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  • SBUG Session: The Enterprise Cache

    - by EltonStoneman
    [Source: http://geekswithblogs.net/EltonStoneman] I did a session on "The Enterprise Cache" at the UK SOA/BPM User Group yesterday which generated some useful discussion. The proposal was for a dedicated caching layer which all app servers and service providers can hook into, sharing resources and common data. The architecture might end up like this: I'll update this post with a link to the slide deck once it's available. The next session will have Udi Dahan walking through nServiceBus, register on EventBrite if you want to come along. Synopsis Looked at the benefits and drawbacks of app-centric isolated caches, compared to an enterprise-wide shared cache running on dedicated nodes; Suggested issues and risks around caching including staleness of data, resource usage, performance and testing; Walked through a generic service cache implemented as a WCF behaviour – suitable for IIS- or BizTalk-hosted services - which I'll be releasing on CodePlex shortly; Listed common options for cache providers and their offerings. Discussion Cache usage. Different value propositions for utilising the cache: improved performance, isolation from underlying systems (e.g. service output caching can have a TTL large enough to cover downtime), reduced resource impact – CPU, memory, SQL and cost (e.g. caching results of paid-for services). Dedicated cache nodes. Preferred over in-host caching provided latency is acceptable. Depending on cache provider, can offer easy scalability and global replication so cache clients always use local nodes. Restriction of AppFabric Caching to Windows Server 2008 not viewed as a concern. Security. Limited security model in most cache providers. Options for securing cache content suggested as custom implementations. Obfuscating keys and serialized values may mean additional security is not needed. Depending on security requirements and architecture, can ensure cache servers only accessible to cache clients via IPsec. Staleness. Generally thought to be an overrated problem. Thinking in line with eventual consistency, that serving up stale data may not be a significant issue. Good technical arguments support this, although I suspect business users will be harder to persuade. Providers. Positive feedback for AppFabric Caching – speed, configurability and richness of the distributed model making it a good enterprise choice. .NET port of memcached well thought of for performance but lack of replication makes it less suitable for these shared scenarios. Replicated fork – repcached – untried and less active than memcached. NCache also well thought of, but Express version too limited for enterprise scenarios, and commercial versions look costly compared to AppFabric.

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  • How should I force-enable BIND's persistent cache, or Unbound's persistent cache

    - by Jacob Rabinsun
    I am trying to run a local DNS server on my home computer so that I can both increase DNS lookups speed and reduce bandwidth use, so that both my laptop and my PC can do lookups faster. I have got BIND 9 running very smoothly, there is only one simple problem, and that being the fact that BIND is not a persistent DNS cache, and if I restart its service, the whole cash would be wiped out. So, is there a way that I could make BIND9 keep its cache after system restart? Also, which one is better Unbound or BIND? Which one would you suggest? Does Unbound DNS have a persistent cache or can it be enabled?

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  • I am trying to figure out the best way to understand how to cache domain objects

    - by Brett Ryan
    I've always done this wrong, I'm sure a lot of others have too, hold a reference via a map and write through to DB etc.. I need to do this right, and I just don't know how to go about it. I know how I want my objects to be cached but not sure on how to achieve it. What complicates things is that I need to do this for a legacy system where the DB can change without notice to my application. So in the context of a web application, let's say I have a WidgetService which has several methods: Widget getWidget(); Collection<Widget> getAllWidgets(); Collection<Widget> getWidgetsByCategory(String categoryCode); Collection<Widget> getWidgetsByContainer(Integer parentContainer); Collection<Widget> getWidgetsByStatus(String status); Given this, I could decide to cache by method signature, i.e. getWidgetsByCategory("AA") would have a single cache entry, or I could cache widgets individually, which would be difficult I believe; OR, a call to any method would then first cache ALL widgets with a call to getAllWidgets() but getAllWidgets() would produce caches that match all the keys for the other method invocations. For example, take the following untested theoretical code. Collection<Widget> getAllWidgets() { Entity entity = cache.get("ALL_WIDGETS"); Collection<Widget> res; if (entity == null) { res = loadCache(); } else { res = (Collection<Widget>) entity.getValue(); } return res } Collection<Widget> loadCache() { // Get widgets from underlying DB Collection<Widget> res = db.getAllWidgets(); cache.put("ALL_WIDGETS", res); Map<String, List<Widget>> byCat = new HashMap<>(); for (Widget w : res) { // cache by different types of method calls, i.e. by category if (!byCat.containsKey(widget.getCategory()) { byCat.put(widget.getCategory(), new ArrayList<Widget>); } byCat.get(widget.getCatgory(), widget); } cacheCategories(byCat); return res; } Collection<Widget> getWidgetsByCategory(String categoryCode) { CategoryCacheKey key = new CategoryCacheKey(categoryCode); Entity ent = cache.get(key); if (entity == null) { loadCache(); } ent = cache.get(key); return ent == null ? Collections.emptyList() : (Collection<Widget>)ent.getValue(); } NOTE: I have not worked with a cache manager, the above code illustrates cache as some object that may hold caches by key/value pairs, though it's not modelled on any specific implementation. Using this I have the benefit of being able to cache all objects in the different ways they will be called with only single objects on the heap, whereas if I were to cache the method call invocation via say Spring It would (I believe) cache multiple copies of the objects. I really wish to try and understand the best ways to cache domain objects before I go down the wrong path and make it harder for myself later. I have read the documentation on the Ehcache website and found various articles of interest, but nothing to give a good solid technique. Since I'm working with an ERP system, some DB calls are very complicated, not that the DB is slow, but the business representation of the domain objects makes it very clumsy, coupled with the fact that there are actually 11 different DB's where information can be contained that this application is consolidating in a single view, this makes caching quite important.

