Skip to main content

Can we configure RMAN backup for very large database to use all the nodes instead of the node where it is scheduled through crontab?

 YES

RMAN and Oracle Net in Real Application Clusters

In any RMAN connection made through a net service name, each net service name must specify one and only one instance. This rule applies to all RMAN connections whether they are made from the command line or through the CONNECT clause in ALLOCATE CHANNEL or CONFIGURE CHANNEL commands. Therefore, you cannot specify a net service name that uses Oracle Net features to distribute RMAN connections to more than one instance.

Channel Connections to Cluster Instances

When making backups in a Real Application Clusters configuration, each allocated channel can connect to a different instance in the cluster, and each channel connection must resolve to one and only one instance. For example, configure automatic channels as follows:

CONFIGURE DEFAULT DEVICE TYPE TO sbt;
CONFIGURE DEVICE TYPE sbt PARALLELISM 3;
CONFIGURE CHANNEL 1 DEVICE TYPE sbt CONNECT = 'SYS/oracle@node1';
CONFIGURE CHANNEL 2 DEVICE TYPE sbt CONNECT = 'SYS/oracle@node2';
CONFIGURE CHANNEL 3 DEVICE TYPE sbt CONNECT = 'SYS/oracle@node3';
If the instance to which one of the channels is connected does not have the database open, then the database must not be open by any instance. In other words, either all channels must be connected to open instances, or all channels must be connected to instances that are not open. For example, if the node1 instance has the database mounted while the node2 and node3 instances have the database open, then the backup fails.

Node Affinity Awareness

In some cluster database configurations, some nodes of the cluster have faster access to some datafiles than to other datafiles. RMAN automatically detects this affinity, which is known as node affinity awareness.
When deciding which channel to use to back up a particular datafile, RMAN gives preference to channels allocated at the nodes that have affinity to the datafiles you want to back up. For example, if you have a three-node cluster, and if node 1 has faster read/write access to datafiles 7, 8, and 9 than the other nodes, then node 1 has greater node affinity to those files than nodes 2 and 3.

To use node affinity, configure RMAN channels on the nodes of the cluster that have affinity to the datafiles you want to back up. For example, use the syntax:

CONFIGURE CHANNEL 1 DEVICE TYPE sbt CONNECT 'user1/password1@node1';
CONFIGURE CHANNEL 2 DEVICE TYPE sbt CONNECT 'user2/password2@node2';
CONFIGURE CHANNEL 3 DEVICE TYPE sbt CONNECT 'user3/password3@node3';
You can manually override the automatic node affinity by specifying which channels should back up which datafiles. For example:


BACKUP
  # channel 1 gets datafile 1
  (DATAFILE 1 CHANNEL ORA_SBT_TAPE_1)
  # channel 2 gets datafiles 2-4
  (DATAFILE 2,3,4 CHANNEL ORA_SBT_TAPE_2)
  # channel 3 gets datafiles 5-10
  (DATAFILE 5,6,7,8,9,10 CHANNEL ORA_SBT_TAPE_3);
Labels:

Comments

Post a Comment

Popular posts from this blog

Data Wrangling vs EDA

  Aspect Data Wrangling (Data Preprocessing) Exploratory Data Analysis (EDA) Objective Prepare raw data for modeling by cleaning, transforming, and formatting it appropriately. Explore and understand the data to gain insights, identify patterns, and make decisions on data handling and modeling. Order Typically performed as a preliminary step before EDA. Usually conducted after data wrangling to further investigate data characteristics. Data Handling Focuses on data cleaning, filling missing values, encoding categorical variables, and scaling features. Involves data visualization, statistical analysis, and summary statistics to uncover patterns, relationships, and anomalies. Techniques Techniques include imputation, outlier detection, feature scaling, and one-hot encoding. Techniques include histograms, scatter plots, box plots, correlation matrices, and descriptive statistics. Data Transformation Involves structural changes to the dataset, such as feature engineering, data normaliz...
Post a Comment
Read more

What is Tensor Parallelism and relationship between Buffer and GPU

  Tensor Parallelism in GPU Tensor parallelism is a technique used to distribute the computation of large tensor operations across multiple GPUs or multiple cores within a GPU .   It is an essential method for improving the performance and scalability of deep learning models, particularly when dealing with very large models that cannot fit into the memory of a single GPU. Key Concepts Tensor Operations : Tensors are multidimensional arrays used extensively in deep learning. Common tensor operations include matrix multiplication, convolution, and element-wise operations. Parallelism : Parallelism involves dividing a task into smaller sub-tasks that can be executed simultaneously. This approach leverages the parallel processing capabilities of GPUs to speed up computations. How Tensor Parallelism Works Splitting Tensors : The core idea of tensor parallelism is to split large tensors into smaller chunks that can be processed in parallel. Each chunk is assigned to a different GP...
Post a Comment
Read more

Infrastructure limitations ESX Server 4 vs ESXI 5

Some limitations in ESX Server 4 may constrain the design of data centers:[28][29] • Guest system maximum RAM: 255 GB • Host system maximum RAM: 1 TB[28] • Number of hosts in a high availability cluster: 32 • Number of Primary Nodes in ESX Cluster high availability: 5 • Number of hosts in a Distributed Resource Scheduler cluster: 32 • Maximum number of processors per virtual machine: 8 • Maximum number of processors per host: 160 • Maximum number of cores per processor: 12 • Maximum number of virtual machines per host: 320 • VMFS-3 limits files to 262,144 (218) blocks, which translates to 256 GB for 1 MB block sizes (the default) or up to 2 TB for 8 MB block sizes.[30] However, on a VMFS Boot drive, it is usually very difficult to use anything other than 1 MB Block size [31]. With ESXI 5 there has been some changes to these limits[32] • Guest system maximum RAM: 1 TB • Host system maximum RAM: 2 TB • Number of hosts in a high availability cluster: 32 • Maximum number ...
Post a Comment
Read more