Can we use the history to implement anti-affinity: for any role with this flag, use our knowledge of the cluster to ask for all nodes that aren't in use already
How to add blacklisting here? We are tracking failures and startup failures per node (not persisted), but not using this in role placement requests yet.
Slider needs to bring up instances of a given role on the machine(s) on which they last ran -it should remember after shrinking or freezing a cluster which servers were last used for a role -and use this (persisted) data to select clusters next time
It does this in the basis that the role instances prefer node-local access to data previously persisted to HDFS. This is precisely the case for Apache HBase, which can use Unix Domain Sockets to talk to the DataNode without using the TCP stack. The HBase master persists to HDFS the tables assigned to specific Region Servers, and when HBase is restarted its master tries to reassign the same tables back to Region Servers on the same machine.
For this to work in a dynamic cluster, Slider needs to bring up Region Servers on the previously used hosts, so that the HBase Master can re-assign the same tables.
Note that it does not need to care about the placement of other roles, such as the HBase masters -there anti-affinity between other instances is the key requirement.
Here are some assumptions in Slider's design
Instances of a specific role should preferably be deployed onto different servers. This enables Slider to only remember the set of server nodes onto which instances were created, rather than more complex facts such as "two Region Servers were previously running on Node #17. On restart Slider can simply request one instance of a Region Server on a specific node, leaving the other instance to be arbitrarily deployed by YARN. This strategy should help reduce the affinity in the role deployment, so increase their resilience to failure.
There is no need to make sophisticated choices on which nodes to request re-assignment -such as recording the amount of data persisted by a previous instance and prioritizing nodes based on such data. More succinctly 'the only priority needed when asking for nodes is ask for the most recently used.
Different roles are independent: it is not an issue if a role of one type (example, an Accumulo Monitor and an Accumulo Tablet Server) are on the same host. This assumption allows Slider to only worry about affinity issues within a specific role, rather than across all roles.
After a cluster has been started, the rate of change of the cluster is low: both node failures and cluster flexing happen at the rate of every few hours, rather than every few seconds. This allows Slider to avoid needing data structures and layout persistence code designed for regular and repeated changes.
Instance placement is best-effort: if the previous placement cannot be satisfied, the application will still perform adequately with role instances deployed onto new servers. More specifically, if a previous server is unavailable for hosting a role instance due to lack of capacity or availability, Slider will not decrement the number of instances to deploy: instead it will rely on YARN to locate a new node -ideally on the same rack.
If two instances of the same role do get assigned to the same server, it is not a failure condition. (This may be problematic for some roles -we may need a role-by-role policy here, so that master nodes can be anti-affine) [specifically, >1 HBase master mode will not come up on the same host]
If a role instance fails on a specific node, asking for a container on that same node for the replacement instance is a valid recovery strategy. This contains assumptions about failure modes -some randomness here may be a valid tactic, especially for roles that do not care about locality.
Tracking failure statistics of nodes may be a feature to add in future; designing the Role History datastructures to enable future collection of rolling statistics on recent failures would be a first step to this
The RoleHistory is a datastructure which models the role assignment, and can persist it to and restore it from the (shared) filesystem.
For each role, there is a list of cluster nodes which have supported this role used in the past.
This history is used when selecting a node for a role.
This history remembers when nodes were allocated. These are re-requested when thawing a cluster.
It must also remember when nodes were released -these are re-requested when returning the cluster size to a previous size during flex operations.
It has to track nodes for which Slider has an outstanding container request with YARN. This ensures that the same node is not requested more than once due to outstanding requests.
It does not retain a complete history of the role -and does not need to. All it needs to retain is the recent history for every node onto which a role instance has been deployed. Specifically, the last allocation or release operation on a node is all that needs to be persisted.
On AM startup, all nodes in the history are considered candidates, even those nodes currently marked as active -as they were from the previous instance.
On AM restart, nodes in the role history marked as active have to be considered still active -the YARN RM will have to provide the full list of which are not.
During cluster flexing, nodes marked as released -and for which there is no outstanding request - are considered candidates for requesting new instances.
