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#***********************************************************************
# Database parameters
#***********************************************************************
# Database blocks should be large in data warehouses. This improves
# performance for operations involving large amounts of data.
db_block_size = 8192
# For a large data warehouse, db_files should be set to a large value.
#db_files = 1000
#***********************************************************************
# Memory parameters
#***********************************************************************
# In a data warehouse, the majority of physical memory will be
# allocated for the one of the following two purposes:
# Runtime memory: used for sorting and hashing data during query processing
# (governed by the parameter pga_aggregate_size)
# Data caching: used to accelerate performance by avoid disk accesses
# (governed by the parameter db_cache_size)
# Additionally, a significant amount of memory may need to be allocated for:
# Shared pool: used for storing shared memory constructs
# (governed by the parameter shared_pool_size)
# Large pool: used during parallel-execution processing
# (governed by the parameter large_pool_size)
#
# Memory is managed globally. The DBA should first determine how much
# memory is available for Oracle to use. Then, the DBA should choose
# memory parameters so that pga_aggregate_size + db_cache_size +
# shared_pool_size + large_pool_size is roughly equal to the amount
# of memory available for the Oracle database.
#
# For example, suppose that a DBA is managing a small data mart. The
# data mart server has 1GB of physical memory. The DBA has determined
# that 500M of memory will be used by the operating system and other
# applications, so that 500M is available for Oracle.
#
# The DBA may choose the following settings:
# shared_pool_size = 50M
# pga_aggregate_size = 200M
# db_cache_size = 200M
# large_pool_size = <default>
#
# The total memory utilization is 450M plus a system-determined value
# for the large pool.
#
# The following sections discuss each of these memory-related
# parameters in more detail. These examples assume that the data
# warehouse server has 1GB, 8GB, and 16GB respectively for small,
# medium, and large configurations.
# Runtime memory (the memory used for sorting and hashing during query
# execution) is automatically and globally managed when the
# pga_aggregate_target parameter is set. For data warehouse workloads
# which involve sorts and joins of large volumes of data, the
# pga_aggregate_target should be set to a large value.
#
# pga_aggregate_target should, in general, be equal to 20-80% of the
# available memory, depending on the workload. The values below assume
# a mixed data-warehouse workload.
#
# This parameters (introduced in Oracle9i) replaces all of the
# following parameters: hash_area_size, sort_area_size,
# create_bitmap_area_size, and bitmap_merge_area_size
pga_aggregate_target = 30M #DEMO
#pga_aggregate_target = 200M #SMALL
#pga_aggregate_target = 3000M #MEDIUM
#pga_aggregate_target = 6000M #LARGE
# The database cache is also a globally-managed portion of memory. The
# database cache should be set to a large value for data warehouse
# workloads which involves short-running queries and/or the access of
# small tables and indexes.
#
# db_cache_size should, in general, be equal to 20-80% of the
# available memory, depending on the workload. The values below assume
# a mixed data-warehouse workload.
#
db_cache_size = 30M #DEMO
#db_cache_size = 200M #SMALL
#db_cache_size = 3000M #MEDIUM
#db_cache_size = 6000M #LARGE
# Shared pool size should be, in general, equal to 5-10% of the
# available memory. Data warehouses typically do not require as much
# memory for shared pool as OLTP systems.
shared_pool_size = 20M #DEMO
#shared_pool_size = 50M #SMALL
#shared_pool_size = 400M #MEDIUM
#shared_pool_size = 800M #LARGE
# The default for large_pool_size should appropriate for most
# environments.
#
# The Large Pool is used for several purposes. In a data warehouse the
# majority of the space in the Large Pool will be used for
# parallel-execution internal message buffers. The amount of memory
# required by parallel-execution is proportional to the product of the
# number of concurrent parallel-execution users and the square of the
# number of CPU's.
#
# The documentation describes in detail how to estimate the default size
# of the Large Pool, and the conditions under which this parameter
# should be set explicitly.
#
# Here are some very general estimates on the amount of memory required
# for the Large Pool based on the number of CPU's:
# 4 cpus: 5M (with parallel_threads_per_cpu = 4)
# 8 cpus: 5M (with parallel_threads_per_cpu = 2)
# 8 cpus: 20M (with parallel_threads_per_cpu = 4)
# 16 cpus: 20M (with parallel_threads_per_cpu = 2)
# 32 cpus: 80M (with parallel_threads_per_cpu = 2)
#
# The Large Pool is only used for parallel-execution message buffers
# when parallel_automatic_tuning is enabled. If
# parallel_automatic_tuning is not utilitized, then parallel-execution
# message buffers are stored in the shared pool, and the
# shared_pool_size parameter should be adjusted appropriately.
#***********************************************************************
