The only guide you’ll need on concurrency & multithreading for senior engineers. Pressure test your skills with real-world practice problems from top companies.

Concurrency in Java is one of the most complex and advanced topics brought up during senior engineering interviews. Knowledge of concurrency and multithreading can put interviewees at a considerable advantage. This course lays the foundations of advanced concurrency and multithreading and explains concepts such as Monitors and Deferred Callbacks in depth. It also builds simple and complete solutions to popular concurrency problems that can be asked about in interviews like the Reader-Writer Problem and the Dining Philosopher Problem. While prior knowledge of concurrency is not required to follow through with this course, familiarity with the very basics of concurrency would be helpful.

Java Multithreading for Senior Engineering Interviews

## Throughput
<p>Throughput is defined as <span class="hi-yl">the <i>rate of doing work</i> </span>or how much work gets done per unit of time. If you are an Instagram user, you could define throughput as the number of images your phone or browser downloads per unit of time.</i></p>
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## Latency
<p>Latency is defined as <span class="hi-yl">the <i>time required to complete a task or produce a result</span></i>. Latency is also referred to as <i>response time</i>. The time it takes for a web browser to download Instagram images from the internet is the latency for downloading the images.
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## Throughput vs Latency
<p>The two terms are more frequently used when describing networking links and have more precise meanings in that domain. In the context of concurrency, throughput can be thought of as time taken to execute a program or computation.
For instance, imagine a program that is given hundreds of files containing integers and asked to sum up all the numbers. Since addition is commutative each file can be worked on in parallel. In a single-threaded environment, each file will be sequentially processed but in a concurrent system, several threads can work in parallel on distinct files. Of course, there will be some overhead to manage the state including already processed files. However, such a program will complete the task much faster than a single thread. The performance difference will become more and more apparent as the number of input files increases. <span class="hi-yl">The throughput in this example can be defined as the number of files processed by the program in a minute. And latency can be defined as the total time taken to completely process all the files.</span> As you observe in a multithreaded implementation throughput will go up and latency will go down. More work gets done in less amount of time. In general, the two have an inverse relationship.</p>

# Throughput
<p>Throughput is defined as <span class="hi-yl">the <i>rate of doing work</i> </span>or how much work gets done per unit of time. If you are an Instagram user, you could define throughput as the number of images your phone or browser downloads per unit of time.</i></p>
</div>
</div>

# Latency
<p>Latency is defined as <span class="hi-yl">the <i>time required to complete a task or produce a result</span></i>. Latency is also referred to as <i>response time</i>. The time it takes for a web browser to download Instagram images from the internet is the latency for downloading the images.
</p>
</div>
</div>

# Throughput vs Latency
<p>The two terms are more frequently used when describing networking links and have more precise meanings in that domain. In the context of concurrency, throughput can be thought of as time taken to execute a program or computation.
For instance, imagine a program that is given hundreds of files containing integers and asked to sum up all the numbers. Since addition is commutative each file can be worked on in parallel. In a single-threaded environment, each file will be sequentially processed but in a concurrent system, several threads can work in parallel on distinct files. Of course, there will be some overhead to manage the state including already processed files. However, such a program will complete the task much faster than a single thread. The performance difference will become more and more apparent as the number of input files increases. <span class="hi-yl">The throughput in this example can be defined as the number of files processed by the program in a minute. And latency can be defined as the total time taken to completely process all the files.</span> As you observe in a multithreaded implementation throughput will go up and latency will go down. More work gets done in less amount of time. In general, the two have an inverse relationship.</p>

# Throughput
<p>Throughput is defined as <span>the <i>rate of doing work</i> </span>or how much work gets done per unit of time. If you are an Instagram user, you could define throughput as the number of images your phone or browser downloads per unit of time.</i></p>
</div>
</div>

# Latency
<p>Latency is defined as <span>the <i>time required to complete a task or produce a result</span></i>. Latency is also referred to as <i>response time</i>. The time it takes for a web browser to download Instagram images from the internet is the latency for downloading the images.
</p>
</div>
</div>

# Throughput vs Latency
<p>The two terms are more frequently used when describing networking links and have more precise meanings in that domain. In the context of concurrency, throughput can be thought of as time taken to execute a program or computation.
For instance, imagine a program that is given hundreds of files containing integers and asked to sum up all the numbers. Since addition is commutative each file can be worked on in parallel. In a single-threaded environment, each file will be sequentially processed but in a concurrent system, several threads can work in parallel on distinct files. Of course, there will be some overhead to manage the state including already processed files. However, such a program will complete the task much faster than a single thread. The performance difference will become more and more apparent as the number of input files increases. <span>The throughput in this example can be defined as the number of files processed by the program in a minute. And latency can be defined as the total time taken to completely process all the files.</span> As you observe in a multithreaded implementation throughput will go up and latency will go down. More work gets done in less amount of time. In general, the two have an inverse relationship.</p>

This lessons discusses throughput and latency in the context of concurrent systems.

The Basics

Multithreading in Java

Java's Memory Model

Interview Practice Problems

Bonus Questions

Beyond the Interview

Java Concurrency Reference

Revision & Quizzes

Throughput vs Latency

Throughput

Latency