- 浏览: 153852 次
- 性别:
- 来自: northeast
文章分类
最新评论
-
lightgjc1:
好,支持,赞一下
复制表结构的通用存储过程 -
star022:
很有个性~~
tomcat 异常 Exception loading sessions from persistent storag -
我奋斗:
我也觉得,混江湖的吧。
tomcat 异常 Exception loading sessions from persistent storag -
wenjinglian:
你的图片真的 ;豪放。。。
tomcat 异常 Exception loading sessions from persistent storag -
helenxiao520:
[/b][b][b][/b]
什么是集群?
This chapter describes the caches maintained on a global and session level for sessions. It also describes the optional persistent client caching feature.
I. Object type caching
Content Server and DFC maintain caches of object type definitions. These caches help to ensure fast response times when users access objects. To ensure that the cached information about an object type is accurate, DFC and Content Server have mechanisms to verify the accuracy of a cached object type definition and update it if necessary. The mechanism varies depending on the object types.
1) For object types with names beginning with dm, dmr, and dmi
These object types are the types that are built‑in in a Content Server installation. Their type definitions are relatively static. There are few changes that can be made to the definition of a built‑in type. For these types, the mechanism is an internal process called Change Checker, that periodically checks all the object type definitions in the Content Server’s global cache. If any are found to be out‑of‑date, the process flushes the cache and reloads the type definitions into the global cache. Changes to these types are not visible to existing sessions because the DFC caches are not updated when the change checker refreshes the global cache.
Stopping and restarting a session makes any changes in the global cache visible. If the session was a web‑based client session, it is necessary to restart the web application server. The interval at which the Change Checker runs is configurable, by changing the setting of the database_refresh_interval in the server.ini file, which default value is 1 minute.
2) For custom object types and types with names beginning with dmc
These object types are installed with DAR files or scripts to support client applications.
Their type definitions typically change more often, and the changes may need to be visible to users immediately. For example, a Collaboration Services user can change the structure of a datatable often, and each change modifies the underlying type definition.
To meet that requirement, the mechanism that refreshes cached type definitions for these types is more dynamic than that for the built‑in types.
For these types, the DFC shared cache is updated regularly, at intervals defined by the dfc.cache.type.currency_check_interval key in the dfc.properties file. That key defaults to
300 seconds (5 minutes). It can be reset. Use Documentum Administrator to reset the key.
Additionally, when requested in a fetch method, DFC checks the currency of its cached version against the server’s global cache. If the versions in the caches are found to be mismatched, the object type definition is updated appropriately. If the server’s cache is more current, the DFC caches are updated. If the DFC has a more current version, the server’s cache is updated.
This mechanism ensures that a user who makes the change sees that change immediately and other users in other sessions see it shortly thereafter. Stopping and restarting a session or the web application server is not required to see changes made to these objects.
II. Repository session caches
Repository session caches are caches that are created when a user or application opens a repository session. These caches exist only for the life of the repository session.
1) Object cache
An in‑memory object cache is maintained for each repository session for the duration of the repository session. If persistent caching is requested and enabled, the cache also contains a copy of every object fetched and persistently cached in previous sessions.
2) Query cache
Query results are only cached when persistent caching is requested and persistent caching is enabled. The results are cached in a file. They are not stored in memory. The file is stored with a randomly generated extension on the client application host disk
3) Data dictionary caches
In conjunction with the object cache, DFC maintains a data dictionary cache. The data dictionary cache is a shared cache, shared by all sessions in a multi‑threaded application.
When an object is fetched, the DFC also fetches and caches in memory the object’s associated data dictionary objects if they are not already in the cache.
III. Persistent caching
This section describes persistent caching, a feature supported by the DFC and Content Server, that provides performance benefits during session start up and when users or applications access cached objects and query results.
1) What persistent caching is
Persistent caching is the ability to create, manage, and maintain persistent caches of query results, objects, and the type and data dictionary information associated with persistently cached objects. Persistent caches are maintained across client sessions for each user and repository combination. Persistent caches are implemented through DFC and supported by Content Server.
The ability to cache objects and query results is enabled by default for every repository and every client session. Documentum Webtop takes advantage of this feature.
Applications can take advantage of the feature through the DFC methods that support requests for persistent client caching.
Consistency between the repository and cached objects and query results is checked and maintained using a consistency check rule identified in the method call that references them. A consistency checking rule can be applied to individual objects or query results or a rule can be defined for a set of cached data.
