designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect JobTracker (Master)，可是要管理多個 TaskTracker (Slave)！ 10 / 74 Hadoop 1.x 架構與限制 比較基本的模組： Hadoop HDFS (Storage) Hadoop MapReduce (Computing Engine + Resource Management + Job Scheduling / Monitoring + ...) 比較明顯的限制： 改造 HDFS -> HDFS2 20 / 74 Hadoop 2.x 架構 比較基本的模組： Hadoop Common (Core Libraries) Hadoop HDFS (Storage) Hadoop MapReduce (Computing Engine) Hadoop YARN (Resource Management + Job Scheduling / Monitoring)

Sparse Arrays 1708 94.1 Compressed Sparse Column (CSC) Sparse Matrix Storage . . . . . . . . . . . . . . . 1708 94.2 Sparse Vector Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . if there are leading zero digits which don’t contribute to the value, they count for determining storage size of a literal. So 0x01 is a UInt8 while 0x0001 is a UInt16. That allows the user to control sense to write something like let x = x since the two x variables are distinct and have separate storage. Here is an example where the behavior of let is needed: julia> Fs = Vector{Any}(undef, 2); i =

Sparse Arrays 1708 94.1 Compressed Sparse Column (CSC) Sparse Matrix Storage . . . . . . . . . . . . . . . 1708 94.2 Sparse Vector Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . if there are leading zero digits which don’t contribute to the value, they count for determining storage size of a literal. So 0x01 is a UInt8 while 0x0001 is a UInt16. That allows the user to control sense to write something like let x = x since the two x variables are distinct and have separate storage. Here is an example where the behavior of let is needed: julia> Fs = Vector{Any}(undef, 2); i =

Sparse Arrays 1708 94.1 Compressed Sparse Column (CSC) Sparse Matrix Storage . . . . . . . . . . . . . . . 1708 94.2 Sparse Vector Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . if there are leading zero digits which don’t contribute to the value, they count for determining storage size of a literal. So 0x01 is a UInt8 while 0x0001 is a UInt16. That allows the user to control sense to write something like let x = x since the two x variables are distinct and have separate storage. Here is an example where the behavior of let is needed: julia> Fs = Vector{Any}(undef, 2); i =

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Sparse Arrays 1773 96.1 Compressed Sparse Column (CSC) Sparse Matrix Storage . . . . . . . . . . . . . . . 1773 96.2 Sparse Vector Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . if there are leading zero digits which don’t contribute to the value, they count for determining storage size of a literal. So 0x01 is a UInt8 while 0x0001 is a UInt16. That allows the user to control sense to write something like let x = x since the two x variables are distinct and have separate storage. Here is an example where the behavior of let is needed: julia> Fs = Vector{Any}(undef, 2); i =

Sparse Arrays 1771 96.1 Compressed Sparse Column (CSC) Sparse Matrix Storage . . . . . . . . . . . . . . . 1771 96.2 Sparse Vector Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . if there are leading zero digits which don’t contribute to the value, they count for determining storage size of a literal. So 0x01 is a UInt8 while 0x0001 is a UInt16. That allows the user to control sense to write something like let x = x since the two x variables are distinct and have separate storage. Here is an example where the behavior of let is needed: julia> Fs = Vector{Any}(undef, 2); i =

Sparse Arrays 1770 96.1 Compressed Sparse Column (CSC) Sparse Matrix Storage . . . . . . . . . . . . . . . 1770 96.2 Sparse Vector Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . if there are leading zero digits which don’t contribute to the value, they count for determining storage size of a literal. So 0x01 is a UInt8 while 0x0001 is a UInt16. That allows the user to control sense to write something like let x = x since the two x variables are distinct and have separate storage. Here is an example where the behavior of let is needed: julia> Fs = Vector{Any}(undef, 2); i =

Sparse Arrays 1770 96.1 Compressed Sparse Column (CSC) Sparse Matrix Storage . . . . . . . . . . . . . . . 1770 96.2 Sparse Vector Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . if there are leading zero digits which don’t contribute to the value, they count for determining storage size of a literal. So 0x01 is a UInt8 while 0x0001 is a UInt16. That allows the user to control sense to write something like let x = x since the two x variables are distinct and have separate storage. Here is an example where the behavior of let is needed: julia> Fs = Vector{Any}(undef, 2); i =

Arrays 1761 95.1 Compressed Sparse Column (CSC) Sparse Matrix Storage . . . . . . . . . . . . . . . 1761CONTENTS xii 95.2 Sparse Vector Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . if there are leading zero digits which don’t contribute to the value, they count for determining storage size of a literal. So 0x01 is a UInt8 while 0x0001 is a UInt16. That allows the user to control sense to write something like let x = x since the two x variables are distinct and have separate storage. Here is an example where the behavior of let is needed: julia> Fs = Vector{Any}(undef, 2); i =