Index

A B C D E F G H I J K L M N O P Q R S T U V W X

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
- ENABLE PARALLEL DML clause 8.5.3.2
- FORCE PARALLEL DDL clause 8.5.1.5, 8.5.2.7
- FORCE PARALLEL DML clause 8.5.3.3, 8.5.3.4
ALTER TABLE statement
- MODIFY DEFAULT ATTRIBUTES clause 4.4.6.1.1
- MODIFY DEFAULT ATTRIBUTES FOR PARTITION clause 4.4.6.1.2, 4.4.6.1.3
applications
- decision support system (DSS)
  - parallel SQL 8.5.2.2
- direct-path INSERT 8.5.3.1.4
- parallel DML operations 8.5.3.1
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

B

backing up and recovering
- very large databases (VLDBs) 9
bigfile tablespaces
- very large databases (VLDBs) 10.2.5
binary XML tables
- partitioning of XMLIndex 4.1.17.2

C

COALESCE PARTITION clause 4.4.2.1
collections
- tables 4.1.17.1
- XMLType 2.1.10, 4.1.17
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
- default partition 4.2.4.2.2
- interval-hash 4.2.2.1
- interval-list 4.2.2.2
- interval-range 4.2.2.3
- list-hash 4.2.3.1
- list-list 4.2.3.2
- list-range 4.2.3.3
- performance considerations 3.5.4
- range-hash 4.2.4.1
- range-list 4.2.4.2
- range-range 4.2.4.3
- subpartition template, modifying 4.3.3
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
- partition attributes 3.3.8
- partitioned indexes 4.1.1.3
CREATE TABLE AS SELECT statement
- decision support system 8.5.2.2
CREATE TABLE statement
- AS SELECT
  - rules of parallelism 8.5.2.8
  - space fragmentation 8.5.2.6
  - temporary storage space 8.5.2.5
- parallelism 8.5.2.2
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
- partitioning, and 1.4
- scalability 8.5.3.1
database writer process (DBWn)
- tuning 8.8.4.6
data loading
- incremental in parallel 8.8.7
data manipulation language
- parallel DML operations 8.5.3
- transaction model for parallel DML operations 8.5.3.5
data segment compression
- bitmap indexes 3.4.1
- example 3.4.2
- partitioning 3.4
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)
- parallel DML operations 8.5.3.1
- parallel SQL 8.5.2.2, 8.5.3.1
- performance 8.5.3.1
- scoring tables 8.5.3.1.3
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
- examples 3.3.1.1
- local indexes 3.3.1
EXCHANGE PARTITION clause 4.4.4.8, 4.4.4.9, 4.4.4.10, 4.4.4.11, 4.4.5
EXCHANGE SUBPARTITION clause 4.4.4.7
exchanging partitions
- cascade option 4.4.4.12
extents
- parallel DDL statements 8.5.2.6
extract, transform, and load
- data warehouses 9.4.6.1

F

features
- new for Information Lifecycle Management
- new for parallel execution
- new for partitioning
- new for VLDBs
filtering
- maintenance operations on partitions 4.3.4
FOR PARTITION clause 4.4.6.2.1
fragmentation
- parallel DDL 8.5.2.6
full partition-wise join
- querying 3.2.1.1
full partition-wise joins 3.2.1, 6.3.2.1
- composite - composite 3.2.1.4
- composite - single-level 3.2.1.3
- single-level - single-level 3.2.1.2
full table scans
- parallel execution 8.1.2
functions
- parallel DML and DDL statements 8.5.4.2
- parallel execution 8.5.4
- parallel queries 8.5.4.1

G

global hash partitioned indexes
- about 2.5.3.2
global indexes
- partitioning 3.3.2, 3.3.2.2
  - summary of index types 3.3.3
global nonpartitioned indexes
- about 2.5.4
global partitioned indexes
- about 2.5.3
- maintenance 2.5.3.3
global range partitioned indexes
- about 2.5.3.1
granuless
- parallelism 8.1.4.3
groups
- instance 8.1.8

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
- creating global indexes 4.1.3.2
- creating tables examples 4.1.3.1
- creating tables using 4.1.3
- index-organized tables 4.1.15.2
- multicolumn partitioning keys 4.1.10
- performance considerations 3.5.2
hash partitions
- splitting 4.4.11.4
heap-organized partitioned tables
- table compression 4.1.12
HEAT_MAP initialization parameter
- disabling 5.2.1.1
- enabling 5.2.1.1
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

