ビッグデータ可視化の性能を徹底検証 〜SparkSQL、Hive on Tez、Hive LLAPを用いた既存RDBデータ 処理の特徴〜1. 新郷 美紀 NEC 蒋 逸峰 Solutions Engineer, Hortonworks ビッグデータ可視化 の性能を徹底検証 〜SparkSQL、Hive on Tez、Hive LLAPを用いた既存RDBデータ 処理の特徴〜 2. Agenda • 初めに • 背景 • クラウドDWH と Hiveとの比較 • 性能改善 – SparkSQL – Hive on Tez – Hive LLAP • まとめ Page. 2
Cloudera Blog
We are thrilled to announce the general availability of the Cloudera AI Inference service, powered by NVIDIA NIM microservices, part of the NVIDIA AI Enterprise platform, to accelerate generative AI deployments for enterprises. This service supports a range of optimized AI models, enabling seamless and scalable AI inference. Background The generative AI landscape is evolving […] Read blog post
Big Data Benchmark
Click Here for the previous version of the benchmark Introduction Several analytic frameworks have been announced in the last year. Among them are inexpensive data-warehousing solutions based on traditional Massively Parallel Processor (MPP) architectures (Redshift), systems which impose MPP-like execution engines on top of Hadoop (Impala, HAWQ), and systems which optimize MapReduce to improve per
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