# Parallel Execution parameters
#***********************************************************************
# Parallel execution parameters were greatly simplified in Oracle8i.
# Data warehouses developed on older releases of Oracle may use
# different init.ora parameters. While these older parameters continue
# to be supported, these parameters below are recommended for all new
# data warehouses, and should be considered when upgrading data
# warehouses from previous releases.
# Setting parallel_automatic_tuning will result in the database
# configuring itself to support parallel execution.
parallel_automatic_tuning = true
# This parameter determines the default number of parallel execution
# processes. Typically, 2 parallel processes per CPU provides good
# performance. However, for systems with a smaller number of CPUs or
# for systems in which the IO subsystem is slow relative to the the
# CPU's, more parallel processes may be desired and the value of this
# parameter may be increased.
parallel_threads_per_cpu = 4 #SMALL
#parallel_threads_per_cpu = 2 or 4 #MEDIUM
#parallel_threads_per_cpu = 2 #LARGE
#***********************************************************************
# Optimizer and query parameters
#***********************************************************************
# All data warehouses should use the cost-based optimizer. All basic
# data warehouse performance features, such as star-query support,
# hash joins, parallel execution, and bitmap indexes are only
# accessible via the cost-based optimizer.
optimizer_mode = choose
# When using a star schema, set this parameter to true.
star_transformation_enabled = true
#***********************************************************************
# IO parameters
#***********************************************************************
# Multiblock reads allow for the database to retrieve multiple
# database blocks in a single IO. In general, a high multiblock read
# count provides better performance, particularly for operations on
# large volumes of data. Oracle supports IO's up to 1MB on many
# platforms. Disk striping will also affect the value for multiblock
# read count, since the stripe size should ideally be a multiple of
# the IO size.
# If you are gathering optimizer system statistics (see DBMSSTAT.SQL
# for more information), then you should set this parameter to a high
# value.
#db_file_multiblock_read_count = 64
# If you are not gathering optimizer system statistics, then you
# should set this parameter to a lower value.
db_file_multiblock_read_count = 16
#***********************************************************************
# Materialized view parameters
#***********************************************************************
# This parameter enables the use of materialized views for improved
# query performance.
query_rewrite_enabled = true
# This parameter determines the degree to which Oralce enforces
# integrity rules during query rewrite. In most data-warehouse
# environment, 'trusted' is the appropriate setting.
query_rewrite_integrity = trusted
#***********************************************************************
# Compatibility
#***********************************************************************
# When building a new application, both compatibility and
# optimizer_features_enabled should be set to the current release to
# take advantage of all new features. If you are upgrading an existing
# application to Oracle9i, then you may want to consider setting one
# or both of these parameters to an earlier release.
#compatible = 9.0
#optimizer_features_enabled = 9.0
#***********************************************************************
# Other Parameters
#***********************************************************************
# This section lists other parameters that, although not specific
# to data warehousing, are required for any Oracle database. By
# uncommenting these parameters, this parameter file can be used
# as a complete stand-alone init.ora file.
db_name = HRMS89
# Define at least two control files by defaultms
control_files = (c:\oracle\oradata\HRMS89\cntrl1HRMS89.ctl, c:\oracle\oradata\HRMS89\cntrl2HRMS89.ctl)
undo_management=AUTO |