I

I/O
- asynchronous 8.6.3.3.4
- parallel execution 8.1.1
ILM
- See: Information Lifecycle Management
ILM policies
- for Automatic Data Optimization 5.2.2.1
implementing an ILM system
- manually with partitioning 5.4
- using Oracle Database 5.1.2
In-Database Archiving
- limitations 5.3.4
- managing data visibility 5.3.1
- ORA_ARCHIVE_STATE 5.3.1
- ROW ARCHIVAL VISIBILITY 5.3.1
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
- hash-partitioned 4.1.15.2
- list-partitioned 4.1.15.3
- parallel queries 8.5.1.1
- partitioning 4.1, 4.1.15
- partitioning secondary indexes 4.1.15.1
- range-partitioned 4.1.15.1
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
Information Lifecycle Management (ILM)
- new features
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
- for parallel operations 8.1.8
- limiting the number of instances 8.1.8
integrity rules
- parallel DML restrictions 8.5.3.10
interval-hash partitioning
- creating tables using 4.2.2.1
- subpartitioning template 4.2.5.1
interval-list partitioning
- creating tables using 4.2.2.2
- subpartitioning template 4.2.5.2
interval partitioned tables
- dropping partitions 4.4.3.2
interval-partitioned tables
- adding partitions 4.4.1.4
- splitting partitions 4.4.11.3
interval partitioning
- creating tables using 4.1.2
- manageability 2.4.1.1
- performance considerations 3.5.1, 3.5.5
interval-range partitioning
- creating tables using 4.2.2.3
interval-reference partitioned tables
- creating 4.1.6

J

joins
- full partition-wise 3.2.1
- partial partition-wise 3.2.2
- partition-wise 3.2

K

key compression
- partitioning indexes 4.1.13

L

list-hash partitioning
- creating tables using 4.2.3.1
- subpartitioning template 4.2.5.1
list-list partitioning
- creating tables using 4.2.3.2
- subpartitioning template 4.2.5.2
list-partitioned tables
- adding partitions 4.4.1.3
- creating 4.1.4, 4.1.4.1
- splitting partitions 4.4.11.2, 4.4.11.5
list partitioning 2.3.1.3
- adding values to value list 4.4.7.1
- creating tables using 4.1.4
- dropping values from value-list 4.4.7.2
- index-organized tables 4.1.15.3
- modifying 4.4.7
- performance considerations 3.5.3
list-range partitioning
- creating tables using 4.2.3.3
LOB data types
- restrictions on parallel DDL statements 8.5.2.1
- restrictions on parallel DML operations 8.5.3.9
local indexes 3.3.1, 3.3.3
- equipartitioning 3.3.1
local partitioned indexes
- about 2.5.2
LOGGING clause 8.8.4.7
logging mode
- parallel DDL 8.5.2.1, 8.5.2.3

M

maintenance operations
- supported on index partitions 4.3
- supported on partitioned tables 4.3
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 statement
- parallel MERGE statement 8.5.3.3
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
MODIFY PARTITION clause 4.4.6.2.1, 4.4.6.2.2, 4.4.8, 4.4.9.2.2
MODIFY SUBPARTITION clause 4.4.6.2.3
monitoring
- parallel processing 8.7, 8.7.1
MOVE PARTITION clause 4.4.6.2, 4.4.8
MOVE SUBPARTITION clause 4.4.6.2, 4.4.8.2
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
- adding 4.4.1.10
- dropping 4.4.3.4
- merging 4.4.5.7
- splitting 4.4.11.8
- truncating 4.4.12.4
multitenant container databases
- parallel statement queuing 8.4.1.6