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  • Cache efficient code

    - by goldenmean
    This could sound a subjective question, but what i am looking for is specific instances which you would have encountered related to this. 1) How to make a code, cache effective-cache friendly? (More cache hits, as less cahce misses as possible). from both perspectives, data cache & program cache(instruction cache). i.e. What all things in one's code, related to data structures, code constructs one should take care of to make it cache effective. 2) Are there any particular data structures one must use, must avoid,or particular way of accessing the memers of that structure etc.. to make code cache effective. 3) Are there any program constructs(if, for, switch, break, goto,...), code-flow(for inside a if, if inside a for, etc...) one should follow/avoid in this matter? I am looking forward to hear individual experiences related to making a cache efficient code in general. It can be any programming language(C,C++,ASsembly,...), any hardware target(ARM,Intel,PowerPC,...), any OS(Windows,Linux,Symbian,...) etc.. More the variety, it will help better to understand it deeply.

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  • Too many Bind query (cache) denied, DNS attack?

    - by Jake
    Once Bind crashed and I did: tail -f /var/log/messages I see a massive number of logs every second. Is this a DNS attack? or is there something wrong? Sometimes I see a domain in logs like this: dOmAin.com (upper and lower). As you see there is only one single domain in the logs with different IPs Oct 10 02:21:26 mail named[20831]: client 74.125.189.18#38921: query (cache) 'ns1.domain2.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 192.221.144.171#38833: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 74.125.189.17#42428: query (cache) 'ns2.domain2.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 192.221.146.27#37899: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 193.203.82.66#39263: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 8.0.16.170#59723: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 80.169.197.66#32903: query (cache) 'dOmAin.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 134.58.60.1#47558: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 192.221.146.34#47387: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 8.0.16.8#59392: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 74.125.189.19#64395: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 217.72.163.3#42190: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 83.146.21.252#22020: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 192.221.146.116#57342: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 193.203.82.66#52020: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 8.0.16.72#64317: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 80.169.197.66#31989: query (cache) 'dOmAin.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 74.125.189.18#47436: query (cache) 'ns2.domain2.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 74.125.189.16#44005: query (cache) 'ns1.domain2.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 85.132.31.10#50379: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 94.241.128.3#60106: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 85.132.31.10#59118: query (cache) 'domain.com/A/IN' denied Oct 10 02:21:26 mail named[20831]: client 212.95.135.78#27811: query (cache) 'domain.com/A/IN' denied /etc/resolv.conf ; generated by /sbin/dhclient-script nameserver 4.2.2.4 nameserver 8.8.4.4 Bind config: // generated by named-bootconf.pl options { directory "/var/named"; /* * If there is a firewall between you and nameservers you want * to talk to, you might need to uncomment the query-source * directive below. Previous versions of BIND always asked * questions using port 53, but BIND 8.1 uses an unprivileged * port by default. */ // query-source address * port 53; allow-transfer { none; }; allow-recursion { localnets; }; //listen-on-v6 { any; }; notify no; }; // // a caching only nameserver config // controls { inet 127.0.0.1 allow { localhost; } keys { rndckey; }; }; zone "." IN { type hint; file "named.ca"; }; zone "localhost" IN { type master; file "localhost.zone"; allow-update { none; }; }; zone "0.0.127.in-addr.arpa" IN { type master; file "named.local"; allow-update { none; }; };

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  • Datanucleus/JDO Level 2 Cache on Google App Engine

    - by Thilo
    Is it possible (and does it make sense) to use the JDO Level 2 Cache for the Google App Engine Datastore? First of all, why is there no documentation about this on Google's pages? Are there some problems with it? Do we need to set up limits to protect our memcache quota? According to DataNucleus on Stackoverflow, you can set the following persistence properties: datanucleus.cache.level2.type=javax.cache datanucleus.cache.level2.cacheName={cache name} Is that all? Can we choose any cache name? Other sources on the Internet report using different settings. Also, it seems we need to download the DataNucleus Cache support plugin. Which version would be appropriate? And do we just place it in WEB-INF/lib or does it need more setup to activate it?