When choosing a candidate node for hosting a role instance, it from the head of the time-ordered list of nodes that last ran an instance of that role
The state of the role is persisted to HDFS on changes -but not on cluster termination.
As at startup, a large number of allocations may arrive in a short period of time, the Role History may be updated very rapidly -yet as the containers are only recently activated, it is not likely that an immediately restarted Slider cluster would gain by re-requesting containers on them -their historical value is more important than their immediate past.
Accordingly, the role history may be persisted to HDFS asynchronously, with the dirty bit triggering an flushing of the state to HDFS. The datastructure will still need to be synchronized for cross thread access, but the sync operation will not be a major deadlock, compared to saving the file on every container allocation response (which will actually be the initial implementation).
There‘s no need to persist the format in a human-readable form; while protobuf might seem the approach most consistent with the rest of YARN, it’s not an easy structure to work with.
The initial implementation will use Apache Avro as the persistence format, with the data saved in JSON or compressed format.
Blacklisting: even if a node fails repeatedly, this design will still try to re-request instances on this node; there is no blacklisting. As a central blacklist for YARN has been proposed, it is hoped that this issue will be addressed centrally, without Slider having to remember which nodes are unreliable for that particular Slider cluster.
Anti-affinity: If multiple role instances are assigned to the same node, Slider has to choose on restart or flexing whether to ask for multiple nodes on that node again, or to pick other nodes. The assumed policy is “only ask for one node”
Bias towards recent nodes over most-used: re-requesting the most recent nodes, rather than those with the most history of use, may push Slider to requesting nodes that were only briefly in use -and so have on a small amount of local state, over nodes that have had long-lived instances. This is a problem that could perhaps be addressed by preserving more history of a node -maintaining some kind of moving average of node use and picking the heaviest used, or some other more-complex algorithm. This may be possible, but we'd need evidence that the problem existed before trying to address it.
The core data structure, the NodeMap is a map of every known node in the cluster, tracking how many containers are allocated to specific roles in it, and, when there are no active instances, when it was last used. This history is used to choose where to request new containers. Because of the asynchronous allocation and release of containers, the Role History also needs to track outstanding release requests --and, more critically, outstanding allocation requests. If Slider has already requested a container for a specific role on a host, then asking for another container of that role would break anti-affinity requirements. Note that not tracking outstanding requests would radically simplify some aspects of the design, especially the complexity of correlating allocation responses with the original requests -and so the actual hosts originally requested.
O(nodes * role-instances). This could be mitigated by regular cleansing of the structure. For example, at thaw time (or intermittently) all unused nodes > 2 weeks old could be dropped.O(nodes) lookups -and if the criteria of “newest” is included, will take exactly O(nodes) lookups. As an optimization, a list of recently explicitly released nodes can be maintained.startTime: long saveTime: long dirty: boolean nodemap: NodeMap roles: RoleStatus[] outstandingRequests: transient OutstandingRequestTracker availableNodes: transient List<NodeInstance>[]
This is the aggregate data structure that is persisted to/from file
clusterNodes: Map: NodeId -> NodeInstance clusterNodes(): Iterable<NodeInstance> getOrCreate(NodeId): NodeInstance
Maps a YARN NodeID record to a Slider NodeInstance structure
Every node in the cluster is modeled as an ragged array of NodeEntry instances, indexed by role index -
NodeEntry[roles] get(roleId): NodeEntry or null create(roleId): NodeEntry getNodeEntries(): NodeEntry[roles] getOrCreate(roleId): NodeEntry remove(roleId): NodeEntry
This could be implemented in a map or an indexed array; the array is more efficient but it does mandate that the number of roles are bounded and fixed.
Records the details about all of a roles containers on a node. The active field records the number of containers currently active.
active: int requested: transient int releasing: transient int last_used: long NodeEntry.available(): boolean = active - releasing == 0 && requested == 0
The two fields releasing and requested are used to track the ongoing state of YARN requests; they do not need to be persisted across freeze/thaw cycles. They may be relevant across AM restart, but without other data structures in the AM, not enough to track what the AM was up to before it was restarted. The strategy will be to ignore unexpected allocation responses (which may come from pre-restart) requests, while treating unexpected container release responses as failures.
