System Counters
FILE: Number of bytes read = 87
FILE: Number of bytes written = 211167
FILE: Number of read operations = 0
FILE: Number of large read operations = 0
FILE: Number of write operations = 0
HDFS: Number of bytes read = 366
HDFS: Number of bytes written = 6
HDFS: Number of read operations = 6
HDFS: Number of large read operations = 0
HDFS: Number of write operations = 2
Job Counters
Launched map tasks = 1
Launched reduce tasks = 1
Data-local map tasks = 1
Total time spent by all maps
matter how you use the command to create the lv, it is an extended DS_LVZ type LV.From the warning log of Oracle, we can see that when Oracle uses raw devices, it is recommended to set a lv without 4 K.
AIX calls this 4 K offset lvcb (logical volume control block), which occupies the first 512 bytes of 4 K. It is similar to the Oracle data file header and retains the creation time of lv, image copy information and file system mount points.
Check whether the lv has a 4 K offset in two ways.1. Ho
successfully16/04/11 22:31:34 INFO MapReduce. job:counters:49File System CountersFile:number of bytes read=67File:number of bytes written=290851File:number of Read operations=0File:number of Large Read operations=0File:number of Write Operations=0Hdfs:number of bytes read=237Hdfs:number of bytes Written=25Hdfs:number of Read operations=9Hdfs:number of Large Read operations=0Hdfs:number of Write operations=2Job CountersLaunched Map tasks=2launched reduce Tasks=1Data-local Map tasks=2Total time s
job_1417519292729_0030 running in Uber mode:false14/12/0600:10:43 INFO MapReduce. Job:map 0% reduce 0%14/12/0600:10:49 INFO mapreduce. Job:map 100% reduce 0%14/12/0600:10:56 INFO mapreduce. Job:map 100% reduce 100%14/12/0600:10:56 INFO MapReduce. Job:job job_1417519292729_0030 completed successfully14/12/0600:10:56 INFO mapreduce. Job:counters:49filesystemcountersfile:number of bytes Read=54file:number of bytes Written=182573file:number of Read Operations=0file:number of large read operations=0
, can improve efficiency. If you set this value to a larger value, the younger generation object will replicate multiple times in the Survivor area, which increases the lifetime of the object's younger generations, increasing the probability of being recycled in the younger generation. This parameter is valid only when the serial GC is in effect. -xx:+aggressiveopts faster compilation Performance improvement of-xx:+usebiasedlocking lock mechanism -XNOCLASSGC Disabling garbage collection
on an existing file on disk.1 using System;2 using System.IO;3 using System.IO.MemoryMappedFiles;4 using System.Runtime.InteropServices;56 Class Program7 {8 static void Main (string[] args)9 {Ten long offset = 0x10000000; MegabytesOne long length = 0x20000000; Megabytes12//Create the memory-mapped file.using (var mmf = Memorymappedfile.createfromfile (@ "C:\ExtremelyLargeImage.data", FileMode.Open, "ImgA")15 {+//Create a random access view, from the 256th m
Dfs:number of bytes Written=15671hdfs:number of read Operations=6hdfs:number of large read operations=0hdfs:number of Write Operations=2job Counters launched map tasks=1launched reduce tasks=1data-local map tasks=1total time spent by all MA PS in occupied slots (ms) =9860total time spent by all reduces in occupied slots (ms) =2053total time spent by all map tasks (ms) =2465total time spent by all reduce tasks (ms) =2053total Vcore-seconds taken by all map Tasks=2465total vcore-seconds Taken b
, which takes any input, can produce a specific size output. The process of using a hash function and then producing some data, which we call hashing (hashing) or transliteration as a hashing method. And the output of the hash function, we call it a hash (hash). The basic characteristic of a particular hash function is the size of its output. For example in this article, we use a hash function that outputs output as a zero bits (32 bytes). Of course there are hash functions that produce smaller
. Job:map 100% Reduce 100%14/07/09 14:51:15 INFO MapReduce. Job:job JOB_1404888618764_0001 completed successfully14/07/09 14:51:16 INFO MapReduce. job:counters:49File System CountersFile:number of bytes read=94File:number of bytes written=185387File:number of Read operations=0File:number of Large Read operations=0File:number of Write Operations=0Hdfs:number of bytes read=1051Hdfs:number of bytes written=43Hdfs:number of Read operations=6Hdfs:number of Large Read operations=0Hdfs:number of Write