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  • Collections not read from hibernate/ehcache second-level-cache

    - by Mark van Venrooij
    I'm trying to cache lazy loaded collections with ehcache/hibernate in a Spring project. When I execute a session.get(Parent.class, 123) and browse through the children multiple times a query is executed every time to fetch the children. The parent is only queried the first time and then resolved from the cache. Probably I'm missing something, but I can't find the solution. Please see the relevant code below. I'm using Spring (3.2.4.RELEASE) Hibernate(4.2.1.Final) and ehcache(2.6.6) The parent class: @Entity @Table(name = "PARENT") @Cacheable @Cache(usage = CacheConcurrencyStrategy.READ_WRITE, include = "all") public class ServiceSubscriptionGroup implements Serializable { /** The Id. */ @Id @Column(name = "ID") private int id; @OneToMany(fetch = FetchType.LAZY, mappedBy = "parent") @Cache(usage = CacheConcurrencyStrategy.READ_WRITE) private List<Child> children; public List<Child> getChildren() { return children; } public void setChildren(List<Child> children) { this.children = children; } @Override public boolean equals(Object o) { if (this == o) return true; if (o == null || getClass() != o.getClass()) return false; Parent that = (Parent) o; if (id != that.id) return false; return true; } @Override public int hashCode() { return id; } } The child class: @Entity @Table(name = "CHILD") @Cacheable @Cache(usage = CacheConcurrencyStrategy.READ_WRITE, include = "all") public class Child { @Id @Column(name = "ID") private int id; @ManyToOne(fetch = FetchType.LAZY, cascade = CascadeType.ALL) @JoinColumn(name = "PARENT_ID") @Cache(usage = CacheConcurrencyStrategy.READ_WRITE) private Parent parent; public int getId() { return id; } public void setId(final int id) { this.id = id; } private Parent getParent(){ return parent; } private void setParent(Parent parent) { this.parent = parent; } @Override public boolean equals(final Object o) { if (this == o) { return true; } if (o == null || getClass() != o.getClass()) { return false; } final Child that = (Child) o; return id == that.id; } @Override public int hashCode() { return id; } } The application context: <bean id="sessionFactory" class="org.springframework.orm.hibernate4.LocalSessionFactoryBean"> <property name="dataSource" ref="dataSource" /> <property name="annotatedClasses"> <list> <value>Parent</value> <value>Child</value> </list> </property> <property name="hibernateProperties"> <props> <prop key="hibernate.dialect">org.hibernate.dialect.SQLServer2008Dialect</prop> <prop key="hibernate.hbm2ddl.auto">validate</prop> <prop key="hibernate.ejb.naming_strategy">org.hibernate.cfg.ImprovedNamingStrategy</prop> <prop key="hibernate.connection.charSet">UTF-8</prop> <prop key="hibernate.show_sql">true</prop> <prop key="hibernate.format_sql">true</prop> <prop key="hibernate.use_sql_comments">true</prop> <!-- cache settings ehcache--> <prop key="hibernate.cache.use_second_level_cache">true</prop> <prop key="hibernate.cache.use_query_cache">true</prop> <prop key="hibernate.cache.region.factory_class"> org.hibernate.cache.ehcache.SingletonEhCacheRegionFactory</prop> <prop key="hibernate.generate_statistics">true</prop> <prop key="hibernate.cache.use_structured_entries">true</prop> <prop key="hibernate.cache.use_query_cache">true</prop> <prop key="hibernate.transaction.factory_class"> org.hibernate.engine.transaction.internal.jta.JtaTransactionFactory</prop> <prop key="hibernate.transaction.jta.platform"> org.hibernate.service.jta.platform.internal.JBossStandAloneJtaPlatform</prop> </props> </property> </bean> The testcase I'm running: @Test public void testGetParentFromCache() { for (int i = 0; i <3 ; i++ ) { getEntity(); } } private void getEntity() { Session sess = sessionFactory.openSession() sess.setCacheMode(CacheMode.NORMAL); Transaction t = sess.beginTransaction(); Parent p = (Parent) s.get(Parent.class, 123); Assert.assertNotNull(p); Assert.assertNotNull(p.getChildren().size()); t.commit(); sess.flush(); sess.clear(); sess.close(); } In the logging I can see that the first time 2 queries are executed getting the parent and getting the children. Furthermore the logging shows that the child entities as well as the collection are stored in the 2nd level cache. However when reading the collection a query is executed to fetch the children on second and third attempt.

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  • Organization &amp; Architecture UNISA Studies &ndash; Chap 4