The active counter is only decremented after a container release response has been received.
This is the existing org.apache.hoya.yarn.appmaster.state.RoleStatus class
A list mapping role to int enum is needed to index NodeEntry elements in the NodeInstance arrays. Although such an enum is already implemented in the Slider Providers, explicitly serializing and deserializing it would make the persistent structure easier to parse in other tools, and resilient to changes in the number or position of roles.
This list could also retain information about recently used/released nodes, so that the selection of containers to request could shortcut a search
The container priority field (a 32 bit integer) is used by Slider (0.5.x) to index the specific role in a container so as to determine which role has been offered in a container allocation message, and which role has been released on a release event.
The Role History needs to track outstanding requests, so that when an allocation comes in, it can be mapped back to the original request. Simply looking up the nodes on the provided container and decrementing its request counter is not going to work -the container may be allocated on a different node from that requested.
Proposal: The priority field of a request is divided by Slider into 8 bits for roleID and 24 bits for requestID. The request ID will be a simple rolling integer -Slider will assume that after 2^24 requests per role, it can be rolled, -though as we will be retaining a list of outstanding requests, a clash should not occur. The main requirement is: not have > 2^24 outstanding requests for instances of a specific role, which places an upper bound on the size of a Slider cluster.
The splitting and merging will be implemented in a ContainerPriority class, for uniform access.
Tracks an outstanding request. This is used to correlate an allocation response (whose Container Priority file is used to locate this request), with the node and role used in the request.
roleId: int requestID : int node: string (may be null) requestedTime: long priority: int = requestID << 24 | roleId
The node identifier may be null -which indicates that a request was made without a specific target node
Contains a map from requestID to the specific OutstandingRequest made, and generates the request ID
nextRequestId: int requestMap(RequestID) -> OutstandingRequest
Operations
addRequest(NodeInstance, RoleId): OutstandingRequest
(and an updated request Map with a new entry)
lookup(RequestID): OutstandingRequest
remove(RequestID): OutstandingRequest
listRequestsForNode(ClusterID): [OutstandingRequest]
The list operation can be implemented inefficiently unless it is found to be important -if so a more complex structure will be needed.
This is a field in RoleHistory
availableNodes: List<NodeInstance>[]
For each role, lists nodes that are available for data-local allocation, ordered by more recently released - To accelerate node selection
The performance benefit is most significant when requesting multiple nodes, as the scan for M locations from N nodes is reduced from M*N comparisons to 1 Sort + M list lookups.
Each list can be created off the Node Map by building for each role a sorted list of all Nodes which are available for an instance of that role, using a comparator that places the most recently released node ahead of older nodes.
This list is not persisted -when a Slider Cluster is frozen it is moot, and when an AM is restarted this structure will be rebuilt.
If the list is empty during a container request operation, it means that the Role History does not know of any nodes in the cluster that have hosted instances of that role and which are not in use. There are then two possible strategies to select a role
Strategy #1 is simpler; Strategy #2 may decrease the affinity in the cluster, as the AM will be explicitly requesting an instance on a node which it knows is not running an instance of that role.
Should a node whose container just failed be placed at the top of the stack, ready for the next request?
If the container failed due to an unexpected crash in the application, asking for that container back is the absolute right strategy -it will bring back a new role instance on that machine.
If the container failed because the node is now offline, the container request will not be satisfied by that node.
If there is a problem with the node, such that containers repeatedly fail on it, then re-requesting containers on it will amplify the damage.
When thawing, the Role History should be loaded -if it is missing Slider must revert to the bootstrap actions.
If found, the Role History will contain Slider‘s view of the Slider Cluster’s state at the time the history was saved, explicitly recording the last-used time of all nodes no longer hosting a role's container. By noting which roles were actually being served, it implicitly notes which nodes have a last_used value greater than any of the last_used fields persisted in the file. That is: all node entries listed as having active nodes at the time the history was saved must have more recent data than those nodes listed as inactive.