2) Persistent object cache storage location
Persistently cached objects are written to a file on the client disk. For a desktop application, this is the user’s local disk. For a web‑based application, this is the web application server’s disk. The file is written after defined intervals during a user’s session and when the session terminates. The file is stored in the following directory:
root/object_caches/machine_name/repository_id/abbreviated_user_name
root is the value of the dfc.data.local_dir key in the client’s dfc.properties file.
The next time the user starts a session with the repository on the same machine, the file is loaded back into memory.
3) Persistent object type and data dictionary storage location
For each persistently cached object, a persistent cache of its object type definition and data dictionary information is also maintained. These are stored in a file located in the following directory:
root/type_caches/machine_name/repository_id
root is the value in the dfc.data.local_dir key in the client’s dfc.properties file.
4) Query cache storage location
The file that contains the cached query results is stored with a randomly generated extension on the client disk. For a desktop application, this is the user’s local disk. For a web‑based application, this is the web application server’s disk. The files are in the following directory:
On Windows:
\root\qrycache\machine_name\repository_id\user_name
On UNIX:
/root/qrycache/machine_name/repository_id/user_name
root is the value in the dfc.data.local_dir key in the client’s dfc.properties file.
The query cache files for each user consist of a cache.map file and files with randomly generated extensions. The cache.map file maps each cached query to the file that contains
the results of the query (one of the files with the randomly generated extensions).
The queries are cached by user name because access permissions may generate different
results for different users.
Note: The cache.map file and the cached results files are stored in ASCII format. They are accessible and readable through the operating system. If security is an issue, make sure that the directory in which they are stored is truly local to each client, not on a shared disk.
5) Using persistent client caching in an application
Some Documentum clients use persistent client caching by default. If you want to use it in your applications, you must:
1>Ensure that persistent client caching is enabled
Persistent client caching is enabled at the repository and session levels by default.
At the client session level, this is controlled by the dfc.cache.enable_persistence key in dfc.properties.
2>Identify the objects or queries or both that you want to cache
You identify the data to cache in application methods that fetch the objects or execute the query.
3>Define the consistency check rule for cached data
A consistency check rule defines how often cached data is checked for consistency with the repository. The methods that support persistent client caching support a variety of rule options through a method argument.
Fetch
Query
I. Persistent caching and multiple sessions for one user In federated environments or any distributed environment that has multiple repositories, users can work in multiple repositories through one primary client session. For the purposes of persistent caching, each connection to a different repository is treated as a separate session. For example, suppose JohnDoe opens a session with repository A and fetches a persistently cached document. Then, the user also fetches a persistently cached document from repository B. On termination, the DFC writes two persistent object caches: root/object_caches/machine_name/repositoryA/JohnDoe and root/object_caches/machine_name/repositoryB/JohnDoe Similarly, if the user queries either repository and caches the results, DFC creates a query cache file specific to the queried repository and user. II. Currency checking Currency checking, the functionality that is used to ensure that objects in the persistent cache are not out of date. Consistency checking Consistency checking is the process that ensures that cached data accessed by a client is current and consistent with the data in the repository. How often the process is performed for any particular cached object or set of query results is determined by the consistency check rule defined in the method that references the data. The consistency check rule can be a keyword, an integer value, or the name of a cache config object. A keyword or integer value is an explicit directive to DFC that tells DFC how often to conduct the check. A cache config object identifies the data to be cached as part of a set of cached data managed by the consistency check rule defined in the cache config object. The data defined by a cache config object can be objects or queries or both. Using a cache config object to group cached data has the following benefits: • More efficient validation of cached data It is more efficient to validate a group of data than it is to validate each object or set of query results individually. • Helps ensure that applications access current data • Makes it easy to change the consistency check rule because the rule is defined in the cache config object rather than in application method calls • Allows you to define a job to automatically validate cached data Consistency checking is basically a two‑part process: 1. DFC determines whether a consistency check is necessary. 