MapReduce Design Patterns

• Summarization patterns: get a top-level view by summarizing and grouping data
• Filtering patterns: view data subsets such as records generated from one user
• Data organization patterns: reorganize data to work with other systems, or to make MapReduce analysis easier
• Join patterns: analyze different datasets together to discover interesting relationships
• Metapatterns: piece together several patterns to solve multi-stage problems, or to perform several analytics in the same job
• Input and output patterns: customize the way you use Hadoop to load or store data 

Key SQL CLR Decisions - Microsoft SQL Server

Key SQL CLR Decisions
# Using SQL CLR or T-SQL
# Using SQL CLR or Extended Stored Procedures
# Using SQL CLR or OLE Automation Procedures
# Using the Data Tier or Application Tier for Business Logic

SQL CLR Barriers of Entry
# Security Considerations
# The DBA Perspective on SQL CLR
# Implementation Considerations
# Performance Considerations
# Maintenance Considerations

Required Namespaces for SQL CLR Objects
There are four namespaces required to support the creation of SQL CLR objects. The required namespaces
are:
❑ System.Data
❑ System.Data.Sql
❑ System.Data.SqlTypes
❑ Microsoft.SqlServer.Server