As an industry leading database technology, oracle has many in-built features which makes it easy to manage the DBA activities, even in the cloud. The Amazon RDS oracle DB provides access to many stored procedures and functions which can be accessed using the SQL developer client tool. This procedure can be executed using the user ID and password created during the Amazon RDS instance creation. Below are the examples of some of the most frequently used DBA activities.

Killing a Session

Sometimes a long running query or any other DB activity needs to be killed by killing the session. We use the Amazon RDS procedure rdsadmin.rdsadmin_util.kill to kill a session. The following code does that.

# First get the session identifier and the session serial number,
select SID, SERIAL#, STATUS from V$SESSION where USERNAME = ''AWSUSER

# Next use the procedure
begin
    rdsadmin.rdsadmin_util.kill(
        sid    => sid,
        serial => serial_number);
end;
/

Setting the Default Tablespace

The Amazon RDS procedure rdsadmin.rdsadmin_util.alter_default_tablespace can be used to set to the default tablespace for a DB using the following command.

exec rdsadmin.rdsadmin_util.alter_default_tablespace(tablespace_name => ''AWSuser'');

Setting the Database Time Zone

We can use the Amazon RDS procedure rdsadmin.rdsadmin_util.alter_db_time_zone to changes the time zone for the DB.

# Change the time zone of the DB to UTC + 5.30
exec rdsadmin.rdsadmin_util.alter_db_time_zone(p_new_tz => ''+5:30'');
# Change the time zone to a specific region
exec rdsadmin.rdsadmin_util.alter_db_time_zone(p_new_tz => ''Asia/Kolkata'');

Adding Online Redo Logs

We can use the Amazon RDS procedure rdsadmin.rdsadmin_util.add_logfile to add additional redo logs. The following command adds a log file of size 128MB.

exec rdsadmin.rdsadmin_util.add_logfile(p_size => ''128M'');

As a cloud platform AWS gives you very minimal number of steps to setup a DB in RDS. Creating a Oracle DB can be done in three ways. Using AWS management console, AWS CLI or AWS API. We will look at each of these approaches one by one.

Using AWS management Console

AWS management console is the most convenient way to get started with RDS. You login to the AWS console using your AWS account details, locate the RDS service and then follow the steps shown below to create a Oracle SQL DB instance.

Step-1

Select the Oracle db Engine form the console.

Step-2

Specify the required DB details.

Step-3

In this step you decide on the db instance class, amount of storage allocated also set the master password along with few other details.

Stpe—4

This is the final step when you mention the vpc and security settings, encryption, backup options and log export etc. For brevity the screen shot has been shortened showing only the important options.

Using CLI

To create a Oracle DB instance by using the AWS CLI, call the create-db-instance command with the parameters below.

aws rds create-db-instance
    --engine oracle-se1
    --db-instance-identifier mydbinstance
    --allocated-storage 20
    --db-instance-class db.m1.small
    --db-security-groups mydbsecuritygroup
    --db-subnet-group mydbsubnetgroup
    --master-username masterawsuser
    --master-user-password masteruserpassword
    --backup-retention-period 3

Using API

To create a Oracle DB instance by using the Amazon RDS API, we call the CreateDBInstance action with the parameters as shown below.

https://rds.amazonaws.com/
    ?Action=CreateDBInstance
    &AllocatedStorage=250
    &BackupRetentionPeriod=3
    &DBInstanceClass=db.m1.large
    &DBInstanceIdentifier=mydbinstance
    &DBSecurityGroups.member.1=mysecuritygroup
    &DBSubnetGroup=mydbsubnetgroup
    &Engine=oracle-se1
    &MasterUserPassword=masteruserpassword
    &MasterUsername=masterawsuser
    &SignatureMethod=HmacSHA256
    &SignatureVersion=4
    &Version=2014-10-31
    &X-Amz-Algorithm=AWS4-HMAC-SHA256
    &X-Amz-Credential=AKIADQKE4SARGYLE/20140305/us-west-1/rds/aws4_request
    &X-Amz-Date=20140305T185838Z
    &X-Amz-SignedHeaders=content-type;host;user-agent;x-amz-content-sha256;x-amz-date
    &X-Amz-Signature=b441901545441d3c7a48f63b5b1522c5b2b37c137500c93c45e209d4b3a064a3

To connect to Amazon RDS Oracle DB we need a client software. In this case we use Sql Developer. Install it using the link .

