Maxim, thanks! В Ср, 14/08/2019 в 18:26 +0300, Maxim Muzafarov пишет: > Nikolay, > > In my message above I've described only internal local BackupManager > for the rebalance needs, but for the backup feature of the whole > Ignite cluster I also have some thoughts. I'll give you a detailed > answer in an appropriate discussion topic [1] a bit later. > > [1] > http://apache-ignite-developers.2346864.n4.nabble.com/DISCUSSION-Hot-cache-backup-td41034.html > > On Wed, 14 Aug 2019 at 16:40, Nikolay Izhikov <nizhi...@apache.org> wrote: > > > > Hello, Maxim. > > > > I think backup is a great feature for Ignite. > > Let's have it! > > > > Few notes for it: > > > > 1. Backup directory should be taken from node configuration. > > > > 2. Backup should be stored on local node only. > > Ignite admin can write sh script to move all backuped partitions to one > > storage by himself. > > > > 3. Ignite should provide CLI tools to start backup/restore procedure. > > > > Questions: > > > > 1. How each backup would be identified? > > 2. Do you plan to implement backup of cache or cache group? > > 3. How restore process would be implemented from user point of view? > > Can we interact with cache during restore? > > > > В Ср, 14/08/2019 в 16:13 +0300, Maxim Muzafarov пишет: > > > Igniters, > > > > > > > > > Since the file transmission between Ignite nodes [2] have been merged > > > to the master branch (it is the first mandatory part of file-based > > > rebalance procedure) I'd like to focus on the next step of the current > > > IEP-28 - the process of creating snapshots of cache group partitions. > > > > > > Previously, we've discussed a creation of cache group backups [3] for > > > the whole cluster. I'd like to take into account the GridGain > > > experience with such snapshot creation and, at first, focuses on the > > > local internal IgniteBackupManager which will be used for such purpose > > > [4] [1]. > > > > > > Changes are almost ready. I need some additional time to finalize the > > > PR with backup creation. > > > > > > > > > API (create local partitions copy) > > > > > > /** > > > * @param name Unique backup name. > > > * @param parts Collection of pairs group and appropratate cache > > > partition to be backuped. > > > * @param dir Local backup directory. > > > */ > > > public IgniteInternalFuture<?> backup( > > > String name, > > > Map<Integer, Set<Integer>> parts, > > > File dir, > > > ExecutorService backupSvc (this can be completely optional) > > > ); > > > > > > > > > API (backup partitoins over the network) > > > > > > /** > > > * @param name Unique backup name. > > > * @param parts Collection of pairs group and appropratate cache > > > partition to be backuped. > > > * @param snd File sender provider. > > > */ > > > public IgniteInternalFuture<?> backup( > > > String name, > > > Map<Integer, Set<Integer>> parts, > > > Supplier<GridIoManager.TransmissionSender> snd > > > ); > > > > > > [1] > > > https://cwiki.apache.org/confluence/display/IGNITE/IEP-28%3A+Cluster+peer-2-peer+balancing#IEP-28:Clusterpeer-2-peerbalancing-Copypartitiononthefly > > > [2] https://issues.apache.org/jira/browse/IGNITE-10619 > > > [3] > > > http://apache-ignite-developers.2346864.n4.nabble.com/DISCUSSION-Hot-cache-backup-td41034.html > > > [4] https://issues.apache.org/jira/browse/IGNITE-11073 > > > > > > On Wed, 12 Dec 2018 at 11:15, Vladimir Ozerov <voze...@gridgain.com> > > > wrote: > > > > > > > > Maxim, > > > > > > > > Thank you for excellent analysis! From profiling data I see the > > > > following: > > > > 1) Almost no parallelism - one rebalance thread is used (default), two > > > > responses are sent per a single demand request (default) > > > > 2) All system resources are underutilized - CPU, disk, network > > > > 3) Huge hotspot ion free lists > > > > > > > > In general I would recommend to consider the following points during > > > > further rebalance optimization: > > > > 1) Start with the fact that rebalance always causes system degradation > > > > due to additional hardware resources required. Different deployments > > > > may require different degradation modes. Sometimes "soft" mode is > > > > preferable - long rebalance with low system