N

NO_STATEMENT_QUEUING
- parallel statement queuing hint 8.4.3
NOLOGGING clause 8.8.4.7
NOLOGGING mode
- parallel DDL 8.5.2.1, 8.5.2.3
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
- parallel queries 8.5.1.4
- restrictions on parallel DDL statements 8.5.2.1
- restrictions on parallel DML operations 8.5.3.9
- restrictions on parallel queries 8.5.1.4
of ALTER TABLE statement 4.4.6.1.2
OLTP database
- batch jobs 8.5.3.1.5
- parallel DML operations 8.5.3.1
- partitioning indexes 3.3.7
Online Transaction Processing (OLTP)
- about 7.1
- common partition maintenance operations 7.3.3
- partitioning, and 7
- when to partition indexes 7.2.1
operating system statistics
- monitoring for parallel processing 8.7.4
optimization
- partitioned indexes 3.3.5
- partition pruning and indexes 3.3.5
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
- automatic degree of parallelism 8.2.3
- controlling automatic DOP 8.2.5
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
- extent allocation 8.5.2.6
- partitioned tables and indexes 8.5.2.1
- restrictions on LOBs 8.5.2.1
- restrictions on object types 8.5.1.4, 8.5.2.1
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
- applications 8.5.3.1
- enabling PARALLEL DML 8.5.3.2
- recovery 8.5.3.7
- restrictions 8.5.3.9
- restrictions on LOB data types 8.5.3.9
- restrictions on object types 8.5.1.4, 8.5.3.9
- restrictions on remote transactions 8.5.3.12
- transaction model 8.5.3.5
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
- about 8.1.4
- adaptive 8.2.6
- degree 8.2
- inter-operator 8.1.4.2
- intra-operator 8.1.4.2
- other types 8.5
- parallel DDL statements 8.5
- parallel DML operations 8.5
- parallel execution of functions 8.5
- parallel queries 8.5
- types 8.5
parallelization
- methods for specifying precedence 8.5.6
- rules for SQL operations 8.5.6
parallel partition-wise joins
- performance considerations 6.3.2.4
parallel processing
- monitoring 8.7
- monitoring operating system statistics 8.7.4
- monitoring session statistics 8.7.2
- monitoring system statistics 8.7.3
- monitoring with GV$FILESTAT view 8.7.1
- monitoring with performance views 8.7.1
parallel queries 8.5.1
- functions 8.5.4.1
- index-organized tables 8.5.1.1
- object types 8.5.1.4
- restrictions on object types 8.5.1.4
parallel query
- integrating with the automatic big table caching 8.3.2
- parallelism type 8.5.1
parallel server resources
- limiting for a consumer group 8.4.1.2
parallel servers
- asynchronous communication 8.1.4.5
parallel SQL
- allocating rows to parallel execution servers 8.1.4.4
- distribution methods 8.1.4.4
- instance groups 8.1.8
- number of parallel execution servers 8.1.5
- optimizer 8.1.4.1
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 CDBs and PDBs 8.4.1.6
- 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 8.4.1.7
- 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
- about 3.2.2
- composite 3.2.2.2
- single-level 3.2.2.1
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
- for composite-partitioned tables 4.2
- for hash partitions 4.1.3
- for list partitions 4.1.4
- for range partitions 4.1.1
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 4.4.8.3
- Online Transaction Processing (OLTP) 7.2.1
- rebuilding index partitions 4.4.9
- renaming index partitions/subpartitions 4.4.10.3
- secondary indexes on index-organized tables 4.1.15.1
- splitting partitions 4.4.11.7
- views 4.7
- 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 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 4.4.11
- 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 4.4.8
- moving subpartitions 4.4.8.2
- 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 4.4.9
- redefining partitions online 4.6.1
- renaming partitions 4.4.10
- renaming subpartitions 4.4.10.2
- splitting partitions 4.4.11
- truncating partitions 4.4.12
- truncating partitions with the cascade option 4.4.12.3
- truncating subpartitions 4.4.12.2
- updating global indexes automatically 4.3.1
- views 4.7
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 2.1.10
- 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
- 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
- merging older partitions 7.3.3.2
- moving older partitions 7.3.3.2
- Online Transaction Processing (OLTP) 7.3.3
- removing old data 7.3.3.1
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
  - examples 3.3.1.1
  - local indexes 3.3.1
- 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
- benefits 6.3.2, 6.3.2.3
- full 3.2.1, 6.3.2.1
- parallel execution 6.3.2.4
- partial 3.2.2, 6.3.2.2
performance
- DSS database 8.5.3.1
- prefixed and nonprefixed indexes 3.3.5
- very large databases (VLDBs) 10.2
pluggable databases
- parallel statement queuing 8.4.1.6
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 8.6.3.1.2.1
process monitor process (PMON)
- parallel DML process recovery 8.5.3.7.2
producer operations 8.1.4.2
pruning partitions
- about 3.1
- benefits 3.1.1
- indexes and performance 3.3.5