When rebuilding the data structures, the fact that nodes were active at save time must be converted into the data that indicates that the nodes were at least in use at the time the data was saved. The state of the cluster after the last save is unknown.
1: Role History loaded; Failure => Bootstrap. 2: Future: if role list enum != current enum, remapping could take place. Until then: fail. 3: Mark all nodes as active at save time to that of the
//define a threshold threshold = rolehistory.saveTime - 7246060 1000
for (clusterId, clusternode) in rolehistory.clusterNodes().entries() :
for (role, nodeEntry) in clusterNode.getNodeEntries():
nodeEntry.requested = 0
nodeEntry.releasing = 0
if nodeEntry.active > 0 :
nodeEntry.last_used = rolehistory.saveTime;
nodeEntry.n.active = 0
if nodeEntry.last_used < threshold :
clusterNode.remove(role)
else:
availableNodes[role].add(clusterId)
if clusterNode.getNodeEntries() isEmpty :
rolehistory.clusterNodes.remove(clusterId)
for availableNode in availableNodes:
sort(availableNode,new last_used_comparator())
After this operation, the structures are purged with all out of date entries, and the available node list contains a sorted list of the remainder.
1: Create the initial data structures as the thaw operation 2: update the structure with the list of live nodes, removing those nodes from the list of available nodes
now = time() activeContainers = RM.getActiveContainers() for container in activeContainers: nodeId = container.nodeId clusterNode = roleHistory.nodemap.getOrCreate(nodeId) role = extractRoleId(container.getPriority) nodeEntry = clusterNode.getOrCreate(role) nodeEntry.active++ nodeEntry.last_used = now availableNodes[role].remove(nodeId)
There's no need to resort the available node list -all that has happened is that some entries have been removed
Issue: what if requests come in for a (role, requestID) for the previous instance of the AM? Could we just always set the initial requestId counter to a random number and hope the collision rate is very, very low (2^24 * #(outstanding_requests)). If YARN-1041 ensures that a restarted AM does not receive outstanding requests, this issue goes away.
This strategy is designed to eliminate the expectation that there will ever be a clean shutdown -and so that the startup-time code should expect the Role History to have been written during shutdown. Instead the code should assume that the history was saved to disk at some point during the life of the Slider Cluster -ideally after the most recent change, and that the information in it is only an approximate about what the previous state of the cluster was.
rolenode = availableNodes[roleId].pop() if node != null : node.nodeEntry[roleId].requested++; outstanding = outstandingRequestTracker.addRequest(node, roleId) request.node = node request.priority = outstanding.priority //update existing Slider role status roleStatus[roleId].incRequested();
There is a bias here towards previous nodes, even if the number of nodes in the cluster has changed. This is why a node is picked where the number of active-releasing == 0 and requested == 0, rather than where it is simply the lowest value of active + requested - releasing: if there is no node in the nodemap that is not running an instance of that role, it is left to the RM to decide where the role instance should be instantiated.
This bias towards previously used nodes also means that (lax) requests will be made of nodes that are currently unavailable either because they are offline or simply overloaded with other work. In such circumstances, the node will have an active count of zero -so the search will find these nodes and request them -even though the requests cannot be satisfied. As a result, the request will be downgraded to a rack-local or cluster-wide, request -an acceptable degradation on a cluster where all the other entries in the nodemap have instances of that specific node -but not when there are empty nodes.
Add some randomness in the search of the datastructure, rather than simply iterate through the values. This would prevent the same unsatisfiable node from being requested first.
Keep track of requests, perhaps through a last-requested counter -and use this in the selection process. This would radically complicate the selection algorithm, and would not even distinguish “node recently released that was also the last requested” from “node that has not recently satisfied requests even though it was recently requested”.
Keep track of requests that weren‘t satisfied, so identify a node that isn’t currently satisfying requests.
Without using that history, there is a risk that a very old assignment is used in place of a recent one and the value of locality decreased.
But there are consequences:
Performance:
Using the history to pick a recent node may increase selection times on a large cluster, as for every instance needed, a scan of all nodes in the nodemap is required (unless there is some clever bulk assignment list being built up), or a sorted version of the nodemap is maintained, with a node placed at the front of this list whenever its is updated.