After it is successfully installed we follow the steps below to connect it to the Amazon RDS.

Step-1

From the DB instance details get the end point.

Step-2

Use the end point and the master user credentials as the connection details.

Step-3

Once connected, we get the following window.

To import data into the RDS oracle database or export data from it, we need to consider the size of the data involved and use a appropriate technique. The Sql Developer tool which we use to connect to AWS RDS oracle instance, can be used for both export and import small volume of data like 20MB or so. But to import data of size in terabytes, we need to use oracle data pump.

Exporting Data Using SQL Developer

Step-1

After connecting to the AWS RDS Oracle DB, choose tools and Database Export.

Step-2

The next step asks for the type of export where we decide the export format.

Step-3

Next we decide on the DB objects to be exported.

Step-4

We can further decide on the name of the objects to be exported.

Step-5

We can further decide on the objects attributes to be exported.

Step-6

Finally we get the summary screen where we can revisit the objects we have choosen.

Clicking finish on the above step will export the DB into a file in choosen format.

Importing Data Using SQL Developer

Similar to the export steps above we can choose to import the db by using Database Copy command from the Tools menu option.

Oracle is very popular Relational DB which is available in the amazon RDS services with its enterprise edition features. Almost every feature of Oracle can be leveraged in the RDS platform. Below is a brief description on MYSQLs major features in RDS platform.

Supported Versions

The versions 11.2 and 12.1 are the major versions supported in the RDS platform. If no version is mentioned during the DB creation, it defaults to the most recent version at that point in time. Below is an example of how to get the supported DB Engine versions using AWS API in a python SDK program.

import boto3
client = boto3.client(''rds'')
response = client.describe_db_engine_versions(
    DBParameterGroupFamily=''oracle-ee-12.1'',
    DefaultOnly=True,
    Engine='''',
    EngineVersion='''',
    ListSupportedCharacterSets=False, #True,
)
print(response)

When we run the above program, we get the following output −

{
   "ResponseMetadata": {
      "RetryAttempts": 0,
      "HTTPStatusCode": 200,
      "RequestId": "f6805635-3e16-4014-83cd-dfdaf3f17950",
      "HTTPHeaders": {
         "x-amzn-requestid": "f6805635-3e16-4014-83cd-dfdaf3f17950",
         "date": "Fri, 14 Sep 2018 03:46:38 GMT",
         "content-length": "1455",
         "content-type": "text/xml"
      }
   },
   "u''DBEngineVersions''": [
      {
         "u''Engine''": "oracle-ee",
         "u''DBParameterGroupFamily''": "oracle-ee-12.1",
         "u''SupportsLogExportsToCloudwatchLogs''": true,
         "u''SupportsReadReplica''": false,
         "u''DefaultCharacterSet''": {
            "u''CharacterSetName''": "AL32UTF8",
            "u''CharacterSetDescription''": "Unicode 5.0 UTF-8 Universal character set"
         },
         "u''DBEngineDescription''": "Oracle Database Enterprise Edition",
         "u''EngineVersion''": "12.1.0.2.v12",
         "u''DBEngineVersionDescription''": "Oracle 12.1.0.2.v12",
         "u''ExportableLogTypes''": [
            "alert",
            "audit",
            "listener",
            "trace"
         ],
         "u''ValidUpgradeTarget''": []
      }
   ]
}

Oracle Licensing

There are two options for using oracle licenses in RDS. They are License Included and Bring Your Own License.

License Included Model

In this model Amazon holds the license for the software you are going to use. Also AWS itself provides the support for both AWS and Oracle software thorugh its support program. So the user does not purchase any separate license. The platform pricing includes the charges for licensing cost the user pays. The two editions supported in this model are Standard Edition One and Standard Edition Two.

Bring Your Own License (BYOL)

In this model the user brings in the license she holds into RDS platform. It is the user’s responsibility to maintain the compatibility between the license, database instance class and database edition. The user directly contacts the Oracle support channel for any need. In this model the supported editions are Enterprise Edition (EE), Standard Edition (SE), Standard Edition One (SE1) and Standard Edition Two (SE2).

For a multi A-Z deployment, the user should have license for both primary DB instance and the secondary DB instance.

