X-Git-Url: https://git.arvados.org/arvados.git/blobdiff_plain/4995783a3270e2f6d2d3b5226238fbbccf2864c1..0456c65364c2189ac64775a40ac6279f8ef61802:/doc/user/tutorials/tutorial-keep.html.textile.liquid?ds=sidebyside
diff --git a/doc/user/tutorials/tutorial-keep.html.textile.liquid b/doc/user/tutorials/tutorial-keep.html.textile.liquid
index 5a5e8796cb..fac3530373 100644
--- a/doc/user/tutorials/tutorial-keep.html.textile.liquid
+++ b/doc/user/tutorials/tutorial-keep.html.textile.liquid
@@ -9,19 +9,17 @@ This tutorial introduces you to the Arvados file storage system.
*This tutorial assumes that you are "logged into an Arvados VM instance":{{site.baseurl}}/user/getting_started/ssh-access.html#login, and have a "working environment.":{{site.baseurl}}/user/getting_started/check-environment.html*
-The Arvados distributed file system is called *Keep*. Keep is a content-addressable file system. This means that files are managed using special unique identifiers derived from the _contents_ of the file, rather than human-assigned file names (specifically, the md5 hash). This has a number of advantages:
+The Arvados distributed file system is called *Keep*. Keep is a content-addressable file system. This means that files are managed using special unique identifiers derived from the _contents_ of the file, rather than human-assigned file names (specifically, the MD5 hash). This has a number of advantages:
* Files can be stored and replicated across a cluster of servers without requiring a central name server.
-* Systematic validation of data integrity by both server and client because the checksum is built into the identifier.
-* Minimizes data duplication (two files with the same contents will result in the same identifier, and will not be stored twice.)
-* Avoids data race conditions (an identifier always points to the same data.)
+* Both the server and client systematically validate data integrity because the checksum is built into the identifier.
+* Data duplication is minimizedâtwo files with the same contents will have in the same identifier, and will not be stored twice.
+* It avoids data race conditions, since an identifier always points to the same data.
h1. Putting Data into Keep
-We will start with downloading a freely available VCF file from the "Personal Genome Project (PGP)":http://www.personalgenomes.org subject "hu599905":https://my.personalgenomes.org/profile/hu599905 to a staging directory on the VM, and then add it to Keep.
+We will start by downloading a freely available VCF file from "Personal Genome Project (PGP)":http://www.personalgenomes.org subject "hu599905":https://my.personalgenomes.org/profile/hu599905 to a staging directory on the VM, and adding it to Keep. In the following commands, replace *@you@* with your login name.
-In the following tutorials, replace you
with your user id.
-
-First, log into the Arvados VM instance and set up the staging area:
+First, log into your Arvados VM and set up the staging area:
notextile.
~$ mkdir /scratch/you
@@ -65,7 +63,7 @@ You can also use @arv keep put@ to add an entire directory:
/scratch/you$ echo "hello bob" > tmp/bob.txt
/scratch/you$ echo "hello carol" > tmp/carol.txt
/scratch/you$ arv keep put tmp
-0M / 0M 100.0%
+0M / 0M 100.0%
887cd41e9c613463eab2f0d885c6dd96+83
@@ -76,12 +74,12 @@ h1. Getting Data from Keep
h2. Using Workbench
-You may access collections through the "Collections section of Arvados Workbench":https://{{ site.arvados_workbench_host }}/collections located at "https://{{ site.arvados_workbench_host }}/collections":https://{{ site.arvados_workbench_host }}/collections . You can also access individual collections and individual files within a collection. Some examples:
+You may access collections through the "Collections section of Arvados Workbench":https://{{ site.arvados_workbench_host }}/collections at *Data* %(rarr)→% *Collections (data files)*. You can also access individual files within a collection. Some examples:
* "https://{{ site.arvados_workbench_host }}/collections/c1bad4b39ca5a924e481008009d94e32+210":https://{{ site.arvados_workbench_host }}/collections/c1bad4b39ca5a924e481008009d94e32+210
* "https://{{ site.arvados_workbench_host }}/collections/887cd41e9c613463eab2f0d885c6dd96+83/alice.txt":https://{{ site.arvados_workbench_host }}/collections/887cd41e9c613463eab2f0d885c6dd96+83/alice.txt
-h2(#arv-get). Using arv-get
+h2(#arv-get). Using the command line
You can view the contents of a collection using @arv keep ls@:
@@ -109,6 +107,8 @@ Use @arv keep get@ to download the contents of a collection and place it in the
/scratch/you$ arv keep get c1bad4b39ca5a924e481008009d94e32+210/ .
+/scratch/you$ ls var-GS000016015-ASM.tsv.bz2
+var-GS000016015-ASM.tsv.bz2
/scratch/you$ md5sum var-GS000016015-ASM.tsv.bz2
@@ -129,10 +129,10 @@ With a local copy of the file, we can do some computation, for example computing
h2. Using arv-mount
-Use @arv-mount@ to take advantage of the "File System in User Space / FUSE":http://fuse.sourceforge.net/ feature of the Linux kernel to mount a Keep collection as if it were a regular directory tree.
+Use @arv-mount@ to mount a Keep collection and access it using traditional filesystem tools.
-/scratch/you$ mkdir mnt
+/scratch/you$ mkdir -p mnt
/scratch/you$ arv-mount --collection c1bad4b39ca5a924e481008009d94e32+210 mnt &
/scratch/you$ cd mnt
/scratch/you/mnt$ ls
@@ -147,7 +147,7 @@ var-GS000016015-ASM.tsv.bz2
You can also mount the entire Keep namespace in "magic directory" mode:
-/scratch/you$ mkdir mnt
+/scratch/you$ mkdir -p mnt
/scratch/you$ arv-mount mnt &
/scratch/you$ cd mnt/c1bad4b39ca5a924e481008009d94e32+210
/scratch/you/mnt/c1bad4b39ca5a924e481008009d94e32+210$ ls
@@ -159,8 +159,8 @@ var-GS000016015-ASM.tsv.bz2
-Using @arv-mount@ has several significant benefits:
+@arv-mount@ provides several features:
* You can browse, open and read Keep entries as if they are regular files.
* It is easy for existing tools to access files in Keep.
-* Data is downloaded on demand, it is not necessary to download an entire file or collection to start processing
+* Data is downloaded on demand. It is not necessary to download an entire file or collection to start processing.