overhead. This is what we > > > > see now. Sometimes the opposite - as short rebalance as possible at the > > > > cost of severe degradation in operations. Sometimes - something in the > > > > middle. Every optimization we made should have clear explanation on how > > > > system degrades. > > > > 2) We need to investigate the hotspot on free lists. Looks like this is > > > > the main limiting factor for now. Alex, do you have any ideas what is > > > > this? Is it possible to bypass freelists completely during rebalance at > > > > the cost of higher data fragmentation during concurrent updates? > > > > 3) We need to investigate streaming rebalance mode, when supplier > > > > constantly streams data to demander similarly to our data streamer. It > > > > should be fairly easy to implement, applicable for all modes and may > > > > speedup rebalance up to 5-10 times. Great thing about this approach is > > > > that it will allow users to choose between system stress level and > > > > rebalance throughput easily. > > > > 4) File transfer rebalance: we need to have clear design of failure and > > > > concurrency cases and degradation modes. Several questions to answer: > > > > 4.1) What would happen if another rebalance starts when previous is not > > > > finished yet? > > > > 4.2) What would happen if supplier or demander fails in the middle? > > > > What kind of cleanup would be required > > > > 4.3) Degradation: what kind of problems should users expect due to > > > > massive disk and network load during file transfer and due to data > > > > merging on demander side? > > > > 4.4) Degradation: how secondary indexes would be rebuilt on demander > > > > side? Note that until indexes are ready node is not operational and > > > > cannot become partition owner, and index rebuild is essentially full > > > > data rescan with potentially the same issues with slow updates of > > > > persistent data structures we have now. > > > > > > > > Vladimir. > > > > > > > > On Fri, Dec 7, 2018 at 3:32 PM Maxim Muzafarov <maxmu...@gmail.com> > > > > wrote: > > > > > > > > > > Vladimir, > > > > > > > > > > > > > > > Let me propose to consider the whole this rebalance process as having > > > > > three strategies: > > > > > - The classical message-based approach, preferable to use for > > > > > in-memory caches; > > > > > - Historical rebalance based on WAL, used for rebalancing persisted > > > > > caches deltas; > > > > > - (new) File-based rebalance (current IEP-28), used for relocation of > > > > > full cache partitions. > > > > > > > > > > > > > > > First of all, I want to show you that for the full cache relocation > > > > > file-based rebalancing strategy from my point has a set of advantages > > > > > prior to the message-based approach. Let's also assume that the time > > > > > spent on WAL logging during the rebalance procedure is already > > > > > optimized (we are not taking it into account at all). > > > > > > > > > > According to preliminary measurements [8] and the message above we > > > > > spend more than 65% of rebalancing time on creating K-V cache pair for > > > > > preloading entries and supporting internal data structures. It is true > > > > > as for in-memory cluster configuration and for a cluster with enabled > > > > > persistence. It is also true, that these data structures can be used > > > > > more efficiently by implementing batch entry processing for them. And > > > > > it should be done (a ticket for it is already created [3]). > > > > > > > > > > Let's have a look closer to the simple example. > > > > > > > > > > I've collected some information about a cache on my stress-testing > > > > > cluster: > > > > > partitions (total): 65534 > > > > > single partition size: 437 MB > > > > > rebalance batch: 512 Kb > > > > > batches per partition: 874 > > > > > partitions per node: 606 > > > > > batches per node: 529644 > > > > > > > > > > Let's assume that we've already implemented batched entry processing > > > > > and we perform bulk operations over internal data structures. > > > > > Regarding these assumptions, we still need to process 874 batches per > > > > > each cache partition to transfer data. I will cost us up to 15 