    - by MarkPearl
    Learning Outcomes Explain the characteristics of memory systems Describe the memory hierarchy Discuss cache memory principles Discuss issues relevant to cache design Describe the cache organization of the Pentium Computer Memory Systems There are key characteristics of memory… Location – internal or external Capacity – expressed in terms of bytes Unit of Transfer – the number of bits read out of or written into memory at a time Access Method – sequential, direct, random or associative From a users perspective the two most important characteristics of memory are… Capacity Performance – access time, memory cycle time, transfer rate The trade off for memory happens along three axis… Faster access time, greater cost per bit Greater capacity, smaller cost per bit Greater capacity, slower access time This leads to people using a tiered approach in their use of memory   As one goes down the hierarchy, the following occurs… Decreasing cost per bit Increasing capacity Increasing access time Decreasing frequency of access of the memory by the processor The use of two levels of memory to reduce average access time works in principle, but only if conditions 1 to 4 apply. A variety of technologies exist that allow us to accomplish this. Thus it is possible to organize data across the hierarchy such that the percentage of accesses to each successively lower level is substantially less than that of the level above. A portion of main memory can be used as a buffer to hold data temporarily that is to be read out to disk. This is sometimes referred to as a disk cache and improves performance in two ways… Disk writes are clustered. Instead of many small transfers of data, we have a few large transfers of data. This improves disk performance and minimizes processor involvement. Some data designed for write-out may be referenced by a program before the next dump to disk. In that case the data is retrieved rapidly from the software cache rather than slowly from disk. Cache Memory Principles Cache memory is substantially faster than main memory. A caching system works as follows.. When a processor attempts to read a word of memory, a check is made to see if this in in cache memory… If it is, the data is supplied, If it is not in the cache, a block of main memory, consisting of a fixed number of words is loaded to the cache. Because of the phenomenon of locality of references, when a block of data is fetched into the cache, it is likely that there will be future references to that same memory location or to other words in the block. Elements of Cache Design While there are a large number of cache implementations, there are a few basic design elements that serve to classify and differentiate cache architectures… Cache Addresses Cache Size Mapping Function Replacement Algorithm Write Policy Line Size Number of Caches Cache Addresses Almost all non-embedded processors support virtual memory. Virtual memory in essence allows a program to address memory from a logical point of view without needing to worry about the amount of physical memory available. When virtual addresses are used the designer may choose to place the cache between the MMU (memory management unit) and the processor or between the MMU and main memory. The disadvantage of virtual memory is that most virtual memory systems supply each application with the same virtual memory address space (each application sees virtual memory starting at memory address 0), which means the cache memory must be completely flushed with each application context switch or extra bits must be added to each line of the cache to identify which virtual address space the address refers to. Cache Size We would like the size of the cache to be small enough so that the overall average cost per bit is close to that of main memory alone and large enough so that the overall average access time is close to that of the cache alone. Also, larger caches are slightly slower than smaller ones. Mapping Function Because there are fewer cache lines than main memory blocks, an algorithm is needed for mapping main memory blocks into cache lines. The choice of mapping function dictates how the cache is organized. Three techniques can be used… Direct – simplest technique, maps each block of main memory into only one possible cache line Associative – Each main memory block to be loaded into any line of the cache Set Associative – exhibits the strengths of both the direct and associative approaches while reducing their disadvantages For detailed explanations of each approach – read the text book (page 148 – 154) Replacement Algorithm For associative and set associating mapping a replacement algorithm is needed to determine which of the existing blocks in the cache must be replaced by a new block. There are four common approaches… LRU (Least recently used) FIFO (First in first out) LFU (Least frequently used) Random selection Write Policy When a block resident in the cache is to be replaced, there are two cases to consider If no writes to that block have happened in the cache – discard it If a write has occurred, a process needs to be initiated where the changes in the cache are propagated back to the main memory. There are several approaches to achieve this including… Write Through – all writes to the cache are done to the main memory as well at the point of the change Write Back – when a block is replaced, all dirty bits are written back to main memory The problem is complicated when we have multiple caches, there are techniques to accommodate for this but I have not summarized them. Line Size When a block of data is retrieved and placed in the cache, not only the desired word but also some number of adjacent words are retrieved. As the block size increases from very small to larger sizes, the hit ratio will at first increase because of the principle of locality, which states that the data in the vicinity of a referenced word are likely to be referenced in the near future. As the block size increases, more useful data are brought into cache. The hit ratio will begin to decrease as the block becomes even bigger and the probability of using the newly fetched information becomes less than the probability of using the newly fetched information that has to be replaced. Two specific effects come into play… Larger blocks reduce the number of blocks that fit into a cache. Because each block fetch overwrites older cache contents, a small number of blocks results in data being overwritten shortly after they are fetched. As a block becomes larger, each additional word is farther from the requested word and therefore less likely to be needed in the near future. The relationship between block size and hit ratio is complex, and no set approach is judged to be the best in all circumstances.   Pentium 4 and ARM cache organizations The processor core consists of four major components: Fetch/decode unit – fetches program instruction in order from the L2 cache, decodes these into a series of micro-operations, and stores the results in the L2 instruction cache Out-of-order execution logic – Schedules execution of the micro-operations subject to data dependencies and resource availability – thus micro-operations may be scheduled for execution in a different order than they were fetched from the instruction stream. As time permits, this unit schedules speculative execution of micro-operations that may be required in the future Execution units – These units execute micro-operations, fetching the required data from the L1 data cache and temporarily storing results in registers Memory subsystem – This unit includes the L2 and L3 caches and the system bus, which is used to access main memory when the L1 and L2 caches have a cache miss and to access the system I/O resources

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  • Is it OK to set "Cache-Control: public" when sending “304 Not Modified” for images stored in the dat

    - by Emilien
    After asking a question about sending “304 Not Modified” for images stored in the in the Google App Engine datastore, I now have a question about Cache-Control. My app now sends Last-Modified and Etag, but by default GAE alsto sends Cache-Control: no-cache. According to this page: The “no-cache” directive, according to the RFC, tells the browser that it should revalidate with the server before serving the page from the cache. [...] In practice, IE and Firefox have started treating the no-cache directive as if it instructs the browser not to even cache the page. As I DO want browsers to cache the image, I've added the following line to my code: self.response.headers['Cache-Control'] = "public" According to the same page as before: The “cache-control: public” directive [...] tells the browser and proxies [...] that the page may be cached. This is good for non-sensitive pages, as caching improves performance. The question is if this could be harmful to the application in some way? Would it be best to send Cache-Control: must-revalidate to "force" the browser to revalidate (I suppose that is the behavior that was originally the reason behind sending Cache-Control: no-cache) This directive insists that the browser must revalidate the page against the server before serving it from cache. Note that it implicitly lets the browser cache the page.