2. DFC conducts the consistency check if needed. The consistency checking process described in this section is applied to all objects in the in‑memory cache, regardless of whether the object is persistently cached or not. Determining if a consistency check is needed To determine whether a check is needed, the DFC uses the consistency check rule defined in the method that references the data. The rule may be expressed as either a keyword, an integer value, or the name of a cache config object. When a keyword or integer defines the rule If the rule was specified as a keyword or an integer value, DFC interprets the rule as a directive on when to perform a consistency check. The directive is one of the following: • Perform a check every time the data is accessed This option means that the data is always checked against the repository. If the cached data is an object, the object is always checked against the object in the repository. If the cached data is a set of query results, the results are always regenerated. The keyword check_always defines this option. • Never perform a consistency check This option directs the DFC to always use the cached data. The cached data is never checked against the repository if it is present in the cache. If the data is not present in the cache, the data is obtained from the server. The keyword check_never defines this option. • Perform a consistency check on the first access only This option directs the DFC to perform a consistency check the first time the cached data is accessed in a session. If the data is accessed again during the session, a consistency check is not conducted. The keyword check_first_access defines this option. • Perform a consistency check after a specified time interval This option directs the DFC to compare the specified interval to the timestamp on the cached data and perform a consistency check only if the interval has expired. The timestamp on the cached data is set when the data is placed in the cache. The interval is expressed in seconds and can be any value greater than 0. When a cache config object defines the rule If a consistency check rule names a cache config object, the DFC uses information from the cache config object to determine whether to perform a consistency check on the cached data. The cache config information is obtained by invoking the CHECK_CACHE_CONFIG administration method and stored in memory with a timestamp that indicates when the information was obtained. The information includes the r_last_changed_date and the client_check_interval property values of the cache config object. When a method defines a consistency check rule by naming a cache config object, DFC first checks whether it has information about the cache config object in its memory. If not, it issues a CHECK_CACHE_CONFIG administration method to obtain the information. If it has information about the cache config object, DFC must determine whether the information is current before using that information to decide whether to perform a consistency check on the cached data. To determine whether the cache config information is current, the DFC compares the stored client_check_interval value to the timestamp on the information. If the interval has expired, the information is considered out of date and DFC executes another CHECK_CACHE_CONFIG method to ask Content Server to provide current information about the cache config object. If the interval has not expired, DFC uses the information that it has in memory. After the DFC has current information about the cache config object, it determines whether the cached data is valid. To determine that, the DFC compares the timestamp on the cached data against the r_last_changed_date property value in the cache config object. If the timestamp is later than the r_last_changed_date value, the cached data is considered usable and no consistency check is performed. If the timestamp is earlier than the r_last_changed_date value, a consistency check is performed on the data. Conducting consistency checks To perform a consistency check on a cached object, DFC uses the i_vstamp property value of the object. If the DFC has determined that a consistency check is needed, it compares the i_vstamp value of the cached object to the i_vstamp value of the object in the repository. If the i_vstamp values are different, DFC refetches the object and resets the time stamp. If they are the same, DFC uses the cached copy. DFC does not perform consistency checks on cached query results. If the cached results are out of date, Content Server re‑executes the query and replaces the cached results with the newly generated results. The default consistency check rule If a fetch method does not include an explicit value for the argument defining a consistency check rule, the default is check_always. That means that DFC checks the i_vstamp value of the in‑memory object against the i_vstamp value of the object in the repository. If a query method that requests persistent caching does not include an explicit value for the argument defining a consistency check rule, the default consistency rule is check_never. This means that DFC uses the cached query results. The client_pcaching_change property The client_pcaching_change property controls whether the persistent caches, including the object caches and all query caches, are flushed when a client session is started. When a client session is started, the DFC checks the cached value of the client_pcaching_change property against the repository value. If the values are different, the DFC flushes all the persistent caches, including the object caches and all query caches. The client_pcaching_change value must be changed in the docbase config object manually, by a Superuser.
发表评论
-
the folder is a lie
2011-07-22 22:51 0dm_sysobject.i_folder_id dm_sy ... -
Documentum xPlore- next generation search technology
2011-05-25 13:56 1973New EMC Documentum xPlore to Re ... -
【转】Controlling Application - a_controlling_app
2011-05-24 16:34 1039This might not be dirty little ... -
【转】When to use registered tables versus object-types with no super type
2011-05-24 16:02 1457The Problem Developer wants to ... -
Job & Method
2011-03-24 16:11 1239Job & Method Defining suc ... -
centera
2011-03-04 16:58 0Q3. 讲的Clip ID那里不是很明白,为什么前面说两个完相 ... -
Utilities for Easy Handling of Administrator Work in Documentum
2011-01-13 12:29 1779Utilities for Easy Handling of ... -
documentum security, user privileges, object-level permissions
2011-01-10 13:38 7019User privileges Basic user ... -
fulltext searchable
2010-12-30 16:46 869DMI_QUEUE_ITEM A queue item ... -
Document/Object store path
2010-12-30 14:19 1053Document/Object store path ... -
Known issues with Java method server
2010-12-28 15:27 936Known issues with Java method s ... -
Troubleshooting agent_exec garbage collection
2010-08-20 09:42 1677There seem to be more and mor ... -
Documentum concurrent_sessions vs max_session_count
2010-08-19 11:14 1169concurrent_sessions in server.i ... -
Helpful DQL
2010-08-19 11:11 3849Helpful DQL: 1. Creating a user ...