seconds > > > > > per each partition file, a lot of CPU cycles to maintain internal data > > > > > structures and block for a while other threads waiting for releasing > > > > > database checkpoint lock. > > > > > > > > > > Increasing the rebalance batch size is not efficient here because we > > > > > are starting to hold the database lock for too long. It will lead to > > > > > thread starvation and will only slow down the whole rebalance speed. > > > > > Exactly the same as increasing batch size, making the rebalance thread > > > > > pool bigger can lead to the cluster performance drop for almost the > > > > > same reasons. > > > > > > > > > > I think the file-based rebalance can provide us (prior to the batch > > > > > processing) for huge caches: > > > > > - a fair non-blocking approach in each part of the rebalancing > > > > > procedure; > > > > > - reduce the number of locks being acquired (the other threads can > > > > > make bigger progress); > > > > > - a zero-copy transmission on supplier saves CPU cycles and memory > > > > > bandwidth; > > > > > - as a result, the transferable batch size increased up to the whole > > > > > partition file size; > > > > > > > > > > SUMMARY TO DO > > > > > > > > > > The plan to do and other ideas (without risks evaluation): > > > > > > > > > > Message-based approach. > > > > > Optimization to do by priority [3] [2] and may be [9]. > > > > > > > > > > Historical rebalance based on WAL. > > > > > Suppose, nothing to do here as Sergey already working on the issue [1] > > > > > with turning off WAL. > > > > > > > > > > (new) Full cache data relocation. > > > > > Prototyping current IEP-28. > > > > > > > > > > I think another approach can be also implemented. > > > > > During the rebalance procedure we can write entries to data pages > > > > > directly skipping free lists, PK index and secondary index. Once the > > > > > partition preloading is finished, we will rebuild free list and all > > > > > indexes. > > > > > Will it work for us? > > > > > > > > > > ANSWERS > > > > > > > > > > > 1) Is it correct that supplier sends only one message for every > > > > > > demand > > > > > > message? If yes, then streaming should improve network utilization > > > > > > a lot. > > > > > > > > > > I think we already have such ability for the Apache Ignite (not > > > > > exactly streaming). The CacheConfiguration#rebalanceBatchesPrefetchCnt > > > > > can be used here to reduce the system delay between send\receive > > > > > message process. The default value is more than enough for most of the > > > > > cases. The testing results showed only 7 seconds (0.32%) delay during > > > > > the 40 min cache rebalance procedure. So, each supply message is ready > > > > > to be sent when the next demand message arrives. > > > > > > > > > > > > > > > > 2) Is it correct that for user caches we process supply messages in > > > > > > a > > > > > > system pool? Did we consider moving it to striped pool? Because if > > > > > > all > > > > > > operations on a single partition is ordered, we may apply a number > > > > > > of > > > > > > critical optimizations - bypassing page cache and checkpointer for > > > > > > new > > > > > > entries, batched index updates, batched free list updates, etc. > > > > > > > > > > I think the rebalance procedure should not cause a thousand messages > > > > > per second, so we don't need to move the rebalance procedure to the > > > > > stripped pool. We should have a limited stable load for rebalancing > > > > > procedure on the cluster. As for the second part, are you talking > > > > > about thread per partition model? If yes, we have tickets for it [4], > > > > > [5], [6]. > > > > > > > > > > > 3) Seems that WAL should no longer be a problem for us [1]. What > > > > > > are exact > > > > > > conditions when it could be disabled on supplier side? > > > > > > > > > > Do you mean the demander side? Why we should try to disable it on the > > > > > supplier node? I do not take it into account at all because it can be > > > > > easily done (suppose issue [1] is about it). But it doesn't help us > > > > > much for the full cache relocations. > > > > > > > > > > > 4) Most important - have we tried to