Thaw-time problems
There is also the risk that while thawing, the rolehistory.saved flag may be updated while the cluster flex is in progress, so making the saved nodes appear out of date. Perhaps the list of recently released nodes could be rebuilt at thaw time.
The proposed recentlyReleasedList addresses this, though it creates another data structure to maintain and rebuild at cluster thaw time from the last-used fields in the node entries.
void onContainersAllocated(List<Container> allocatedContainers)
This is the callback received when containers have been allocated. Due to (apparently) race conditions, the AM may receive duplicate container allocations -Slider already has to recognize this and currently simply discards any surplus.
If the AM tracks outstanding requests made for specific hosts, it will need to correlate allocations with the original requests, so as to decrement the node-specific request count. Decrementing the request count on the allocated node will not work, as the allocation may not be to the node originally requested.
assignments = []
operations = []
for container in allocatedContainers:
cid = container.getId();
roleId = container.priority & 0xff
nodeId = container.nodeId
outstanding = outstandingRequestTracker.remove(C.priority)
roleStatus = lookupRoleStatus(container);
roleStatus.decRequested();
allocated = roleStatus.incActual();
if outstanding == null || allocated > desired :
operations.add(new ContainerReleaseOperation(cid))
surplusNodes.add(cid);
surplusContainers++
roleStatus.decActual();
else:
assignments.add(new ContainerAssignment(container, role))
node = nodemap.getOrCreate(nodeId)
nodeentry = node.get(roleId)
if nodeentry == null :
nodeentry = new NodeEntry()
node[roleId] = nodeentry
nodeentry.active = 1
else:
if nodeentry.requested > 0 :
nodeentry.requested--
nodeentry.active++
nodemap.dirty = true
// work back from request ID to node where the
// request was outstanding
requestID = outstanding != null? outstanding.nodeId : null
if requestID != null:
reqNode = nodeMap.get(requestID)
reqNodeEntry = reqNode.get(roleId)
reqNodeEntry.requested--
if reqNodeEntry.available() :
availableNodeList.insert(reqNodeEntry)
At end of this, there is a node in the nodemap, which has recorded that there is now an active node entry for that role. The outstanding request has been removed.
If a callback comes in for which there is no outstanding request, it is rejected (logged, ignored, etc). This handles duplicate responses as well as any other sync problem.
The node selected for the original request has its request for a role instance decremented, so that it may be viewed as available again. The node is also re-inserted into the AvailableNodes list -not at its head, but at its position in the total ordering of the list.
onContainerStarted(ContainerId containerId)
The AM uses this as a signal to remove the container from the list of starting containers, moving it into the map of live nodes; the counters in the associated RoleInstance are updated accordingly; the node entry adjusted to indicate it has one more live node and one less starting node.
The AM uses this as a signal to remove the container from the list of starting containers -the count of starting containers for the relevant NodeEntry is decremented. If the node is now available for instances of this container, it is returned to the queue of available nodes.
Simple strategy: find a node with at least one active container
select a node N in nodemap where for NodeEntry[roleId]: active > releasing; nodeentry = node.get(roleId) nodeentry.active--;
Advanced Strategy:
Scan through the map looking for a node where active >1 && active > releasing. If none are found, fall back to the previous strategy
This is guaranteed to release a container on any node with >1 container in use, if such a node exists. If not, the scan time has increased to #(nodes).
Once a node has been identified
containersBeingReleased Map has the container inserted into itAfter the AM processes the request, it triggers a callback
void onContainersCompleted(List<ContainerStatus> completedContainers)
This callback returns a list of containers that have completed.
These need to be split into successful completion of a release request and containers which have failed.
This is currently done by tracking which containers have been queued for release, as well as which were rejected as surplus before even having any role allocated onto them.
