AWS VM Import/Export is designed for you to easily import your existing VM-based environment to AWS EC2 instances and export them back to your on-premises environment. VM Import/Export is free except standard usage charges for AWS EC2 and S3. You can use AWS CLI (command Line Interface) or AWS API to import Windows or Linux […]
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VM Import/Export Prerequisites Operating Systems Microsoft Windows Server 2003 SP1, 2003 R2, 2008, 2008 R2, 2012, 2012 R2 (Standard, Datacenter, Enterprise) Microsoft Windows 7 US English (Professional, Enterprise, Ultimate) You must have existing licenses with rights to use these licenses in a third-party, multi-tenant cloud like AWS. (Using BYOL flag with the LicenseType parameter) Licenses […]
Prepare VM image Disable any antivirus or intrusion detection software on your VM. These services can be re-enabled after the import process is complete. Disconnect any CD-ROM drives (virtual or physical). Set your network to DHCP instead of a static IP address. If you want to assign a static private IP address, be sure to […]
Import Image There are two ways to import your VM image in S3: Convert VM image to custom AMI, and then create EC2 instances from the AMI. Convert VM image to snapshot, and then create EBS volume from the snapshot. From Linux environment, there’s one CLI command ec2-import-instance which can create EC2 instance directly from […]
In this video, you are shown how to use SQL Pattern Matching with the Big Data Lite VM.
With Oracle Database 12c Release 1 (12.1), you can use the MATCH_RECOGNIZE clause to perform pattern matching in SQL to do the following:
1. Logically partition and order the data that is used in the MATCH_RECOGNIZE clause with its PARTITION BY and ORDER BY clauses.
2. Define patterns of rows to seek using the PATTERN clause of the MATCH_RECOGNIZE clause. These patterns use regular expressions syntax, a powerful and expressive feature, applied to the pattern variables you define.
3. Specify the logical conditions required to map a row to a row pattern variable in the DEFINE clause.
4. Define output measures, which are expressions usable in the MEASURES clause of the SQL query.
5. Control the output (summary vs. detailed) from the pattern matching process