Twitter Boosts Performance and Cost Efficiency

Twitter increases Hadoop performance and cost efficiency with caching, fast SSDs and more compute.

At a Glance:

  • Twitter uses Hadoop* for storing data and performing advanced analytics to generate important business insights.

  • Twitter expects that caching temporary data with Intel® SSDs based on Intel® 3D NAND Technology and increasing core counts with 2nd Gen Intel® Xeon® Scalable processors will result in approximately 30 percent lower TCO and over 50 percent faster runtimes, compared to their legacy production cluster configuration.1

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Executive Overview

Storage I/O can be a significant performance bottleneck for Hadoop* clusters, especially in hyperscale deployments like those at Twitter, where a single cluster can have up to 10,000 nodes and nearly 100 PB of logical storage. The typical Hadoop cluster at Twitter contains over 100,000 hard disk drives (HDDs)—but this configuration was reaching an I/O performance limit because while HDD capacity has increased over time, HDD performance has not significantly changed.2 Therefore, simply adding more, bigger HDDs wasn’t going to solve Twitter’s scaling challenges—in fact, it would make things worse as the I/O per GB decreases. Adding more spindles per node was not feasible due to space and power limitations.

Working in collaboration with an Intel engineering team, Twitter engineers conducted a series of experiments that revealed that storing temporary files managed by YARN* (Yet Another Resource Negotiator*) on a fast SSD enabled significant performance improvements on existing hardware (up to a 50 percent reduction in runtime).3 The team also discovered that removing a storage I/O bottleneck enabled them to use larger hard drives while simultaneously increasing processor utilization, which in turn resulted in the ability to use higher-core-count processors. This positively affected storage performance, and contributed to higher data center density by reducing the number of required HDDs.

Higher density leads to total cost of ownership (TCO) savings through energy efficiency, fewer racks, and a smaller data center footprint. Overall, Twitter expects that caching temporary data and increasing core counts will result in approximately 30 percent lower TCO and over 50 percent faster runtimes, compared to their legacy production cluster configuration.1

Read the white paper - Boosting Hadoop* Performance and Cost Efficiency with Caching, Fast SSDs, and More Compute

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Informacje o produktach i wydajności

1

Punkt odniesienia: jednogniazdowy procesor Intel® Xeon® E3-1230 v6 (4-rdzeniowy); pamięć RAM od 32 do 64 GB; 1 x dysk HDD o pojemności 1 TB lub 2 TB; dysk rozruchowy Intel S4500 240 GB; Ethernet od 1 GbE do 10 GbE E; bez buforowania. Test: jednogniazdowy procesor Intel® Xeon® Gold 6262 (24-rdzeniowy); pamieć RAM 192 GB; dysk rozruchowy Intel S4500 240 GB; 8 x dysk HDD o pojemności 6 TB; 1 x dysk Intel® SSD DC P4610 6,4 TB; Ethernet 25 GbE; buforowanie przy użyciu oprogramowania Intel® Cache Acceleration Software (Intel® CAS). System operacyjny: Twitter CentOS* 6 Derivative, Kernel Version 2.6.74-t1.el6.x86_64 (based on upstream 4.14.12 Kernel), BIOS Wersja: D3WWM11, Wersja mikrokodu: 0xb000021.

2

Backblaze, wrzesień 2018 r.: „Dysk twardy (HDD) kontra dysk półprzewodnikowy (SSD) – jaka jest różnica?” https://www.backblaze.com/blog/hdd-versus-ssd-whats-the-diff/.

3

Punkt odniesienia: dwugniazdowy procesor Intel® Xeon® E5-2630 v4 @ 2,2 GHz (10 rdzeni/20 wątków na gniazdo); pamięć RAM 128 GB; 12 x dysk HDD SATA 6 TB 7200 RPM; 1 x dysk rozruchowy SSD SATA; Ethernet 25 GbE; 102 węzły rozmieszczone na 6 szafach serwerowych. Użyte testy porównawcze: Gridmix* i Terasort*. Wynik Gridmix: 3309 sekund; wynik Terasort: 5504 sekund. Zestaw testowy: dwugniazdowy procesor Intel® Xeon® E5-2630 v4 @ 2,2 GHz (10 rdzeni/20 wątków na gniazdo); pamięć RAM 128 GB; 12 x dysk HDD SATA 6 TB 7200 RPM; 1 x dysk rozruchowy SSD SATA; 1 x pamięć Intel® Optane™ DC P4800X NVMe* 750 GB – oparta na dysku SSD; Ethernet 25 GbE; 102 węzły rozmieszczone na 6 szafach serwerowych. Użyte testy porównawcze: Gridmix i Terasort. Wynik Gridmix: 2396 sekund; wynik Terasort: 2640 sekund; System operacyjny: Twitter CentOS*, dystrybucja 6, kernel.