profile plain single-threaded > > > > > > rebalance without concurrent write load? We need to have clear > > > > > > understanding on where time is spent - supplier/demander, > > > > > > cpu/network/disk, > > > > > > etc. Some Java tracing code should help. > > > > > > > > > > I've updated some information about profiling results on the > > > > > confluence page [8]. If you will find that I've missed something or > > > > > information is unclear, please, let me know and I will fix it. > > > > > > > > > > > And one question regarding proposed implementation - how are we > > > > > > going to > > > > > > handle secondary indexes? > > > > > > > > > > Thank you for pointing this out. Actually, the current IEP page > > > > > doesn't cover this case. I think we can schedule rebuild indexes after > > > > > all partition files would be transferred. This approach was also > > > > > mentioned at [2] issue. > > > > > Will it be the correct? > > > > > > > > > > > > > > > [1] https://issues.apache.org/jira/browse/IGNITE-10505 > > > > > [2] https://issues.apache.org/jira/browse/IGNITE-7934 > > > > > [3] https://issues.apache.org/jira/browse/IGNITE-7935 > > > > > > > > > > [4] https://issues.apache.org/jira/browse/IGNITE-4682 > > > > > [5] https://issues.apache.org/jira/browse/IGNITE-4506 > > > > > [6] https://issues.apache.org/jira/browse/IGNITE-4680 > > > > > > > > > > [7] https://issues.apache.org/jira/browse/IGNITE-7027 > > > > > [8] > > > > > https://cwiki.apache.org/confluence/display/IGNITE/Rebalance+peer-2-peer > > > > > [9] https://issues.apache.org/jira/browse/IGNITE-9520 > > > > > On Wed, 28 Nov 2018 at 23:00, Vladimir Ozerov <voze...@gridgain.com> > > > > > wrote: > > > > > > > > > > > > Maxim, > > > > > > > > > > > > Regarding MVCC - this is essentially a copy-on-write approach. New > > > > > > entry is > > > > > > created on every update. They are cleaned asynchronously by > > > > > > dedicated > > > > > > threads (aka "vacuum"). > > > > > > > > > > > > I looked at the document you mentioned, thank you for pointing to > > > > > > it. But > > > > > > it doesn't answer all questions around existing design, and what I > > > > > > am > > > > > > trying to do is to get how deep do we understand current problems. > > > > > > It is > > > > > > very true that various subsystems, such as buffer managers, WALs, > > > > > > supporting sctructures, etc. incur very serious overhead. And when > > > > > > it comes > > > > > > to heavy operations implementors typically seek for a way to bypass > > > > > > as much > > > > > > components as possible, taking in count that different shortcuts > > > > > > lead to > > > > > > different types of side effects. And IMO our very important goal > > > > > > for now is > > > > > > to create space of possible improvements, and estimate their costs, > > > > > > risks > > > > > > and applicability for product's configuration space. > > > > > > > > > > > > Let me claridy several questions about current rebalance > > > > > > implementation, as > > > > > > I am not a big expert here. > > > > > > 1) Is it correct that supplier sends only one message for every > > > > > > demand > > > > > > message? If yes, then streaming should improve network utilization > > > > > > a lot. > > > > > > 2) Is it correct that for user caches we process supply messages in > > > > > > a > > > > > > system pool? Did we consider moving it to striped pool? Because if > > > > > > all > > > > > > operations on a single partition is ordered, we may apply a number > > > > > > of > > > > > > critical optimizations - bypassing page cache and checkpointer for > > > > > > new > > > > > > entries, batched index updates, batched free list updates, etc. > > > > > > 3) Seems that WAL should no longer be a problem for us [1]. What > > > > > > are exact > > > > > > conditions when it could be disabled on supplier side? > > > > > > 4) Most important - have we tried to profile plain single-threaded > > > > > > rebalance without concurrent write load? We need to have clear > > > > > > understanding on where time is spent - supplier/demander, > > > > > > cpu/network/disk, > > > > > > etc. Some Java tracing code should help. > > > > > > > > > > > > And one question regarding proposed implementation - how are we > > > > > > going to > > > > > > handle secondary indexes? > > > > > > > > > > > > [1] https://issues.apache.org/jira/browse/IGNITE-8017 > > > > > > > > > > > > > > > > > > On Wed, Nov 28, 2018 at 6:43 PM Maxim Muzafarov > > > > > > <maxmu...