#m3r

[jpopstreaming]

🆕🎶 「 VEETHOV3N 」 new single by L.O.S.T, M3R is now available worldwide! 🌐 Listen now on our weekly updated playlist and discover new sounds from Japan 🎧 https://spoti.fi/42HdAgd

[juanburgosg-blog]

🌲❄️

[cestmoithemess-blog]

Loving Boise💕 time to go dress shopping 💃🏻👑✨ #m3r #missthreerivers #roadtomissidaho #seizetheday #missidahoclassof2017 (at Caffé D'arte)

[storyofsoo]

빈병을 치우고 새로 꺼낸 병을 나윤양이 미간을 찌푸리며 다시 냉장고에 넣어둔다. 멋쩍게 창밖을 보니 땅바닥이 말라 끌고 나온 한강엔 낚시꾼으로 북적인다. #장마 #브레이크타임 #한강 #브롬톤 #브룩스 #레이싱그린 #m3R #brompton (한강 자전거도로에서)

[synth-city-blog]

Expansion cards for the Korg M3R

[nosql]

Paper: M3R - Increased Performance for In-Memory Hadoop Jobs

For the weekend reads, a paper authored by a reseach team from IBM:

Main Memory Map Reduce (M3R) is a new implementation of the Hadoop Map Reduce (HMR) API targeted at online analytics on high mean-time-to-failure clusters. It does not support resilience, and supports only those workloads which can fit into cluster memory. In return, it can run HMR jobs unchanged — including jobs produced by compilers for higher-level languages such as Pig, Jaql, and SystemML and interactive front-ends like IBM BigSheets — while providing significantly better performance than the Hadoop engine on several workloads (e.g. 45x on some input sizes for sparse matrix vector multiply). M3R also supports extensions to the HMR API which can enable Map Reduce jobs to run faster on the M3R engine, while not affecting their perfor- mance under the Hadoop engine.

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Original title and link: Paper: M3R - Increased Performance for In-Memory Hadoop Jobs (NoSQL database©myNoSQL)