Librados (Python)

rados 模块是 librados 的 Python 瘦封装。

安装

To install Python libraries for Ceph, see Getting librados for Python.

开工

You can create your own Ceph client using Python. The following tutorial will show you how to import the Ceph Python module, connect to a Ceph cluster, and perform object operations as a client.admin user.

Note

To use the Ceph Python bindings, you must have access to a running Ceph cluster. To set one up quickly, see Getting Started.

First, create a Python source file for your Ceph client.

:linenos:
sudo vim client.py

导入模块

要使用 rados 模块,需在源码文件里导入。

1
     import rados

配置集群句柄

Before connecting to the Ceph Storage Cluster, create a cluster handle. By default, the cluster handle assumes a cluster named ceph (i.e., the default for deployment tools, and our Getting Started guides too), and a client.admin user name. You may change these defaults to suit your needs.

To connect to the Ceph Storage Cluster, your application needs to know where to find the Ceph Monitor. Provide this information to your application by specifying the path to your Ceph configuration file, which contains the location of the initial Ceph monitors.

1
2
3
4
5
6
     import rados, sys

     #Create Handle Examples.
     cluster = rados.Rados(conffile='ceph.conf')
     cluster = rados.Rados(conffile=sys.argv[1])
     cluster = rados.Rados(conffile = 'ceph.conf', conf = dict (keyring = '/path/to/keyring'))

Ensure that the conffile argument provides the path and file name of your Ceph configuration file. You may use the sys module to avoid hard-coding the Ceph configuration path and file name.

Your Python client also requires a client keyring. For this example, we use the client.admin key by default. If you would like to specify the keyring when creating the cluster handle, you may use the conf argument. Alternatively, you may specify the keyring path in your Ceph configuration file. For example, you may add something like the following line to you Ceph configuration file:

keyring = /path/to/ceph.client.admin.keyring

通过 Python 修改配置的额外细节见 配置

连接到集群

Once you have a cluster handle configured, you may connect to the cluster. With a connection to the cluster, you may execute methods that return information about the cluster.

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
     import rados, sys

     cluster = rados.Rados(conffile='ceph.conf')
     print "\nlibrados version: " + str(cluster.version())
     print "Will attempt to connect to: " + str(cluster.conf_get('mon initial members'))

     cluster.connect()
     print "\nCluster ID: " + cluster.get_fsid()

     print "\n\nCluster Statistics"
     print "=================="
     cluster_stats = cluster.get_cluster_stats()

     for key, value in cluster_stats.iteritems():
             print key, value

By default, Ceph authentication is on. Your application will need to know the location of the keyring. The python-ceph module doesn’t have the default location, so you need to specify the keyring path. The easiest way to specify the keyring is to add it to the Ceph configuration file. The following Ceph configuration file example uses the client.admin keyring you generated with ceph-deploy.

1
2
3
     [global]
     # ... elided configuration
     keyring=/path/to/keyring/ceph.client.admin.keyring

管理存储池

When connected to the cluster, the Rados API allows you to manage pools. You can list pools, check for the existence of a pool, create a pool and delete a pool.

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
     print "\n\nPool Operations"
     print "==============="

     print "\nAvailable Pools"
     print "----------------"
     pools = cluster.list_pools()

     for pool in pools:
             print pool

     print "\nCreate 'test' Pool"
     print "------------------"
     cluster.create_pool('test')

     print "\nPool named 'test' exists: " + str(cluster.pool_exists('test'))
     print "\nVerify 'test' Pool Exists"
     print "-------------------------"
     pools = cluster.list_pools()

     for pool in pools:
             print pool

     print "\nDelete 'test' Pool"
     print "------------------"
     cluster.delete_pool('test')
     print "\nPool named 'test' exists: " + str(cluster.pool_exists('test'))

输入/输出上下文

Reading from and writing to the Ceph Storage Cluster requires an input/output context (ioctx). You can create an ioctx with the open_ioctx() or open_ioctx2() method of the Rados class. The ioctx_name parameter is the name of the pool and pool_id is the ID of the pool you wish to use.