Oracle DB Parameter Group

The oracle DB involves many DB parameters to be configured for various features and performance needs of the database. Aws makes these parameters visible through CLI commands, which the user can use to query for the parameter values. Below is the CLI command and the sample output.

aws rds describe-engine-default-parameters --db-parameter-group-family oracle-ee-12.1

Below are the some important parameters obtained as a result of above CLI command.

{
    "EngineDefaults": {
        "Parameters": [
            {
                "AllowedValues": "TRUE,FALSE",
                "ParameterName": "_allow_level_without_connect_by",
                "ApplyType": "dynamic",
                "Description": "_allow_level_without_connect_by",
                "IsModifiable": true,
                "Source": "engine-default",
                "DataType": "boolean"
            },
            {
                "AllowedValues": "CHOOSE,OFF,CUBE,NESTED_LOOPS,MERGE,HASH",
                "ParameterName": "_always_semi_join",
                "ApplyType": "dynamic",
                "Description": "_always_semi_join",
                "IsModifiable": true,
                "Source": "engine-default",
                "DataType": "string"
            },
            {
                "AllowedValues": "TRUE,FALSE",
                "ParameterName": "_b_tree_bitmap_plans",
                "ApplyType": "dynamic",
                "Description": "_b_tree_bitmap_plans",
                "IsModifiable": true,
                "Source": "engine-default",
                "DataType": "boolean"
            },
    {
                "AllowedValues": "TRUE,FALSE",
                "ParameterName": "parallel_automatic_tuning",
                "ApplyType": "static",
                "Description": "enable intelligent defaults for parallel execution parameters",
                "IsModifiable": true,
                "Source": "engine-default",
                "DataType": "boolean"
            },
            {
                "AllowedValues": "ENABLE,DISABLE",
                "ParameterName": "xml_db_events",
                "ApplyType": "dynamic",
                "Description": "are XML DB events enabled",
                "IsModifiable": false,
                "Source": "engine-default",
                "DataType": "string"
            }
        ]
    }
}

To connect to Amazon RDS MSSQL server we need a client software. In this case we use Sql Server Management Studio. Install it using the link .

After it is successfully installed we follow the steps below to connect it to the Amazon RDS.

Step-1

From the DB instance details get the end point.

Step-2

Use the end point and the master user credentials as the connection details.

Step-3

Once connected, we get the following window.

Step-4

We can also query the MSSQL DB as shown below.

As a cloud platform AWS gives you very minimal number of steps to setup a DB in RDS. Creating a MSSQL DB can be done in three ways. Using AWS management console, AWS CLI or AWS API. We will look at each of these approaches one by one.

Using AWS management Console

AWS management console is the most convenient way to get started with RDS. You login to the AWS console using your AWS account details, locate the RDS service and then follow the steps shown below to create a MSm SQL DB instance.

Step-1

Select the MySQL db Engine form the console.

Step-2

Specify the required DB details.

Step-3

In this step you decide on the db instance class, amount of storage allocated also set the master password along with few other details.

Stpe—4

This is the final step when you mention the vpc and security settings, encryption, backup options and log export etc. For brevity the screen shot has been shortened showing only the important options.

Using CLI

To create a MSSQL DB instance by using the AWS CLI, call the create-db-instance command with the parameters below.

aws rds create-db-instance
    --engine sqlserver-se
    --db-instance-identifier mymsftsqlserver
    --allocated-storage 250
    --db-instance-class db.m1.large
    --db-security-groups mydbsecuritygroup
    --db-subnet-group mydbsubnetgroup
    --master-user-name masterawsuser
    --master-user-password masteruserpassword
    --backup-retention-period 3

Using API

To create a MSSQL DB instance by using the Amazon RDS API, we call the CreateDBInstance action with the parameters as shown below.

https://rds.amazonaws.com/
    ?Action=CreateDBInstance
    &AllocatedStorage=250
    &BackupRetentionPeriod=3
    &DBInstanceClass=db.m1.large
    &DBInstanceIdentifier=mydbinstance
    &DBSecurityGroups.member.1=mysecuritygroup
    &DBSubnetGroup=mydbsubnetgroup
    &Engine=sqlserver-se
    &MasterUserPassword=masteruserpassword
    &MasterUsername=masterawsuser
    &SignatureMethod=HmacSHA256
    &SignatureVersion=4
    &Version=2014-10-31
    &X-Amz-Algorithm=AWS4-HMAC-SHA256
    &X-Amz-Credential=AKIADQK/20140305/us-west-1/rds/aws4_request
    &X-Amz-Date=20140305T185838Z
    &X-Amz-SignedHeaders=content-type;host;user-agent;x-amz-content-sha256;x-amz-date
    &X-Amz-Signature=d445654615b1522c5b2b37c13bsseb7575hdh45e209d4b3a064a3

The RDS instances use Amazon Block Storage (EBS) volumes for storing data and log. These storage types can dynamically increase their size as and when needed. But based on the database workloads and price associated with these storage types we can customize the storage need. Following are the factors to be analysed while deciding on the storage types.

