Loma  Baumbach

Loma Baumbach


TPC-C Benchmark: 10,000 Warehouses on YugabyteDB

We are excited to announce that the TPC-C benchmark implementation for YugabyteDB is now open source and ready to use! While this implementation is not officially ratified by the TPC organization, it closely follows the TPC-C v5.11.0 specification.

For those new to TPC-C, the aim of the benchmark is to test how a database performs when handling transactions generated by a real-world OLTP application. This blog post shows the results of running the TPC-C benchmark in addition to outlining our experience of developing and running a TPC-C benchmark against YugabyteDB.


The results of running the above TPC-C benchmark with 10, 100, 1000, and 10,000 warehouses on a YugabyteDB cluster running in a single zone of AWS are shown below.

results of running the above TPC-C benchmark with 10, 100, 1000, and 10,000 warehouses on a YugabyteDB cluster

You can find the instructions to reproduce the above results in the benchmarking section of YugabyteDB docs. The rest of this post goes into some details about the TPC-C workload itself, how we built the benchmark tool, and our considerations when running it in public clouds.

Linear TPC-C scalability in the context of a distributed relational database refers to the fact that support for a larger number of warehouses without compromising high efficiency can be achieved by simply adding new nodes to the cluster. As shown below, we are excited to prove this property in the context YugabyteDB. YugabyteDB shows a tpmC value of 12,590 (while running 1000 warehouses on a 3 node cluster of c5d.4xlarge nodes) which is 97.90% of the theoretical maximum. In order to handle scaling the workload up by a factor of 10 from 1,000 to 10,000 warehouses, the cluster was scaled up to 30 nodes. This resulted in 10 times as many transactions per second being handled, for a tpmC of 125,194 (which is 97.35% of the theoretical maximum possible tpmC value of 128,600).

Linear TPC-C scalability results YugabyteDB high performance distributed sql database

Understanding the TPC-C workload

TPC-C models a business that has a warehouse, multiple districts, and inventory for those warehouses, as well as items and orders for those items. The TPC-C benchmark tests five different transaction workloads, which are briefly described below.

  • The New Order transaction simulates entering a new order through a single database transaction. This transaction, which forms the backbone of the workload, has a high frequency of execution with low latency requirements to satisfy online users. About 1% of these transactions will simulate failures to test transaction rollback.
  • The Payment transaction updates the customer’s balance and reflects the payment on the district and warehouse sales statistics. This transaction includes non-primary key access to the CUSTOMER table.
  • The Order Status transaction queries the status of a customer’s last order.
  • The Delivery transaction processes a batch of new orders which are not yet delivered, executed in the background using a queuing mechanism.
  • The Stock Level transaction determines the number of recently sold items that have a stock level below a specified threshold and therefore would need to be restocked.

The complete entity-relationship diagram for the TPC-C workload is shown below.

complete entity-relationship diagram for the TPC-C workload yugabytedb benchmarks high performance

The number of warehouses is the key configurable parameter that determines the scale of running the benchmark. Increasing the number of warehouses increases the data set size, the number of concurrent clients as well as the number of concurrently running transactions. A warehouse can have up to ten terminals (point of sale or point of inquiry counters) which generate transactions such as entering a new order, settling payments, and looking up the status of an existing order. TPC-C also models other behind the scenes activities at warehouses that would result in transactions, such as finding items that need to be restocked or marking items as delivered.

#community news #databases #distributed sql #how it works #open source #performance benchmarks

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TPC-C Benchmark: 10,000 Warehouses on YugabyteDB
Tamale  Moses

Tamale Moses


How to Run C/C++ in Sublime Text?

C and C++ are the most powerful programming language in the world. Most of the super fast and complex libraries and algorithms are written in C or C++. Most powerful Kernel programs are also written in C. So, there is no way to skip it.

In programming competitions, most programmers prefer to write code in C or C++. Tourist is considered the worlds top programming contestant of all ages who write code in C++.

During programming competitions, programmers prefer to use a lightweight editor to focus on coding and algorithm designing. VimSublime Text, and Notepad++ are the most common editors for us. Apart from the competition, many software developers and professionals love to use Sublime Text just because of its flexibility.

I have discussed the steps we need to complete in this blog post before running a C/C++ code in Sublime Text. We will take the inputs from an input file and print outputs to an output file without using freopen file related functions in C/C++.

#cpp #c #c-programming #sublimetext #c++ #c/c++

Dicey Issues in C/C++

If you are familiar with C/C++then you must have come across some unusual things and if you haven’t, then you are about to. The below codes are checked twice before adding, so feel free to share this article with your friends. The following displays some of the issues:

  1. Using multiple variables in the print function
  2. Comparing Signed integer with unsigned integer
  3. Putting a semicolon at the end of the loop statement
  4. C preprocessor doesn’t need a semicolon
  5. Size of the string matters
  6. Macros and equations aren’t good friends
  7. Never compare Floating data type with double data type
  8. Arrays have a boundary
  9. Character constants are different from string literals
  10. Difference between single(=) and double(==) equal signs.

The below code generates no error since a print function can take any number of inputs but creates a mismatch with the variables. The print function is used to display characters, strings, integers, float, octal, and hexadecimal values onto the output screen. The format specifier is used to display the value of a variable.

  1. %d indicates Integer Format Specifier
  2. %f indicates Float Format Specifier
  3. %c indicates Character Format Specifier
  4. %s indicates String Format Specifier
  5. %u indicates Unsigned Integer Format Specifier
  6. %ld indicates Long Int Format Specifier

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A signed integer is a 32-bit datum that encodes an integer in the range [-2147483648 to 2147483647]. An unsigned integer is a 32-bit datum that encodes a non-negative integer in the range [0 to 4294967295]. The signed integer is represented in twos-complement notation. In the below code the signed integer will be converted to the maximum unsigned integer then compared with the unsigned integer.

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#problems-with-c #dicey-issues-in-c #c-programming #c++ #c #cplusplus

Mery tris

Mery tris



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Ari  Bogisich

Ari Bogisich


Using isdigit() in C/C++

In this article, we’ll take a look at using the isdigit() function in C/C++. This is a very simple way to check if any value is a digit or not. Let’s look at how to use this function, using some simple examples.

#c programming #c++ #c #c#

Ari  Bogisich

Ari Bogisich


Loops in C++ | For, While, and Do While Loops in C++

In this Video We are going to see how to use Loops in C++. We will see How to use For, While, and Do While Loops in C++.
C++ is general purpose, compiled, object-oriented programming language and its concepts served as the basis for several other languages such as Java, Python, Ruby, Perl etc.

#c #c# #c++ #programming-c