1
     ioctx = cluster.open_ioctx('data')

or

1
     ioctx = cluster.open_ioctx2(pool_id)

Once you have an I/O context, you can read/write objects, extended attributes, and perform a number of other operations. After you complete operations, ensure that you close the connection. For example:

1
2
     print "\nClosing the connection."
     ioctx.close()

对象的写入、读取和删除

Once you create an I/O context, you can write objects to the cluster. If you write to an object that doesn’t exist, Ceph creates it. If you write to an object that exists, Ceph overwrites it (except when you specify a range, and then it only overwrites the range). You may read objects (and object ranges) from the cluster. You may also remove objects from the cluster. For example:

1
2
3
4
5
6
7
8
print "\nWriting object 'hw' with contents 'Hello World!' to pool 'data'."
ioctx.write_full("hw", "Hello World!")

print "\n\nContents of object 'hw'\n------------------------\n"
print ioctx.read("hw")

print "\nRemoving object 'hw'"
ioctx.remove_object("hw")

XATTRS 的读取和写入

Once you create an object, you can write extended attributes (XATTRs) to the object and read XATTRs from the object. For example:

1
2
3
4
5
print "\n\nWriting XATTR 'lang' with value 'en_US' to object 'hw'"
ioctx.set_xattr("hw", "lang", "en_US")

print "\n\nGetting XATTR 'lang' from object 'hw'\n"
print ioctx.get_xattr("hw", "lang")

罗列对象

If you want to examine the list of objects in a pool, you may retrieve the list of objects and iterate over them with the object iterator. For example:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
object_iterator = ioctx.list_objects()

while True :

        try :
                rados_object = object_iterator.next()
                print "Object contents = " + rados_object.read()

        except StopIteration :
                break

The Object class provides a file-like interface to an object, allowing you to read and write content and extended attributes. Object operations using the I/O context provide additional functionality and asynchronous capabilities.

集群句柄 API

The Rados class provides an interface into the Ceph Storage Daemon.

配置

The Rados class provides methods for getting and setting configuration values, reading the Ceph configuration file, and parsing arguments. You do not need to be connected to the Ceph Storage Cluster to invoke the following methods. See Storage Cluster Configuration for details on settings.

Rados.conf_get(option)
Rados.conf_set(option, val)
Rados.conf_read_file(path=None)
Rados.conf_parse_argv(args)

Rados.conf_parse_argv(self, args)

Parse known arguments from args, and remove; returned args contain only those unknown to ceph

Rados.version()

Rados.version(self)

Get the version number of the librados C library.

Returns

a tuple of (major, minor, extra) components of the librados version

连接管理

Once you configure your cluster handle, you may connect to the cluster, check the cluster fsid, retrieve cluster statistics, and disconnect (shutdown) from the cluster. You may also assert that the cluster handle is in a particular state (e.g., “configuring”, “connecting”, etc.).

Rados.connect(timeout=0)

Rados.connect(self, timeout=0)

Connect to the cluster. Use shutdown() to release resources.

Rados.shutdown()

Rados.shutdown(self)

Disconnects from the cluster. Call this explicitly when a Rados.connect()ed object is no longer used.

Rados.get_fsid()

Rados.get_fsid(self)

Get the fsid of the cluster as a hexadecimal string.

Raises

Error

Returns

str - cluster fsid

Rados.get_cluster_stats()

Rados.get_cluster_stats(self)

Read usage info about the cluster

This tells you total space, space used, space available, and number of objects. These are not updated immediately when data is written, they are eventually consistent.

Returns

dict - contains the following keys:

  • kb (int) - total space

  • kb_used (int) - space used

  • kb_avail (int) - free space available

  • num_objects (int) - number of objects

class rados.Rados
require_state(*args)

检查一下 Rados 对象是否处于指定状态。

Parameters

args – Any number of states to check as separate arguments

Raises

RadosStateError

存储池操作

To use pool operation methods, you must connect to the Ceph Storage Cluster first. You may list the available pools, create a pool, check to see if a pool exists, and delete a pool.