@gmail.com> wrote: > > > > > > > > > > > > > Eduard, > > > > > > > > > > > > > > Thank you very much for the discussion! > > > > > > > > > > > > > > Your algorithm looks much better for me too and easier to > > > > > > > implement. > > > > > > > I'll update appropriate process points on IEP page of the proposed > > > > > > > rebalance procedure. > > > > > > > On Tue, 27 Nov 2018 at 18:52, Eduard Shangareev > > > > > > > <eduard.shangar...@gmail.com> wrote: > > > > > > > > > > > > > > > > So, after some discussion, I could describe another approach on > > > > > > > > how to > > > > > > > > build consistent partition on the fly. > > > > > > > > > > > > > > > > 1. We make a checkpoint, fix the size of the partition in > > > > > > > > OffheapManager. > > > > > > > > 2. After checkpoint finish, we start sending partition file > > > > > > > > (without any > > > > > > > > lock) to the receiver from 0 to fixed size. > > > > > > > > 3. Next checkpoints if they detect that they would override > > > > > > > > some pages of > > > > > > > > transferring file should write the previous state of a page to a > > > > > > > > > > > > > > dedicated > > > > > > > > file. > > > > > > > > So, we would have a list of pages written 1 by 1, page id is > > > > > > > > written in > > > > > > > > > > > > > > the > > > > > > > > page itself so we could determine page index. Let's name it log. > > > > > > > > 4. When transfer finished checkpointer would stop updating > > > > > > > > log-file. Now > > > > > > > > > > > > > > we > > > > > > > > are ready to send it to the receiver. > > > > > > > > 5. On receiver side we start merging the dirty partition file > > > > > > > > with log > > > > > > > > (updating it with pages from log-file). > > > > > > > > > > > > > > > > So, an advantage of this method: > > > > > > > > - checkpoint-thread work couldn't increase more than twice; > > > > > > > > - checkpoint-threads shouldn't wait for anything; > > > > > > > > - in best case, we receive partition without any extra effort. > > > > > > > > > > > > > > > > > > > > > > > > On Mon, Nov 26, 2018 at 8:54 PM Eduard Shangareev < > > > > > > > > eduard.shangar...@gmail.com> wrote: > > > > > > > > > > > > > > > > > Maxim, > > > > > > > > > > > > > > > > > > I have looked through your algorithm of reading partition > > > > > > > > > consistently. > > > > > > > > > And I have some questions/comments. > > > > > > > > > > > > > > > > > > 1. The algorithm requires heavy synchronization between > > > > > > > > > > > > > > checkpoint-thread > > > > > > > > > and new-approach-rebalance-threads, > > > > > > > > > because you need strong guarantees to not start writing or > > > > > > > > > reading to > > > > > > > > > chunk which was updated or started reading by the counterpart. > > > > > > > > > > > > > > > > > > 2. Also, if we have started transferring this chunk in > > > > > > > > > original > > > > > > > > > > > > > > partition > > > > > > > > > couldn't be updated by checkpoint-threads. They should wait > > > > > > > > > for > > > > > > > > > > > > > > transfer > > > > > > > > > finishing. > > > > > > > > > > > > > > > > > > 3. If sending is slow and partition is updated then in worst > > > > > > > > > case > > > > > > > > > checkpoint-threads would create the whole copy of the > > > > > > > > > partition. > > > > > > > > > > > > > > > > > > So, what we have: > > > > > > > > > -on every page write checkpoint-thread should synchronize with > > > > > > > > > new-approach-rebalance-threads; > > > > > > > > > -checkpoint-thread should do extra-work, sometimes this could > > > > > > > > > be as > > > > > > > > > > > > > > huge > > > > > > > > > as copying the whole partition. > > > > > > > > > > > > > > > > > > > > > > > > > > > On Fri, Nov 23, 2018 at 2:55 PM Ilya Kasnacheev < > > > > > > > > > > > > > > ilya.kasnach...