相关推荐
Documentum Composer是一款由EMC公司开发的内容管理软件,它属于EMC Documentum产品线的一部分。Documentum是一个企业级的、以文档为中心的内容管理解决方案,它可以帮助企业捕捉、存储、保护、管理、交付和存档关键...
Documentum是一款由 EMC (现为戴尔科技的一部分) 开发的企业内容管理(ECM)系统。这个系统主要用于管理和控制组织内的数字内容,包括文档、图片、视频、音频和其他类型的文件。Documentum的核心功能包括文档管理、...
Documentum是EMC公司开发的一款企业级内容管理系统(Enterprise Content Management,ECM),它主要用于管理和控制组织内的数字内容。在本文中,我们将详细介绍如何搭建一个Documentum环境,以供学习和测试之用。 ...
Documentum是一款由EMC公司(现已被Dell收购)开发的企业级内容管理(ECM,Enterprise Content Management)系统。它提供了全面的文档管理和协作功能,适用于各种规模的企业,尤其在金融、医疗、政府和制造等行业...
5. 设置Documentum环境变量,包括$DOCUMENTUM(Documentum的安装目录)、$DM_HOME($DOCUMENTUM/product/version_number,例如$DOCUMENTUM/product/6.0)以及$DOCUMENTUM_SHARED(EMC Documentum Foundation类的安装...
### Documentum 6.5 架构概览 #### Documentum 技术架构概述 Documentum 6.5 的架构设计旨在提供一个高度可扩展、灵活且可靠的企业内容管理系统(ECM)。该版本强调了服务导向架构(SOA)的重要性,并在多个层面上...
标题“documentum install for linux oracle”表明我们正在讨论在Linux操作系统上安装Documentum与Oracle数据库相关的流程。Documentum是一款企业级的内容管理系统(CMS),而Oracle则是一种广泛应用的关系型数据库...
### Documentum V6.5 安装步骤详解 #### 一、环境准备 在开始安装Documentum V6.5之前,需要确保环境已经准备好。主要包括以下几个方面: 1. **网络配置**:首先需要确保服务器的网络配置正确无误,包括正确的...
文档标题:“Documentum Process Suite, A Comprehensive Overview” 文档描述:“Documentum Process Suite, A Comprehensive Overview” 标签:“Documentum BPM” 核心知识点:EMC Documentum Process Suite...
Documentum 是一款强大的企业内容管理系统(Enterprise Content Management, ECM),由甲骨文公司提供,用于管理组织内的各种非结构化信息,如文档、图像、视频等。这份"Documentum 官方资料"包含了两个关键部分:...
《Documentum内容管理基础》是针对企业级内容管理系统的一个核心概念和实践的详细介绍。Documentum是EMC公司推出的一款强大的企业内容管理系统(ECM),它主要用于管理和控制组织内的数字内容,包括文档、图像、视频...
### Documentum 产品介绍 #### 一、Documentum 产品概述 Documentum 是一款由 EMC 公司开发的企业级内容管理平台,旨在帮助企业管理和优化其内部的信息和文档资源。随着数字化转型的步伐加快,内容管理成为了现代...
Documentum DFC(Documentum Foundation Classes)是EMC Documentum内容管理平台的核心API,它为开发者提供了与Documentum系统交互的底层接口。这个最新的Documentum DFC API版本为开发人员提供了一系列工具,以便...
### Documentum系统管理知识点概述 #### 一、Documentum系统简介 Documentum系统是一款由Documentum Inc.开发的企业级文档管理系统。它旨在帮助企业管理和组织大量的文档数据,支持文档的创建、存储、检索、版本...
### Documentum 6.X 安装与配置详细指南 #### 一、Documentum 6.X 简介 Documentum 是一款由EMC公司提供的企业级文档管理和内容管理系统。Documentum 6.X 版本提供了丰富的功能和服务,包括文档管理、内容存储、...
### Documentum 6.5 DFC Guide:深入解析与应用实践 #### 一、Documentum Foundation Classes (DFC) 概览 **Documentum 6.5 DFC Guide** 是针对EMC®Documentum® Foundation Classes (DFC) 的开发指南,主要介绍...
不错的DOCUMENTUM资料