Q

queries
- ad hoc 8.5.2.2
queuing
- parallel statements 8.4

R

range-hash partitioning
- creating tables using 4.2.4.1
- subpartitioning template 4.2.5.1
range-list partitioning
- creating tables using 4.2.4.2
- subpartitioning template 4.2.5.2
range-partitioned tables
- adding partitions 4.4.1.1
- splitting partitions 4.4.11.1, 4.4.11.6
range partitioning 2.3.1.1
- creating tables using 4.1.1
- index-organized tables 4.1.15.1
- multicolumn partitioning keys 4.1.10
- performance considerations 3.5.1, 3.5.6
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 4.4.8.3, 4.4.9.2.1
REBUILD UNUSABLE LOCAL INDEXES clause 4.4.9.2.2
recovery
- parallel DML operations 8.5.3.7
reference-partitioned tables
- adding partitions 4.4.1.8
reference partitioning
- creating tables using 4.1.5
- key extension 2.4.2.1
RENAME PARTITION clause 4.4.10.1, 4.4.10.3.1
RENAME SUBPARTITION clause 4.4.10.2
replication
- restrictions on parallel DML 8.5.3.9
resources
- consumption, parameters affecting 8.6.3.2, 8.6.3.2.3
- limiting for users 8.6.3.1.2.2
- limits 8.6.3.1.2
- parallel query usage 8.6.3.2
restrictions
- direct-path INSERT 8.5.3.9
- parallel DDL statements 8.5.2.1
- parallel DML operations 8.5.3.9
- parallel DML operations and remote transactions 8.5.3.12
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
- batch jobs 8.5.3.1.5
- parallel DML operations 8.5.3.1
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
- creating on demand 4.1.14.3
- deferred 4.1.14.1
- partitioning 4.1.14
- truncating 4.1.14.2
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
- MINIMUM EXTENT parameter 8.5.2.6
- parallel DDL 8.5.2.4
SPLIT PARTITION clause 4.4.1.1, 4.4.11
SPLIT PARTITION operations
- optimizing 4.4.11.9
SPLIT SUBPARTITION operations
- optimizing 4.4.11.9
splitting multiple partitions 4.4.11.8
splitting partitions and subpartitions 4.4.11
SQL statementsSQL statements
- data flow operations 8.1.4.1
- parallelizing 8.1.4.1
STATEMENT_QUEUING
- parallel statement queuing hint 8.4.3
statistics
- operating system 8.7.4
storage
- fragmentation in parallel DDL 8.5.2.6
- index partitions 3.3.8
STORAGE clause
- parallel execution 8.5.2.5
storage management
- very large databases (VLDBs) 10
STORE IN clause 4.2.4.1.2
stripe and mirror everything
- very large databases (VLDBs) 10.3.1
striping
- Information Lifecycle Management 10.2.3
- partitioning placement 10.2.4
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, 4.4.11.4
- for composite-partitioned tables 4.2
SUBPARTITIONS clause 4.4.1.5.1, 4.4.11.4
- 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
- DBMS_FLASHBACK_ARCHIVE package ENABLE_AT_VALID_TIME procedure 5.3.2
- limitations 5.3.4
- managing data validity 5.3.2
- valid-time period 5.3.2
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
- restrictions 8.5.3.11
- restrictions on parallel DML 8.5.3.9
TRUNCATE PARTITION clause 4.4.12, 4.4.12.1, 4.4.12.1.1
TRUNCATE SUBPARTITION clause 4.4.12.2
truncating multiple partitions 4.4.12.4
truncating partitions
- asynchronous global index maintenance 4.3.2
- cascade option 4.4.12.3
- marking indexes UNUSABLE 4.4.12
truncating segments
- partitioning 4.1.14.2
two-phase commit 8.6.3.2.3.1
types of parallelism 8.5

U

UNION ALL
- concurrent execution 8.5.3.14
UPDATE GLOBAL INDEX clause
- of ALTER TABLE 4.3.1
UPDATE statement
- parallel UPDATE statement 8.5.3.3
updating indexes automatically 4.3.1
user resources
- limiting 8.6.3.1.2.2

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$SYSSTAT view 8.8.4.6
valid-time period
- Temporal Validity 5.3.2
very large databases (VLDBs)
- about 1
- backing up and recovering 9
- backup tools 9.2.3
- backup types 9.2.2
- bigfile tablespaces 10.2.5
- database structures for recovering data 9.2.1
- hardware-based mirroring 10.1.1
- hardware-based striping 10.2.1
- high availability 10.1
- introduction 1
- mirroring with Oracle ASM 10.1.2
- new features
- Oracle Automatic Storage Management settings 10.4
- Oracle Backup and Recovery 9.2
- Oracle Database File System 10.2.6
- Oracle Data Pump 9.2.3, 9.2.3.2
- Oracle Recovery Manager 9.2.3.1
- partitioning, and 1.2
- performance 10.2
- physical and logical backups 9.2.2
- RAID 0 striping 10.2.1.1
- RAID 1 mirroring 10.1.1.1
- RAID 5 mirroring 10.1.1.2
- RAID 5 striping 10.2.1.2
- RMAN 9.2.3
- scalability and manageability 10.3
- storage management 10
- stripe and mirror everything 10.3.1
- striping with Oracle ASM 10.2.2
- user-managed backups 9.2.3, 9.2.3.3
views
- parallel processing monitoring 8.7.1
- partitioned tables and indexes 4.7
- V$SESSTAT 8.7.4
- V$SYSSTAT 8.8.4.6
views for ILM policies
- Automatic Data Optimization 5.2.2.9
virtual column-based partitioning
- about 4.1.11
- key extension 2.4.2.2
- using for the subpartitioning key 4.1.11
virtual column partitioning
- performance considerations 3.5.7
VLDBs
- very large databases 1

W

workloads
- skewing 8.1.6

X

XMLType collections
- partitioning 4.1.17
XMLType objects 2.1.10