+++
title = "Sequential and Parallel Table Scans"
date = 2019-12-02T10:17:10-08:00
weight = 3
chapter = true
pre = "<b>Exercise 2: </b>"
description = "Learn the difference between sequential and parallel scans."
+++


This exercise demonstrates the two methods of DynamoDB table scanning: sequential and parallel.

Even though DynamoDB distributes items across multiple physical partitions, a `Scan` operation can only read one partition at a time. To learn more, read [our documentation page on partitions and data distribution](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.Partitions.html). For this reason, the throughput of a `Scan` is constrained by the maximum throughput of a single partition.

In order to maximize the utilization of table-level provisioning, use a parallel `Scan` to logically divide a table (or secondary index) into multiple logical segments, and use multiple application workers to scan these logical segments in parallel. Each application worker can be a thread in programming languages that support multithreading or an operating system process. To learn more about how to implement a parallel scan, read [our developer documentation page on parallel scans](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Scan.html#Scan.ParallelScan). The `Scan` API is not suitable for all query patterns, and for more information on why scans are less efficient than queries please read about the [performance implications of `Scan`](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/bp-query-scan.html) in our documentation.

The following diagram shows how a multithreaded application performs a parallel `Scan` with three application worker threads. The application spawns three threads and each thread issues a `Scan` request, scans its designated segment, retrieving data 1 MB at a time, and returns the data to the main application thread.

![Parallel Scan](/images/image7.jpg)