A container is considered to have failed if it was an active container which has completed although it wasn't on the list of containers to release
shouldReview = false
for container in completedContainers:
containerId = container.containerId
nodeId = container.nodeId
node = nodemap.get(nodeId)
if node == null :
// unknown node
continue
roleId = node.roleId
nodeentry = node.get(roleId)
nodeentry.active--
nodemap.dirty = true
if getContainersBeingReleased().containsKey(containerId) :
// handle container completion
nodeentry.releasing --
// update existing Slider role status
roleStatus[roleId].decReleasing();
containersBeingReleased.remove(containerId)
else:
//failure of a live node
roleStatus[roleId].decActual();
shouldReview = true
if nodeentry.available():
nodentry.last_used = now()
availableNodes[roleId].insert(node)
//trigger a comparison of actual vs desired
if shouldReview :
reviewRequestAndReleaseNodes()
By calling reviewRequestAndReleaseNodes() the AM triggers a re-evaluation of how many instances of each node a cluster has, and how many it needs. If a container has failed and that freed up all role instances on that node, it will have been inserted at the front of the availableNodes list. As a result, it is highly likely that a new container will be requested on the same node. (The only way a node the list would be newer is be if other containers were completed in the same callback)
Notes made while implementing the design.
OutstandingRequestTracker should also track requests made with no target node; this makes seeing what is going on easier. ARMClientImpl is doing something similar, on a priority-by-priority basis -if many requests are made, each with their own priority, that base class's hash tables may get overloaded. (it assumes a limited set of priorities)
Access to the role history datastructures was restricted to avoid synchronization problems. Protected access is permitted so that a test subclass can examine (and change?) the internals.
`NodeEntries need to add a launching value separate from active so that when looking for nodes to release, no attempt is made to release a node that has been allocated but is not yet live.
We can't reliably map from a request to a response. Does that matter? If we issue a request for a host and it comes in on a different port, do we care? Yes -but only because we are trying to track nodes which have requests outstanding so as not to issue new ones. But if we just pop the entry off the available list, that becomes moot.
Proposal: don't track the requesting numbers in the node entries, just in the role status fields.
but: this means that we never re-insert nodes onto the available list if a node on them was requested but not satisfied.
Other issues: should we place nodes on the available list as soon as all the entries have been released? I.e. Before YARN has replied
RoleStats were removed -left in app state. Although the rolestats would belong here, leaving them where they were reduced the amount of change in the AppState class, so risk of something breaking.
Mini YARN cluster NodeIDs all share the same hostname , at least when running against file://; so mini tests with >1 NM don't have a 1:1 mapping of NodeId:NodeInstance. What will happen is that NodeInstance getOrCreateNodeInstance(Container container) ' will always return the same (now shared) NodeInstance`.
When identifying instances to release in a bulk downscale operation, the full list of targets must be identified together. This is not just to eliminate multiple scans of the data structures, but because the containers are not released until the queued list of actions are executed -the nodes' release-in-progress counters will not be incremented until after all the targets have been identified.
It also needs to handle the scenario where there are many role instances on a single server -it should prioritize those.
The NodeMap/NodeInstance/NodeEntry structure is adequate for identifying nodes, at least provided there is a 1:1 mapping of hostname to NodeInstance. But it is not enough to track containers in need of release: the AppState needs to be able to work backwards from a NodeEntry to container(s) stored there.
The AppState class currently stores this data in a ConcurrentMap<ContainerId, RoleInstance>
To map from NodeEntry/NodeInstance to containers to delete, means that either a new datastructure is created to identify containers in a role on a specific host (e.g a list of ContainerIds under each NodeEntry), or we add an index reference in a RoleInstance that identifies the node. We already effectively have that in the container
When scanning the available list, any nodes that are no longer idle for that role should be dropped from the list.
This can happen when an instance was allocated on a different node from that requested.
known to be available
One condition found during testing is the following:
In this situation, the findNodeForNewInstance method returns null: there is no recommended location for placement. However, this is untrue: all nodes in the cluster other than those in use are the recommended nodes.
It would be possible to build up a list of all known nodes in the cluster that are not running this role and use that in the request, effectively telling the AM to pick one of the idle nodes. By not doing so, we increase the probability that another instance of the same role will be allocated on a node in use, a probability which (were there capacity on these nodes and placement random), be 1/(clustersize-roleinstances). The smaller the cluster and the bigger the application, the higher the risk.