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  • Squid refresh_pattern won't cache "Expires: ..."

    - by Marcelo Cantos
    Background I frequent the OpenGL ES documentation site at http://www.khronos.org/opengles/sdk/1.1/docs/man/. Even though the content is completely static, it seems to force a reload on every single page I visit, which is very annoying. I have a squid 3.0 proxy set up (apt-get install squid3 on Ubuntu 10.04), and I added a refresh_pattern to force the pages to cache: refresh_pattern ^http://www.khronos.org/opengles/sdk/1\.1/docs/man/ … 1440 20% 10080 … override-expire ignore-reload ignore-no-cache ignore-private ignore-no-store This is all on one line, of course. While this appears to work for the XHTML documents (e.g., glBindTexture), it fails to cache the linked content, such as the DTD, some .ent files (?) and some XSL files. The delay in fetching these extra files delays rendering of the main document, so my principal annoyance isn't fixed. The only difference I can glean with these ancillary files is that they come with an Expires: header set to the current time, whereas the XHTML document has none. But I would have expected the override-expire option to fix this. I have confirmed that documents have the same base URL. I have also truncated the pattern to varying degrees, with no effect. My questions Why does the override-expire option not seem to work? Is there a simple way to tell squid to unconditionally cache a document, no matter what it finds in the response headers? (Hopefully) relevant output cache.log Jan 01 10:33:30 1970/06/25 21:18:27| Processing Configuration File: /etc/squid3/squid.conf (depth 0) Jan 01 10:33:30 1970/06/25 21:18:27| WARNING: use of 'override-expire' in 'refresh_pattern' violates HTTP Jan 01 10:33:30 1970/06/25 21:18:27| WARNING: use of 'ignore-reload' in 'refresh_pattern' violates HTTP Jan 01 10:33:30 1970/06/25 21:18:27| WARNING: use of 'ignore-no-cache' in 'refresh_pattern' violates HTTP Jan 01 10:33:30 1970/06/25 21:18:27| WARNING: use of 'ignore-no-store' in 'refresh_pattern' violates HTTP Jan 01 10:33:30 1970/06/25 21:18:27| WARNING: use of 'ignore-private' in 'refresh_pattern' violates HTTP Jan 01 10:33:30 1970/06/25 21:18:27| DNS Socket created at 0.0.0.0, port 37082, FD 10 Jan 01 10:33:30 1970/06/25 21:18:27| Adding nameserver 192.168.1.1 from /etc/resolv.conf Jan 01 10:33:30 1970/06/25 21:18:27| Accepting HTTP connections at 0.0.0.0, port 3128, FD 11. Jan 01 10:33:30 1970/06/25 21:18:27| Accepting ICP messages at 0.0.0.0, port 3130, FD 13. Jan 01 10:33:30 1970/06/25 21:18:27| HTCP Disabled. Jan 01 10:33:30 1970/06/25 21:18:27| Loaded Icons. Jan 01 10:33:30 1970/06/25 21:18:27| Ready to serve requests. access.log Jun 25 21:19:35 2010.710 0 192.168.1.50 TCP_MEM_HIT/200 2452 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/glBindTexture.xml - NONE/- text/xml Jun 25 21:19:36 2010.263 543 192.168.1.50 TCP_MISS/304 322 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/xhtml1-transitional.dtd - DIRECT/74.54.224.215 - Jun 25 21:19:36 2010.276 556 192.168.1.50 TCP_MISS/304 370 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/mathml.xsl - DIRECT/74.54.224.215 - Jun 25 21:19:36 2010.666 278 192.168.1.50 TCP_MISS/304 322 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/xhtml-lat1.ent - DIRECT/74.54.224.215 - Jun 25 21:19:36 2010.958 279 192.168.1.50 TCP_MISS/304 322 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/xhtml-symbol.ent - DIRECT/74.54.224.215 - Jun 25 21:19:37 2010.251 276 192.168.1.50 TCP_MISS/304 322 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/xhtml-special.ent - DIRECT/74.54.224.215 - Jun 25 21:19:37 2010.332 0 192.168.1.50 TCP_IMS_HIT/304 316 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/ctop.xsl - NONE/- text/xml Jun 25 21:19:37 2010.332 0 192.168.1.50 TCP_IMS_HIT/304 316 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/pmathml.xsl - NONE/- text/xml store.log Jun 25 21:19:36 2010.263 RELEASE -1 FFFFFFFF D3056C09B42659631A65A08F97794E45 304 1277464776 -1 1277464776 unknown -1/0 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/xhtml1-transitional.dtd Jun 25 21:19:36 2010.276 RELEASE -1 FFFFFFFF 9BF7F37442FD84DD0AC0479E38329E3C 304 1277464776 -1 1277464776 unknown -1/0 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/mathml.xsl Jun 25 21:19:36 2010.666 RELEASE -1 FFFFFFFF 7BCFCE88EC91578C8E2589CB6310B3A1 304 1277464776 -1 1277464776 unknown -1/0 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/xhtml-lat1.ent Jun 25 21:19:36 2010.958 RELEASE -1 FFFFFFFF ECF1B24E437CFAA08A2785AA31A042A0 304 1277464777 -1 1277464777 unknown -1/0 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/xhtml-symbol.ent Jun 25 21:19:37 2010.251 RELEASE -1 FFFFFFFF 36FE3D76C80F0106E6E9F3B7DCE924FA 304 1277464777 -1 1277464777 unknown -1/0 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/xhtml-special.ent Jun 25 21:19:37 2010.332 RELEASE -1 FFFFFFFF A33E5A5CCA2BFA059C0FA25163485192 304 1277462871 1221139523 1277462871 text/xml -1/0 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/ctop.xsl Jun 25 21:19:37 2010.332 RELEASE -1 FFFFFFFF E2CF8854443275755915346052ACE14E 304 1277462872 1221139523 1277462872 text/xml -1/0 GET http://www.khronos.org/opengles/sdk/1.1/docs/man/pmathml.xsl