@gmail.com> > > > > > > > > > wrote: > > > > > > > > > > > > > > > > > > > Hello! > > > > > > > > > > > > > > > > > > > > This proposal will also happily break my > > > > > > > > > > compression-with-dictionary > > > > > > > > > > > > > > patch > > > > > > > > > > since it relies currently on only having local dictionaries. > > > > > > > > > > > > > > > > > > > > However, when you have compressed data, maybe speed boost > > > > > > > > > > is even > > > > > > > > > > > > > > greater > > > > > > > > > > with your approach. > > > > > > > > > > > > > > > > > > > > Regards, > > > > > > > > > > -- > > > > > > > > > > Ilya Kasnacheev > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > пт, 23 нояб. 2018 г. в 13:08, Maxim Muzafarov > > > > > > > > > > <maxmu...@gmail.com>: > > > > > > > > > > > > > > > > > > > > > Igniters, > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > I'd like to take the next step of increasing the Apache > > > > > > > > > > > Ignite with > > > > > > > > > > > enabled persistence rebalance speed. Currently, the > > > > > > > > > > > rebalancing > > > > > > > > > > > procedure doesn't utilize the network and storage device > > > > > > > > > > > throughout > > > > > > > > > > > > > > to > > > > > > > > > > > its full extent even with enough meaningful values of > > > > > > > > > > > rebalanceThreadPoolSize property. As part of the previous > > > > > > > > > > > discussion > > > > > > > > > > > `How to make rebalance faster` [1] and IEP-16 [2] Ilya > > > > > > > > > > > proposed an > > > > > > > > > > > idea [3] of transferring cache partition files over the > > > > > > > > > > > network. > > > > > > > > > > > From my point, the case to which this type of rebalancing > > > > > > > > > > > procedure > > > > > > > > > > > can bring the most benefit – is adding a completely new > > > > > > > > > > > node or set > > > > > > > > > > > > > > of > > > > > > > > > > > new nodes to the cluster. Such a scenario implies fully > > > > > > > > > > > relocation > > > > > > > > > > > > > > of > > > > > > > > > > > cache partition files to the new node. To roughly > > > > > > > > > > > estimate the > > > > > > > > > > > superiority of partition file transmitting over the > > > > > > > > > > > network the > > > > > > > > > > > > > > native > > > > > > > > > > > Linux scp\rsync commands can be used. My test environment > > > > > > > > > > > showed the > > > > > > > > > > > result of the new approach as 270 MB/s vs the current 40 > > > > > > > > > > > MB/s > > > > > > > > > > > single-threaded rebalance speed. > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > I've prepared the design document IEP-28 [4] and > > > > > > > > > > > accumulated all the > > > > > > > > > > > process details of a new rebalance approach on that page. > > > > > > > > > > > Below you > > > > > > > > > > > can find the most significant details of the new > > > > > > > > > > > rebalance procedure > > > > > > > > > > > and components of the Apache Ignite which are proposed to > > > > > > > > > > > change. > > > > > > > > > > > > > > > > > > > > > > Any feedback is very appreciated. > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > *PROCESS OVERVIEW* > > > > > > > > > > > > > > > > > > > > > > The whole process is described in terms of rebalancing > > > > > > > > > > > single cache > > > > > > > > > > > group and partition files would be rebalanced one-by-one: > > > > > > > > > > > > > > > > > > > > > > 1. The demander node sends the > > > > > > > > > > > GridDhtPartitionDemandMessage to the > > > > > > > > > > > supplier node; > > > > > > > > > > > 2. When the supplier node receives > > > > > > > > > > > GridDhtPartitionDemandMessage and > > > > > > > > > > > starts the new checkpoint process; > > > > > > > > > > > 3. The supplier node creates empty the temporary cache > > > > > > > > > > > partition > > > > > > > > > > > > > > file > > > > > > > > > > > with .tmp postfix in the same cache persistence directory; > > > > > > > > > > > 4. The supplier node splits the whole cache partition > > > > > > > > > > > file into > > > > > > > > > > > virtual chunks of predefined size (multiply to the > > > > > > > > > > > PageMemory size); > > > > > > > > > > > 4.1. If the concurrent checkpoint thread determines