# MapReduce

`mapreduce`

is a programming technique which is suitable
for analyzing large data sets that otherwise cannot fit in your computer’s
memory. Using a `datastore`

to process the data in small
chunks, the technique is composed of a Map phase, which formats the data or
performs a precursory calculation, and a Reduce phase, which aggregates all
of the results from the Map phase. For more information, see Getting Started with MapReduce.

For information about using other products with
`mapreduce`

, see Speed Up and Deploy MapReduce Using Other Products.

## Functions

## Objects

`KeyValueStore` | Store key-value pairs for use with mapreduce |

`ValueIterator` | An iterator over intermediate values for use with mapreduce |

## Topics

**Getting Started with MapReduce**Learn about the MapReduce programming technique and run an example calculation.

**Write a Map Function**Create a map function for use in a

`mapreduce`

algorithm.**Write a Reduce Function**Create a reduce function for use in a

`mapreduce`

algorithm.**Build Effective Algorithms with MapReduce**Summary of

`mapreduce`

example files.**Speed Up and Deploy MapReduce Using Other Products**Capabilities of other products to speed up and share

`mapreduce`

algorithms.**Find Maximum Value with MapReduce**This example shows how to find the maximum value of a single variable in a data set using

`mapreduce`

.**Compute Mean Value with MapReduce**This example shows how to compute the mean of a single variable in a data set using

`mapreduce`

.**Create Histograms Using MapReduce**This example shows how to visualize patterns in a large data set without having to load all of the observations into memory simultaneously.

**Compute Mean by Group Using MapReduce**This example shows how to compute the mean by group in a data set using

`mapreduce`

.**Simple Data Subsetting Using MapReduce**This example shows how to extract a subset of a large data set.

**Using MapReduce to Compute Covariance and Related Quantities**This example shows how to compute the mean and covariance for several variables in a large data set using

`mapreduce`

.**Compute Summary Statistics by Group Using MapReduce**This example shows how to compute summary statistics organized by group using

`mapreduce`

.**Using MapReduce to Fit a Logistic Regression Model**This example shows how to use

`mapreduce`

to carry out simple logistic regression using a single predictor.**Tall Skinny QR (TSQR) Matrix Factorization Using MapReduce**This example shows how to compute a tall skinny QR (TSQR) factorization using

`mapreduce`

.**Compute Maximum Average HSV of Images with MapReduce**This example shows how to use

`ImageDatastore`

and`mapreduce`

to find images with maximum hue, saturation and brightness values in an image collection.

## Troubleshooting

This example shows how to debug your `mapreduce`

algorithms
in MATLAB^{®} using a simple example file, `MaxMapReduceExample.m`

.
Debugging enables you to follow the movement of data between the different
phases of `mapreduce`

execution and inspect the
state of all intermediate variables.