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  • Help create a unit test for test response header, specifically Cache-Control, in determining if cach

    - by VajNyiaj
    Scenario: I have a base controller which disables caching within the OnActionExecuting override. protected override void OnActionExecuting(ActionExecutingContext filterContext) { filterContext.HttpContext.Response.Cache.SetExpires(DateTime.UtcNow.AddDays(-1)); filterContext.HttpContext.Response.Cache.SetValidUntilExpires(false); filterContext.HttpContext.Response.Cache.SetRevalidation(HttpCacheRevalidation.AllCaches); filterContext.HttpContext.Response.Cache.SetCacheability(HttpCacheability.NoCache); //IE filterContext.HttpContext.Response.Cache.SetNoStore(); //FireFox } How can I create a Unit Test to test this behavior?

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  • Clear Asp.Net cache from outside of application (not using source code)

    - by TheJudge
    Hi, I have a asp.net web application and I'm using cache (HttpRuntime.Cache) to save some stuff from db. I also update db from time to time so that data in db does not match the data in my application's cache. Is there any way how to clear my application's cache without modifying any source code or republishing the page? I tried to restart IIS and to clear browsers cache but nothing helps. Please help.

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  • Working with the IE cache from C# & WPF

    - by Eric
    I'm writing a program in C# using the WPF framework. I need to display images, and I'd like to cache them to avoid downloading them constantly. I can code my own cache, however, IE already has a caching system. I can find code to read entries out of the IE cache, however I've found nothing dealing with the issue of adding items to the cache. Is there a good way to do it, or should I just implement a separate cache?

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  • Aggregating cache data from OCEP in CQL

    - by Manju James
    There are several use cases where OCEP applications need to join stream data with external data, such as data available in a Coherence cache. OCEP’s streaming language, CQL, supports simple cache-key based joins of stream data with data in Coherence (more complex queries will be supported in a future release). However, there are instances where you may need to aggregate the data in Coherence based on input data from a stream. This blog describes a sample that does just that. For our sample, we will use a simplified credit card fraud detection use case. The input to this sample application is a stream of credit card transaction data. The input stream contains information like the credit card ID, transaction time and transaction amount. The purpose of this application is to detect suspicious transactions and send out a warning event. For the sake of simplicity, we will assume that all transactions with amounts greater than $1000 are suspicious. The transaction history is available in a Coherence distributed cache. For every suspicious transaction detected, a warning event must be sent with maximum amount, total amount and total number of transactions over the past 30 days, as shown in the diagram below. Application Input Stream input to the EPN contains events of type CCTransactionEvent. This input has to be joined with the cache with all credit card transactions. The cache is configured in the EPN as shown below: <wlevs:caching-system id="CohCacheSystem" provider="coherence"/> <wlevs:cache id="CCTransactionsCache" value-type="CCTransactionEvent" key-properties="cardID, transactionTime" caching-system="CohCacheSystem"> </wlevs:cache> Application Output The output that must be produced by the application is a fraud warning event. This event is configured in the spring file as shown below. Source for cardHistory property can be seen here. <wlevs:event-type type-name="FraudWarningEvent"> <wlevs:properties type="tuple"> <wlevs:property name="cardID" type="CHAR"/> <wlevs:property name="transactionTime" type="BIGINT"/> <wlevs:property name="transactionAmount" type="DOUBLE"/> <wlevs:property name="cardHistory" type="OBJECT"/> </wlevs:properties </wlevs:event-type> Cache Data Aggregation using Java Cartridge In the output warning event, cardHistory property contains data from the cache aggregated over the past 30 days. To get this information, we use a java cartridge method. This method uses Coherence’s query API on credit card transactions cache to get the required information. Therefore, the java cartridge method requires a reference to the cache. This may be set up by configuring it in the spring context file as shown below: <bean class="com.oracle.cep.ccfraud.CCTransactionsAggregator"> <property name="cache" ref="CCTransactionsCache"/> </bean> This is used by the java class to set a static property: public void setCache(Map cache) { s_cache = (NamedCache) cache; } The code snippet below shows how the total of all the transaction amounts in the past 30 days is computed. Rest of the information required by CardHistory object is calculated in a similar manner. Complete source of this class can be found here. To find out more information about using Coherence's API to query a cache, please refer Coherence Developer’s Guide. public static CreditHistoryData(String cardID) { … Filter filter = QueryHelper.createFilter("cardID = :cardID and transactionTime :transactionTime", map); CardHistoryData history = new CardHistoryData(); Double sum = (Double) s_cache.aggregate(filter, new DoubleSum("getTransactionAmount")); history.setTotalAmount(sum); … return history; } The java cartridge method is used from CQL as seen below: select cardID, transactionTime, transactionAmount, CCTransactionsAggregator.execute(cardID) as cardHistory from inputChannel where transactionAmount1000 This produces a warning event, with history data, for every credit card transaction over $1000. That is all there is to it. The complete source for the sample application, along with the configuration files, is available here. In the sample, I use a simple java bean to load the cache with initial transaction history data. An input adapter is used to create and send transaction events for the input stream.