the > > > > > > > > > > > appropriate > > > > > > > > > > > cache partition file chunk and tries to flush dirty page > > > > > > > > > > > to the > > > > > > > > > > > > > > cache > > > > > > > > > > > partition file > > > > > > > > > > > 4.1.1. If rebalance chunk already transferred > > > > > > > > > > > 4.1.1.1. Flush the dirty page to the file; > > > > > > > > > > > 4.1.2. If rebalance chunk not transferred > > > > > > > > > > > 4.1.2.1. Write this chunk to the temporary cache > > > > > > > > > > > partition file; > > > > > > > > > > > 4.1.2.2. Flush the dirty page to the file; > > > > > > > > > > > 4.2. The node starts sending to the demander node each > > > > > > > > > > > cache > > > > > > > > > > > > > > partition > > > > > > > > > > > file chunk one by one using FileChannel#transferTo > > > > > > > > > > > 4.2.1. If the current chunk was modified by checkpoint > > > > > > > > > > > thread – read > > > > > > > > > > > it from the temporary cache partition file; > > > > > > > > > > > 4.2.2. If the current chunk is not touched – read it from > > > > > > > > > > > the > > > > > > > > > > > > > > original > > > > > > > > > > > cache partition file; > > > > > > > > > > > 5. The demander node starts to listen to new pipe incoming > > > > > > > > > > > > > > connections > > > > > > > > > > > from the supplier node on TcpCommunicationSpi; > > > > > > > > > > > 6. The demander node creates the temporary cache > > > > > > > > > > > partition file with > > > > > > > > > > > .tmp postfix in the same cache persistence directory; > > > > > > > > > > > 7. The demander node receives each cache partition file > > > > > > > > > > > chunk one > > > > > > > > > > > > > > by one > > > > > > > > > > > 7.1. The node checks CRC for each PageMemory in the > > > > > > > > > > > downloaded > > > > > > > > > > > > > > chunk; > > > > > > > > > > > 7.2. The node flushes the downloaded chunk at the > > > > > > > > > > > appropriate cache > > > > > > > > > > > partition file position; > > > > > > > > > > > 8. When the demander node receives the whole cache > > > > > > > > > > > partition file > > > > > > > > > > > 8.1. The node initializes received .tmp file as its > > > > > > > > > > > appropriate > > > > > > > > > > > > > > cache > > > > > > > > > > > partition file; > > > > > > > > > > > 8.2. Thread-per-partition begins to apply for data > > > > > > > > > > > entries from the > > > > > > > > > > > beginning of WAL-temporary storage; > > > > > > > > > > > 8.3. All async operations corresponding to this partition > > > > > > > > > > > file still > > > > > > > > > > > write to the end of temporary WAL; > > > > > > > > > > > 8.4. At the moment of WAL-temporary storage is ready to > > > > > > > > > > > be empty > > > > > > > > > > > 8.4.1. Start the first checkpoint; > > > > > > > > > > > 8.4.2. Wait for the first checkpoint ends and own the > > > > > > > > > > > cache > > > > > > > > > > > > > > partition; > > > > > > > > > > > 8.4.3. All operations now are switched to the partition > > > > > > > > > > > file instead > > > > > > > > > > > of writing to the temporary WAL; > > > > > > > > > > > 8.4.4. Schedule the temporary WAL storage deletion; > > > > > > > > > > > 9. The supplier node deletes the temporary cache > > > > > > > > > > > partition file; > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > *COMPONENTS TO CHANGE* > > > > > > > > > > > > > > > > > > > > > > CommunicationSpi > > > > > > > > > > > > > > > > > > > > > > To benefit from zero copy we must delegate the file > > > > > > > > > > > transferring to > > > > > > > > > > > FileChannel#transferTo(long, long, > > > > > > > > > > > java.nio.channels.WritableByteChannel) because the fast > > > > > > > > > > > path of > > > > > > > > > > > transferTo method is only executed if the destination > > > > > > > > > > > buffer > > > > > > > > > > > > > > inherits > > > > > > > > > > > from an internal JDK class. > > > > > > > > > > > > > > > > > > > > > > Preloader > > > > > > > > > > > > > > > > > > > > > > A new implementation of cache entries preloader assume to > > > > > > > > > > > be done. > > > > > > > > > > > > > > The > > > > > > > > > > > new implementation must send and receive