
- static 3.1.4
- tips and considerations 3.1.7
- with zone maps 3.1.6
- partitions 1.1
- advanced index compression 3.3.6
- equipartitioning
- global indexes 3.3.2, 6.3.3.3
- guidelines for partitioning indexes 3.3.7
- indexes 3.3
- local indexes 3.3.1, 6.3.3.1
- nonprefixed indexes 2.5.2, 3.3.1.2, 3.3.4
- on indexes 6.3.3
- parallel DDL statements 8.5.2.1
- physical attributes 3.3.8
- prefixed indexes 3.3.1.1
- PARTITIONS clause
- for hash partitions 4.1.3
- partition-wise joins 3.2
- partition-wise operations 3.2
- performance
- predicates
- index partition pruning 3.3.5
- prefixed indexes 3.3.1.1, 3.3.3
- partition pruning 3.3.5
- processes
- memory contention in parallel processing 8.6.3.1.2
- process monitor process (PMON)
- parallel DML process recovery 8.5.3.7.2
- producer operations 8.1.4.2
- pruning partitions
R
- range-hash partitioning
- range-list partitioning
- range-partitioned tables
- range partitioning 2.3.1.1
- range-range partitioning
- creating tables using 4.2.4.3
- read-only status
- tables, partitions, and subpartitions 4.1.8
- read-only tablespaces
- performance considerations 3.5.8
- REBUILD PARTITION clause 4.4.9.3, 4.4.10.2.1
- REBUILD UNUSABLE LOCAL INDEXES clause 4.4.10.2.2
- recovery
- parallel DML operations 8.5.3.7
- reference-partitioned tables
- adding partitions 4.4.1.8
- reference partitioning
- RENAME PARTITION clause 4.4.11.1, 4.4.11.3.1
- RENAME SUBPARTITION clause 4.4.11.2
- replication
- restrictions on parallel DML 8.5.3.9
- resources
- restrictions
- ROW ARCHIVAL VISIBILITY
- In-Database Archiving 5.3.1
- row-level compression tiering
- Automatic Data Optimization 5.2.2.6
- row movement clause for partitioned tables 4.1
S
- scalability
- scalability and manageability
- very large databases (VLDBs) 10.3
- scans
- parallel query on full table 8.1.2
- segment-level compression tiering
- Automatic Data Optimization 5.2.2.5
- segments
- sessions
- enabling parallel DML operations 8.5.3.2
- session statistics
- monitoring for parallel processing 8.7.2
- SET INTERVAL clause 4.4.1.4
- SHARED_POOL_SIZE initialization parameter 8.6.3.1.7
- single-level partitioning 2.3.1
- skewing parallel DML workload 8.1.6
- SORT_AREA_SIZE initialization parameter
- parallel execution 8.6.3.2.1.2
- space management
- SPLIT PARTITION clause 4.4.1.1, 4.4.12
- SPLIT PARTITION operations
- optimizing 4.4.12.9
- SPLIT SUBPARTITION operations
- optimizing 4.4.12.9
- splitting multiple partitions 4.4.12.8
- splitting partitions and subpartitions 4.4.12
- SQL statementsSQL statements
- STATEMENT_QUEUING
- parallel statement queuing hint 8.4.3
- statistics
- operating system 8.7.4
- storage
- STORAGE clause
- parallel execution 8.5.2.5
- storage management
- very large databases (VLDBs) 10
- STORE IN clause
- partitions 4.2.4.1.2
- stripe and mirror everything
- very large databases (VLDBs) 10.3.1
- striping
- striping with Oracle ASM
- very large databases (VLDBs) 10.2.2
- SUBPARTITION BY HASH clause
- for composite-partitioned tables 4.2
- SUBPARTITION clause 4.4.1.5.1, 4.4.1.6.1, 4.4.1.7.1, 4.4.12.4
- for composite-partitioned tables 4.2
- SUBPARTITIONS clause 4.4.1.5.1, 4.4.12.4
- for composite-partitioned tables 4.2
- subpartition templates 4.2.5
- modifying 4.3.3
- subqueries
- in DDL statements 8.5.2.2
- system monitor process (SMON)
- parallel DML system recovery 8.5.3.7.3
- system partitioning 2.1.5