Tags: http io ar os using SP strong on fileOriginal address: Http://msdn.microsoft.com/zh-cn/library/ms190969.aspxThe basic unit of data storage in SQL Server is the page. The disk space allocated for the data file (. mdf or. ndf) in the database can be logically divided into pages (numbered 0 through n consecutively). Disk I/O operations are performed at the page level. In other words, SQL Server reads or writes all data pages. A zone is a collection of eight physically contiguous pages that ar
38-1, "STORAGE Clause that specifies STORAGE Limits"
Example 38-2, "STORAGE Clause, specifies STORAGE Limits for the gkfx temporary tablespace only"
Example 38-3, "STORAGE Clause that specifies Unlimited STORAGE"
Example 38-1 STORAGE Clause that specifies STORAGE LimitsThis clause specifies, the storage used by all tablespaces, belong to the STORAGE PDB must not exceed 2 gigabytes. I T also specifies that the storage used by the PDB sessions in the GKFX temporary tablespace must no
of bytes written=66 4972 File:numberof read operations=0 File:number of large read operations=0 File:number of write operations=0 HDFS: Number of bytes read=636501 hdfs:number of bytes written=68 hdfs:number of Read operations=9 HDFS: Number of large read operations=0 Hdfs:number of write operations=2 Job Counters launched map tasks=2 Launched reduce Tasks=1 data-local map tasks=2 Total time spent by all maps in occupied slots (ms) =12 584 total time spent by all reduces in occu
The realm of writing programs using the Java language for Palm OS is not completely unified, and there are a number of differences, and there are several different application interfaces available on the market, each of which provides varying degrees of access to the current Palm OS application. Perhaps the most familiar of these are the products produced by Sun Microsystems, but this is not the only product that can write programs for Palm OS.
One, Sun solution: KVM, Configuration and profile
settings to move the boundary, if the OS design provides this option.
Under Low-memory conditions on some Windows CE-based devices, the OS might prompt the user for permission to take some object store RAM for use as program Ram to meet the ram requirements of an application.
When Windows ce OS starts, it creates a single 4-gigabyte (GB) virtual address space. the address space is divided into 33 slots, and each slot is 32 megabytes (MB ). all the processes share the address space. when a proce
specified, the trash, if enabled, will be bypassed and the specified file (s) deleted immediately. this can be useful when it is necessary to delete files from an over-quota directory.Example:
Hadoop FS-RMR/user/hadoop/Dir
Hadoop FS-rmr hdfs: // nn.example.com/user/hadoop/dir
Exit code:
Returns 0 on success and-1 on error.
Setrep
Usage: hadoop FS-setrep [-R]
Changes the replication factor of a file.-R option is for recursively increasing the replication factor of files within a directory.
Now, we use the Java language to write for the Palm OS Program The fields are not completely unified, and there are also many differences. Currently, there are several available application interfaces on the market, each application interface provides different access permissions to the current Palm OS application. Perhaps everyone is most familiar with Sun Microsystems, but it is not the only product that can write programs for Palm OS. This part of this article is not a tutorial on writing a p
newly created partitions. First, we start from the main File System ("/"), and the others are carried out in order. Of course, the two partitions on the source computer can be integrated into one partition on the target computer. In fact, this is exactly what we need to do -- merge/usr/and/usr/share in the above example into a partition. We will load the future main file system:Mount/dev/xxx/mntDuring replication, it is necessary to go to the target directory.Cd/mntTypeSsh targetPC dump-0-f-/|
; face; For (INT I = 0; I IB = face [I]. V [1]; const int Ic = face [I]. V [2]; const vec3 e1 = vert [Ia]. pos-Vert [IB]. pos; const vec3 e2 = vert [IC]. pos-Vert [IB]. pos; const vec3 NO = cross (E1, E2); vert [Ia]. normal + = no; vert [IB]. normal + = no; vert [IC]. normal + = no;} for (I = 0; I Myself-> mnumverts; I ++) Verts [I]. Normal = normalize (Verts [I]. Normal );}This is quite fast, fast enough to do lot of mesh normalizations per frame. on top of it, if you are using Vertex Shaders Y
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