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  • The clock hands of the buffer cache

    - by Tony Davis
    Over a leisurely beer at our local pub, the Waggon and Horses, Phil Factor was holding forth on the esoteric, but strangely poetic, language of SQL Server internals, riddled as it is with 'sleeping threads', 'stolen pages', and 'memory sweeps'. Generally, I remain immune to any twinge of interest in the bowels of SQL Server, reasoning that there are certain things that I don't and shouldn't need to know about SQL Server in order to use it successfully. Suddenly, however, my attention was grabbed by his mention of the 'clock hands of the buffer cache'. Back at the office, I succumbed to a moment of weakness and opened up Google. He wasn't lying. SQL Server maintains various memory buffers, or caches. For example, the plan cache stores recently-used execution plans. The data cache in the buffer pool stores frequently-used pages, ensuring that they may be read from memory rather than via expensive physical disk reads. These memory stores are classic LRU (Least Recently Updated) buffers, meaning that, for example, the least frequently used pages in the data cache become candidates for eviction (after first writing the page to disk if it has changed since being read into the cache). SQL Server clearly needs some mechanism to track which pages are candidates for being cleared out of a given cache, when it is getting too large, and it is this mechanism that is somewhat more labyrinthine than I previously imagined. Each page that is loaded into the cache has a counter, a miniature "wristwatch", which records how recently it was last used. This wristwatch gets reset to "present time", each time a page gets updated and then as the page 'ages' it clicks down towards zero, at which point the page can be removed from the cache. But what is SQL Server is suffering memory pressure and urgently needs to free up more space than is represented by zero-counter pages (or plans etc.)? This is where our 'clock hands' come in. Each cache has associated with it a "memory clock". Like most conventional clocks, it has two hands; one "external" clock hand, and one "internal". Slava Oks is very particular in stressing that these names have "nothing to do with the equivalent types of memory pressure". He's right, but the names do, in that peculiar Microsoft tradition, seem designed to confuse. The hands do relate to memory pressure; the cache "eviction policy" is determined by both global and local memory pressures on SQL Server. The "external" clock hand responds to global memory pressure, in other words pressure on SQL Server to reduce the size of its memory caches as a whole. Global memory pressure – which just to confuse things further seems sometimes to be referred to as physical memory pressure – can be either external (from the OS) or internal (from the process itself, e.g. due to limited virtual address space). The internal clock hand responds to local memory pressure, in other words the need to reduce the size of a single, specific cache. So, for example, if a particular cache, such as the plan cache, reaches a defined "pressure limit" the internal clock hand will start to turn and a memory sweep will be performed on that cache in order to remove plans from the memory store. During each sweep of the hands, the usage counter on the cache entry is reduced in value, effectively moving its "last used" time to further in the past (in effect, setting back the wrist watch on the page a couple of hours) and increasing the likelihood that it can be aged out of the cache. There is even a special Dynamic Management View, sys.dm_os_memory_cache_clock_hands, which allows you to interrogate the passage of the clock hands. Frequently turning hands equates to excessive memory pressure, which will lead to performance problems. Two hours later, I emerged from this rather frightening journey into the heart of SQL Server memory management, fascinated but still unsure if I'd learned anything that I'd put to any practical use. However, I certainly began to agree that there is something almost Tolkeinian in the language of the deep recesses of SQL Server. Cheers, Tony.

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  • Disable linux read and write file cache on partition

    - by complistic
    How do i disable the linux file cache on a xfs partition (both read an write). We have a xfs partition over a hardware RAID that stores our RAW HD Video. Most of the shoots are 50-300gb each so the linux cache has a hit-rate of 0.001%. I have tryed the sync option but it still fills up the cache when copinging the files. ( about 30x over per shoot :P ) /etc/fstab: /dev/sdb1 /video xfs sync,noatime,nodiratime,logbufs=8 0 1 Im running debian lenny if it helps.

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  • Error headers: ap_headers_output_filter() after putting cache header in htaccess file

    - by Brad
    Receiving error: [debug] mod_headers.c(663): headers: ap_headers_output_filter() after I included this within the htaccess file: # 6 DAYS <FilesMatch "\.(ico|pdf|flv|jpg|jpeg|png|gif|js|css|swf)$"> Header set Cache-Control "max-age=518400, public" </FilesMatch> # 2 DAYS <FilesMatch "\.(xml|txt)$"> Header set Cache-Control "max-age=172800, public, must-revalidate" </FilesMatch> # 2 HOURS <FilesMatch "\.(html|htm)$"> Header set Cache-Control "max-age=7200, must-revalidate" </FilesMatch> Any help is appreciated as to what I could do to fix this?

