A Minimal Book Example
1
Who is this book for?
1.1
What will the book cover?
1.2
What does the book not cover?
2
Introduction
2.1
What analysts need
3
System setup
3.1
Follow along with the BigData Lite VM or XE18 on Docker
3.2
A production environment
3.2.1
Installing drivers
3.2.2
Installing Rstudio
3.2.3
Installing SQL Workbench
3.3
Connecting to a database from R
4
A relational state of mind
4.1
An illustrated example with movie-data
5
Loading our data
6
Basic SQL
6.1
SELECT
FROM
WHERE
? Starting our exploration
6.1.1
A quick glance at our data
6.1.2
Aggregating your results
6.2
More ways to
JOIN
tables
6.3
A few common gotchas
6.3.1
Missing values
6.3.2
Execution order
6.3.3
ANSI and the dialects
7
Intermediate SQL {intermediate-sql}
7.1
Create conditional statements with
CASE WHEN
7.2
Filter on aggregates with
HAVING
7.3
More about limiting the result with
FETCH FIRST
7.4
Simple convenience functions
7.4.1
The
decode
function
7.4.2
upper / lower
7.4.3
substring
7.4.4
Regular expressions
7.4.5
Dealing with dates
7.5
What we are not going to cover
7.5.1
PL/SQL
7.5.2
the
dbplyr
library
8
Aggregation functions {aggregation-functions}
8.1
Median and quantiles
8.2
First values {first-values}
8.3
Aggregating text
9
Analytical functions
9.1
Over the partitions and far away
9.2
Models
10
Statistical functions
10.1
Covariance: Revisitng quantity vs unitprice
10.2
Regression
10.3
T-tests
10.4
Kolmogorov-Smirnoff tests
10.5
And more...
11
Row pattern matching
11.1
A simple(ish) example
11.2
A more involved example
11.2.1
Importing and cleaning
12
Inserting and updating data
12.1
Committing changes to a database
12.2
Truncate, don't drop
13
Performance and integrity
13.1
Indexes
13.2
constraints
13.3
Optimizing your queries
13.3.1
Inline views
13.3.2
Filter First
13.3.3
Take advantage of partitions
13.3.4
Explain plans
13.3.5
Leave some things for R
14
Shiny and Oracle
15
Relevance to other databases
16
Big Data Databases
16.1
What is hive, and how does it compare
17
What Oracle R Enterprise is
17.1
Loading ORE
17.2
Pushing R computation to the database
17.3
ORE build-in algorithms
17.4
Calling R from SQL
References
Published with bookdown
Data analysis with R and Oracle
Chapter 13
Performance and integrity
13.1
Indexes
13.2
constraints
13.3
Optimizing your queries
13.3.1
Inline views
13.3.2
Filter First
13.3.3
Take advantage of partitions
13.3.4
Explain plans
13.3.5
Leave some things for R