Rados.list_pools()

Rados.list_pools(self)

Gets a list of pool names.

Returns

list - of pool names.

Rados.create_pool(pool_name, crush_rule=None)
Rados.pool_exists()
Rados.delete_pool(pool_name)

输入/输出上下文 API

To write data to and read data from the Ceph Object Store, you must create an Input/Output context (ioctx). The Rados class provides open_ioctx() and open_ioctx2() methods. The remaining ioctx operations involve invoking methods of the Ioctx and other classes.

Rados.open_ioctx(ioctx_name)
Ioctx.require_ioctx_open()

Ioctx.require_ioctx_open(self)

Checks if the rados.Ioctx object state is ‘open’

Raises

IoctxStateError

Ioctx.get_stats()

Ioctx.get_stats(self)

Get pool usage statistics

Returns

dict - contains the following keys:

  • num_bytes (int) - size of pool in bytes

  • num_kb (int) - size of pool in kbytes

  • num_objects (int) - number of objects in the pool

  • num_object_clones (int) - number of object clones

  • num_object_copies (int) - number of object copies

  • num_objects_missing_on_primary (int) - number of objets

    missing on primary

  • num_objects_unfound (int) - number of unfound objects

  • num_objects_degraded (int) - number of degraded objects

  • num_rd (int) - bytes read

  • num_rd_kb (int) - kbytes read

  • num_wr (int) - bytes written

  • num_wr_kb (int) - kbytes written

Ioctx.get_last_version()

Ioctx.get_last_version(self)

Return the version of the last object read or written to.

This exposes the internal version number of the last object read or written via this io context

Returns

version of the last object used

Ioctx.close()

Ioctx.close(self)

Close a rados.Ioctx object.

This just tells librados that you no longer need to use the io context. It may not be freed immediately if there are pending asynchronous requests on it, but you should not use an io context again after calling this function on it.

Object Operations

The Ceph Storage Cluster stores data as objects. You can read and write objects synchronously or asynchronously. You can read and write from offsets. An object has a name (or key) and data.

Ioctx.aio_write(object_name, to_write, offset=0, oncomplete=None, onsafe=None)
Ioctx.aio_write_full(object_name, to_write, oncomplete=None, onsafe=None)
Ioctx.aio_append(object_name, to_append, oncomplete=None, onsafe=None)
Ioctx.write(key, data, offset=0)
Ioctx.write_full(key, data)
Ioctx.aio_flush()

Ioctx.aio_flush(self)

Block until all pending writes in an io context are safe

Raises

Error

Ioctx.set_locator_key(loc_key)
Ioctx.aio_read(object_name, length, offset, oncomplete)
Ioctx.read(key, length=8192, offset=0)
Ioctx.stat(key)
Ioctx.trunc(key, size)
Ioctx.remove_object(key)

对象的扩展属性

You may set extended attributes (XATTRs) on an object. You can retrieve a list of objects or XATTRs and iterate over them.

Ioctx.set_xattr(key, xattr_name, xattr_value)
Ioctx.get_xattrs(oid)
XattrIterator.__next__()

Get the next xattr on the object

Raises

StopIteration

Returns

pair - of name and value of the next Xattr

Ioctx.get_xattr(key, xattr_name)
Ioctx.rm_xattr(key, xattr_name)

Object Interface

From an I/O context, you can retrieve a list of objects from a pool and iterate over them. The object interface provide makes each object look like a file, and you may perform synchronous operations on the objects. For asynchronous operations, you should use the I/O context methods.

Ioctx.list_objects()

Ioctx.list_objects(self)

Get ObjectIterator on rados.Ioctx object.

Returns

ObjectIterator

ObjectIterator.__next__()

Get the next object name and locator in the pool

Raises

StopIteration

Returns

next rados.Ioctx Object

Object.read(length = 1024*1024)
Object.write(string_to_write)
Object.get_xattrs()
Object.get_xattr(xattr_name)
Object.set_xattr(xattr_name, xattr_value)
Object.rm_xattr(xattr_name)
Object.stat()
Object.remove()