• IOPS – It represents the number of Input Output operations performed per second. Both read and write operations are summed up for finding the IOPS value. AWS creates a report of IOPS value for every 1 minute. It can have value from 0 to tens of thousands per second.

• Latency – It is the number of milliseconds elapsed between the initiation of an I/O request and the completion of the I/O request. A bigger latency indicates a slower performance.

• Throughput – The number of bytes transferred to and from the disk every second. AWS reports the read and write throughput separately for every 1-minute interval.

• Queue Depth – It is the number of I/O requests waiting in the queue before they can reach the disk. AWS reports the queue depth for every 1-minute interval. Also a higher queue-depth indicates a slower storage performance.

Based on the above considerations, the aws storage types are as below.

General Purpose SSD

This is a cost-effective storage that is useful in most of the common database tasks. It can provide 3000 IOPS for a 1- TiB volume. In a 3.34 TiB size the performance can go up to 10000 IOPS.

I/O Credits

Each GB of storage allows 3 IOPs as a base line performance. Which mean a 100 GB volume can provide 300 IOPs. But there may be scenario when you need more IOPS. In such scenario you need to use some IO credit balance which is offered when the storage is initialized. It is 5.4 million IO credits which can be used when a burstable performance need arises. On the other hand when you use less IOPS than the baseline performance, you accumulate the credits which can be used in future requirement of burstable performances.

Below is a equation which shows the relation between burst duration and Credit balance.

Burst Duration = (credit Balance) / [(burst IOPS) – 3(Storage size in GB)]

If your DB needs frequent and long duration burstable performance, then the next storage type will be a better choice.

Provisioned IOPS Storage

This is a type of storage system that gives sustained higher performance and consistently low latency which is most suitable for OLTP workloads.

When creating the DB instance, you specify the required IOPS rate and volume size for such storage. Below is a chart which is used for reference for deciding about the IOPS and storage needed under provisioned storage.

This is a very old storage technology which is maintained by aws, only for backward compatibility. Its features are very limited which are the following.

• Does not support Elastic Volumes

• Limited to maximum size of 4 TB

• Limited to maximum of 1000 IOPS

The RDS interfaces are a way to access the RDS service we create. After the creation and configuration of the RDS service there is a need of accessing the data, uploading data to this database and running some other program which should be able to connect to the database. Such requirements of accessing and manipulating data by end users of the database and not necessarily the AWS account holder which created the database needs these interfaces.

There are three main such interfaces.

GUI Console

This is the simplest of the interfaces where the user can login through a web browser and start using the DB services. The down side of such access is , it needs a human to interact with the RDS services and we cannot run a database program to do some regular tasks like – backup or analysing the DB etc.

Command Line Interface

It is also called CLI access where you can execute DB command through the AWS command prompt screen which should have been installed in the client computer you are using. Below are the steps to install CLI in your local system using which you will access AWS services.

The steps to install AWS CLI are as below.

Step-1

Check for the version of python in your environment.

ubuntu@ubuntu:~$ python -V
ubuntu@ubuntu:~$ python3 -V

When we run the above program, we get the following output −

Python 2.7.12
Python 3.5.2

If the version is less than 2.6 or 3.3 , then you need to upgrade the version of python in your system.

Step -2

Check for availability of the python package named pip . It will be needed to install AWS CLI.

Pip -V

When we run the above program, we get the following output −

pip 10.0.1 from /home/ubuntu/.local/lib/python3.5/site-packages/pip (python 3.5)

Step -3

Issue the following command to install the AWS CLI.

pip install awscli –upgrade –user
aws --version

When we run the above program, we get the following output −

Aws-cli/1.11.84 Python/3.6.2 Linux/4.4.0

Step-4

Next we configure the aws CLI with credentials. We issue this command and then input the required values one by one.

aws configure

When we run the above program, we get the following output −

AWS Access Key ID [None]: ****PLE
AWS Secret Access Key [None]: ********8
Default region name [None]: us-west-2
Default output format [None]: json

With the above configuration in place you are now ready to use CLI for communicating with AWS environments for setting up and using amazon RDS. In the next chapters we will see how we can do that.