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  • Nginx proxy cache (proxy_pass $request_uri;)

    - by imastar
    I need to create proxy web using nginx. If I access http://myweb.com/http://www.target.com/ the proxy_pass should be http://www.target.com/ Here is my configuration: location / { proxy_pass $request_uri; proxy_cache_methods GET; proxy_set_header Referer "$request_uri"; proxy_redirect off; proxy_set_header X-Real-IP $remote_addr; proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; proxy_ignore_headers Cache-Control; proxy_hide_header Pragma; proxy_hide_header Set-Cookie; proxy_set_header Cache-Control Public; proxy_cache cache; proxy_cache_valid 200 10h; proxy_cache_valid 301 302 1h; proxy_cache_valid any 1h; } Here is the log error 2013/02/05 12:58:51 [error] 2118#0: *8 invalid URL prefix in "/http://www.target.com/", client: 108.59.8.83, server: myweb.com, request: "HEAD /http://www.target.com/ HTTP/1.1", host: "myweb.com"

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  • Error headers: ap_headers_output_filter() after putting cache header in htaccess file

    - by Brad
    Receiving error: [debug] mod_headers.c(663): headers: ap_headers_output_filter() after I included this within the htaccess file: # 6 DAYS <FilesMatch "\.(ico|pdf|flv|jpg|jpeg|png|gif|js|css|swf)$"> Header set Cache-Control "max-age=518400, public" </FilesMatch> # 2 DAYS <FilesMatch "\.(xml|txt)$"> Header set Cache-Control "max-age=172800, public, must-revalidate" </FilesMatch> # 2 HOURS <FilesMatch "\.(html|htm)$"> Header set Cache-Control "max-age=7200, must-revalidate" </FilesMatch> Any help is appreciated as to what I could do to fix this?

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  • ISA caching with no cache-related info in response header

    - by Mike M. Lin
    From the documentation, I can't figure out what criteria an ISA server uses to figure out if a cached file is valid when no cache-related info is in the response header. Let's say I got this header in my response on Thu, 13 Jan 2011 18:43:35 GMT: HTTP/1.1 200 OK Date: Thu, 13 Jan 2011 18:43:35 GMT Server: Apache/2.2.3 (Red Hat) Content-Language: en X-Powered-By: Servlet/2.5 JSP/2.1 Keep-Alive: timeout=15 Connection: Keep-Alive Transfer-Encoding: chunked Content-Type: text/html; charset=ISO-8859-1 There's no cache directive, no last-modified field, no expires field. How will the ISA server decide for how long to cache this response?

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  • Safari on Mac OS X lasts beyond Empty Cache

    - by Mitch
    So, I broke a website with some server changes oops. I roll back the changes I made, hit cmd-R, and oh noes, it is still broken. But I relax thinking, there must be something held in safari's cache so I press the handy 'Empty Cache' button. Hit cmd-R for refresh it is still broken. I'm really worried that I've done it and broken something bigtime. But first decide to check on a hand win xp computer, and voila it works. So the question is how do you "really" clear the cache w/o restart safari, I have many browser windows open a restart every time I make a server side change will ruin me. Any suggestions? Thanks!

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  • How to find video in Firefox cache?

    - by Alegro
    I'm trying to find youtube video (just watched) in Firefox cache folder, but I cant find the folder. win xp sp3 Firefox 16.1 I tried C:\Documents and Settings\eDIN\Local Settings\Application Data\Mozilla\Firefox\Profiles\xp44aixq.default\Cache Also C:\Documents and Settings\eDIN\Local Settings\Application Data\Mozilla\Firefox\Profiles\49mvq84u.default\Cache In this folder I found the png thumbnail of visited youtube page C:\Documents and Settings\eDIN\Local Settings\Application Data\Mozilla\Firefox\Profiles\49mvq84u.default\thumbnails But, there is no video file. I also searched all files and folders arround (Default user, All users...etc). There is only one win user.

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  • Do Chrome and Firefox share a browser cache?

    - by Davy8
    So I was having a problem with some stuff on SO not working that was similar to this post on Meta which recommended clearing the browser cache. Now it wasn't working in both Chrome and Firefox and I had never logged in to SO on FF before today so FF couldn't have cached the file itself. Tried hitting refresh multiple times and even tried Ctrl-F5 with no luck. I cleared the browser cache in Chrome only, and after that it started working on both Chrome and FF. How could clearing the cache of one browser affect the other?

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  • windows cache not working as it should?

    - by piotrektt
    I run windows 2012 server with data center. The setup is with 60GB of RAM. I have one file shared on VHD and when I copy this file locally the RAM cache is all used up but when multiple computers connect to the share it the cache is not used. The network is 8Gb. The whole network is around 200 computers that need to read that one file but on this setup only 10 connection kills the server. Is there any way to check what is going on? What other solution can I use to manage cache in windows?

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