cache partition > > > > > > > > > > > files over > > > > > > > > > > > the CommunicationSpi channels by chunks of data with > > > > > > > > > > > validation > > > > > > > > > > > received items. The new layer over the cache partition > > > > > > > > > > > file must > > > > > > > > > > > support direct using of FileChannel#transferTo method > > > > > > > > > > > over the > > > > > > > > > > > CommunicationSpi pipe connection. The connection > > > > > > > > > > > bandwidth of the > > > > > > > > > > > cache partition file transfer must have the ability to be > > > > > > > > > > > limited at > > > > > > > > > > > runtime. > > > > > > > > > > > > > > > > > > > > > > Checkpointer > > > > > > > > > > > > > > > > > > > > > > When the supplier node receives the cache partition file > > > > > > > > > > > demand > > > > > > > > > > > request it will send the file over the CommunicationSpi. > > > > > > > > > > > The cache > > > > > > > > > > > partition file can be concurrently updated by checkpoint > > > > > > > > > > > thread > > > > > > > > > > > > > > during > > > > > > > > > > > its transmission. To guarantee the file consistency > > > > > > > > > > > Сheckpointer > > > > > > > > > > > > > > must > > > > > > > > > > > use copy-on-write technique and save a copy of updated > > > > > > > > > > > chunk into > > > > > > > > > > > > > > the > > > > > > > > > > > temporary file. > > > > > > > > > > > > > > > > > > > > > > (new) Catch-up temporary WAL > > > > > > > > > > > > > > > > > > > > > > While the demander node is in the partition file > > > > > > > > > > > transmission state > > > > > > > > > > > > > > it > > > > > > > > > > > must save all cache entries corresponding to the moving > > > > > > > > > > > partition > > > > > > > > > > > > > > into > > > > > > > > > > > a new temporary WAL storage. These entries will be > > > > > > > > > > > applied later one > > > > > > > > > > > by one on the received cache partition file. All > > > > > > > > > > > asynchronous > > > > > > > > > > > operations will be enrolled to the end of temporary WAL > > > > > > > > > > > storage > > > > > > > > > > > > > > during > > > > > > > > > > > storage reads until it becomes fully read. The file-based > > > > > > > > > > > FIFO > > > > > > > > > > > approach assumes to be used by this process. > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > *RECOVERY* > > > > > > > > > > > > > > > > > > > > > > In case of crash recovery, there is no additional actions > > > > > > > > > > > need to be > > > > > > > > > > > applied to keep the cache partition file consistency. We > > > > > > > > > > > are not > > > > > > > > > > > recovering partition with the moving state, thus the > > > > > > > > > > > single > > > > > > > > > > > > > > partition > > > > > > > > > > > file will be lost and only it. The uniqueness of it is > > > > > > > > > > > guaranteed by > > > > > > > > > > > the single-file-transmission process. The cache partition > > > > > > > > > > > file will > > > > > > > > > > > > > > be > > > > > > > > > > > fully loaded on the next rebalance procedure. > > > > > > > > > > > > > > > > > > > > > > To provide default cluster recovery guarantee we must to: > > > > > > > > > > > 1. Start the checkpoint process when the temporary WAL > > > > > > > > > > > storage > > > > > > > > > > > > > > becomes > > > > > > > > > > > empty; > > > > > > > > > > > 2. Wait for the first checkpoint ends and set owning > > > > > > > > > > > status to the > > > > > > > > > > > cache partition; > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > [1] > > > > > > > > > > > > > > > > > > > > > > > > > http://apache-ignite-developers.2346864.n4.nabble.com/Rebalancing-how-to-make-it-faster-td28457.html > > > > > > > > > > > [2] > > > > > > > > > > > > > > > > > > > > > > > > > https://cwiki.apache.org/confluence/display/IGNITE/IEP-16%3A+Optimization+of+rebalancing > > > > > > > > > > > [3] https://issues.apache.org/jira/browse/IGNITE-8020 > > > > > > > > > > > [4] > > > > > > > > > > > > > > > > > > > > > > > > > https://cwiki.apache.org/confluence/display/IGNITE/IEP-28%3A+Cluster+peer-2-peer+balancing > > > > > > > > > > >
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