AWS API

Amazon Relational Database Service (Amazon RDS) also provides an application programming interface (API). APIs are used when the information is exchanged between the systems rather than a human issuing the commands and receiving the result. For example, if you want to automate the addition of database instances to a RDS service when the number of transactions reach certain threshold , then you use a AWS SDK to write a program which will monitor the number of database transactions and spin-off a RDS instance when the required condition is met.

Below is an example of API code that creates a copy of a DB snapshot. It is a python program which uses AWS sdk named boto3. The client library in boto3 has a method named copy_db_snapshot which is called by the python program to create a copy of the DB snapshot with the required parameters as shown.

import boto3

client = boto3.client(''rds'')

response = client.copy_db_snapshot(
    SourceDBSnapshotIdentifier=''mydbsnapshot'',
    TargetDBSnapshotIdentifier=''mydbsnapshot-copy'',
)

print(response)

When the above program is run we get the response which describes the various properties of the copy event. Here the term string represents the various names of parameters which is defined by the user for their environment. For example VpcID represents the ID of the vpc in which the copy action is happening.

{
    ''DBSnapshot'': {
        ''DBSnapshotIdentifier'': ''string'',
        ''DBInstanceIdentifier'': ''string'',
        ''SnapshotCreateTime'': datetime(2015, 1, 1),
        ''Engine'': ''string'',
        ''AllocatedStorage'': 123,
        ''Status'': ''string'',
        ''Port'': 123,
        ''AvailabilityZone'': ''string'',
        ''VpcId'': ''string'',
        ''InstanceCreateTime'': datetime(2015, 1, 1),
        ''MasterUsername'': ''string'',
        ''EngineVersion'': ''string'',
        ''LicenseModel'': ''string'',
        ''SnapshotType'': ''string'',
        ''Iops'': 123,
        ''OptionGroupName'': ''string'',
        ''PercentProgress'': 123,
        ''SourceRegion'': ''string'',
        ''SourceDBSnapshotIdentifier'': ''string'',
        ''StorageType'': ''string'',
        ''TdeCredentialArn'': ''string'',
        ''Encrypted'': True|False,
        ''KmsKeyId'': ''string'',
        ''DBSnapshotArn'': ''string'',
        ''Timezone'': ''string'',
        ''IAMDatabaseAuthenticationEnabled'': True|False,
        ''ProcessorFeatures'': [
            {
                ''Name'': ''string'',
                ''Value'': ''string''
            },
        ]
    }
}

As RDS is a managed service provided by AWS, we can expect that like other AWS services it will provide scalability, security and cost effectiveness to the various RDBMS it provides. The database products available through AWS RDS are as listed below.

• MySQL – Support versions for MySQL 5.5 to 5.7. Minor upgrades happen automatically without needing any involvement from the user.

• MariaDB – Support versions for MariaDB from 10.0 to 10.2.

• Oracle – Supports version 11g and 12c. You can use the oracle license provided by aws or bring your own license. The costing for these two are different.

• Microsoft SQL Server – Supports version 200t to 2017. Also AWS supports the various editions like – Enterprise, Standard, Web and Express.

• PostgreSQL – Supports version 9 to 11. Can be configured as a multi A-Z deployment with read replicas.

• Amazon Aurora – This is Amazon’s own RDBMS. We will be covering it in a separate tutorial.

Each of these Database software is offered as Software as a Service (saas) by providing following features.

• Customization of CPU capacity, Memory allocation and IOPS(Input Output per second) for a database instance.

• Manage software patching, failure and recovery of the RDBMS software without any user intervention.

• Allow manual or automated backup of the database using snapshots. Restore the database from these snapshots.

• Provide high availability by creating a primary and secondary instance which are synchronous. In case of a failure of primary AWS RDS automatically fails over to secondary.

• Put the databases in a virtual private cloud (VPC) and aslo use AWS IAM (Identity and Access management) service to control access to the databases.

• There are two purchase options for AWS RDS service. On-Demand Instances and Reserved Instances. For on-Demand instance you pay for every hour of usage while for Reserved instance you make a upfront payment for one year to three period time frame.