- system statistics
- monitoring for parallel processing 8.7.3
T
- table compression
- partitioning 4.1.12
- table queues
- monitoring parallel processing 8.7.1.7
- tables
- creating and populating in parallel 8.8.2
- creating composite partitioned 4.2
- full partition-wise joins 3.2.1, 6.3.2.1
- historical 8.5.3.1.4
- index-organized, partitioning 4.1.15
- parallel creation 8.5.2.2
- parallel DDL storage 8.5.2.6
- partial partition-wise joins 3.2.2, 6.3.2.2
- partitioning 2.1.3
- partitions 1.1
- refreshing in data warehouse 8.5.3.1.1
- STORAGE clause with parallel execution 8.5.2.5
- summary 8.5.2.2
- when to partition 2.1.3.1
- tables for exchange
- with partitioned tables 4.4.4.1
- TAPE_ASYNCH_IO initialization parameter
- parallel query 8.6.3.3.4
- temporal validity
- creating a table with 5.3.3
- Temporal Validity
- temporary segments
- parallel DDL 8.5.2.6
- time-based information
- Information Lifecycle Management 5
- transactions
- distributed and parallel DML restrictions 8.5.3.12
- triggers
- TRUNCATE PARTITION clause 4.4.13, 4.4.13.1, 4.4.13.1.1
- TRUNCATE SUBPARTITION clause 4.4.13.3
- truncating multiple partitions 4.4.13.2
- truncating partitions
- truncating segments
- partitioning 4.1.14.2
- two-phase commit 8.6.3.2.3.1
- types of parallelism 8.5
V
- V$PQ_SESSTAT view
- monitoring parallel processing 8.7.1.6
- V$PQ_TQSTAT view
- monitoring parallel processing 8.7.1.7
- V$PX_BUFFER_ADVICE view
- monitoring parallel processing 8.7.1.1
- V$PX_PROCESS_SYSSTAT view
- monitoring parallel processing 8.7.1.5
- V$PX_PROCESS view
- monitoring parallel processing 8.7.1.4
- V$PX_SESSION view
- monitoring parallel processing 8.7.1.2
- V$PX_SESSTAT view
- monitoring parallel processing 8.7.1.3
- V$RSRC_CONS_GROUP_HISTORY view
- monitoring parallel processing 8.7.1.8
- V$RSRC_CONSUMER_GROUP view
- monitoring parallel processing 8.7.1.9
- V$RSRC_PLAN_HISTORY view
- monitoring parallel processing 8.7.1.11
- V$RSRC_PLAN view
- monitoring parallel processing 8.7.1.10
- V$RSRC_SESSION_INFO view
- parallel statement queuing metrics 8.7.1.12
- V$RSRCMGRMETRIC view
- parallel statement queuing statistics 8.7.1.13
- V$SESSTAT view 8.7.4
- V$SYSSTAT view 8.8.4.6
- valid-time period
- Temporal Validity 5.3.2
- very large databases (VLDBs)
- about 1
- backing up and recovering 9
- backup tools 9.2.3
- backup types 9.2.2
- bigfile tablespaces 10.2.5
- database structures for recovering data 9.2.1
- hardware-based mirroring 10.1.1
- hardware-based striping 10.2.1
- high availability 10.1
- introduction 1
- mirroring with Oracle ASM 10.1.2
- new features ,
- Oracle Automatic Storage Management settings 10.4
- Oracle Backup and Recovery 9.2
- Oracle Database File System 10.2.6
- Oracle Data Pump 9.2.3, 9.2.3.2
- Oracle Recovery Manager 9.2.3.1
- partitioning, and 1.2
- performance 10.2
- physical and logical backups 9.2.2
- RAID 0 striping 10.2.1.1
- RAID 1 mirroring 10.1.1.1
- RAID 5 mirroring 10.1.1.2
- RAID 5 striping 10.2.1.2
- RMAN 9.2.3
- scalability and manageability 10.3
- storage management 10
- stripe and mirror everything 10.3.1
- striping with Oracle ASM 10.2.2
- user-managed backups 9.2.3, 9.2.3.3
- views
- views for ILM policies
- Automatic Data Optimization 5.2.2.9
- virtual column-based partitioning
- virtual column partitioning
- performance considerations 3.5.7
- VLDBs
- very large databases 1