This could be revisited, if YARN does not support anti-affinity between new requests at a given priority and existing ones: the solution would be to issue a relaxed placement request listing all nodes that are in the NodeMap and which are not running an instance of the specific role. [To be even more rigorous, the request would have to omit those nodes for which an allocation has already been made off the available list and yet for which no container has yet been granted].
The reworked request tracker behaves as follows
(role, hostname)This strategy returns unused hosts to the list of possible hosts, while retaining the ordering of that list in most-recent-first.
if one or more container requests cannot be satisifed, then all the hosts in the set of outstanding requests will be retained, so all these hosts in the will be considered unavailable for new location-specific requests. This may imply that new requests that could be explicity placed will now only be randomly placed -however, it is moot on the basis that if there are outstanding container requests it means the RM cannot grant resources: new requests at the same priority (i.e. same Slider Role ID) will not be granted either.
The only scenario where this would be different is if the resource requirements of instances of the target role were decreated during a cluster flex such that the placement could now be satisfied on the target host. This is not considered a significant problem.
The initial implementation uses the JSON-formatted Avro format; while significantly less efficient than a binary format, it is human-readable
Here are sequence of entries from a test run on a single node cluster; running 1 HBase Master and two region servers.
Initial save; the instance of Role 1 (HBase master) is live, Role 2 (RS) is not.
{"entry":{"org.apache.hoya.avro.RoleHistoryHeader":{"version":1,"saved":1384183475949,"savedx":"14247c3aeed","roles":3}}}
{"entry":{"org.apache.hoya.avro.NodeEntryRecord":{"host":"192.168.1.85","role":1,"active":true,"last_used":0}}}
{"entry":{"org.apache.hoya.avro.NodeEntryRecord":{"host":"192.168.1.85","role":2,"active":false,"last_used":0}}}
At least one RS is live:
{"entry":{"org.apache.hoya.avro.RoleHistoryFooter":{"count":2}}}{"entry":{"org.apache.hoya.avro.RoleHistoryHeader":{"version":1,"saved":1384183476010,"savedx":"14247c3af2a","roles":3}}}
{"entry":{"org.apache.hoya.avro.NodeEntryRecord":{"host":"192.168.1.85","role":1,"active":true,"last_used":0}}}
{"entry":{"org.apache.hoya.avro.NodeEntryRecord":{"host":"192.168.1.85","role":2,"active":true,"last_used":0}}}
Another entry is saved -presumably the second RS is now live, which triggered another write
{"entry":{"org.apache.hoya.avro.RoleHistoryFooter":{"count":2}}}{"entry":{"org.apache.hoya.avro.RoleHistoryHeader":{"version":1,"saved":1384183476028,"savedx":"14247c3af3c","roles":3}}}
{"entry":{"org.apache.hoya.avro.NodeEntryRecord":{"host":"192.168.1.85","role":1,"active":true,"last_used":0}}}
{"entry":{"org.apache.hoya.avro.NodeEntryRecord":{"host":"192.168.1.85","role":2,"active":true,"last_used":0}}}
At this point the cluster was frozen and thawed. Slider does not save the cluster state at freeze time, but does as it is rebuilt.
When the cluster is restarted, every node that was active for a role at the time the file was saved 1384183476028 is given a last_used timestamp of that time.
When the history is next saved, the master has come back onto the (single) node, it is active while its last_used timestamp is the previous file's timestamp. No region servers are yet live.
{"entry":{"org.apache.hoya.avro.RoleHistoryFooter":{"count":2}}}{"entry":{"org.apache.hoya.avro.RoleHistoryHeader":{"version":1,"saved":1384183512173,"savedx":"14247c43c6d","roles":3}}}
{"entry":{"org.apache.hoya.avro.NodeEntryRecord":{"host":"192.168.1.85","role":1,"active":true,"last_used":1384183476028}}}
{"entry":{"org.apache.hoya.avro.NodeEntryRecord":{"host":"192.168.1.85","role":2,"active":false,"last_used":1384183476028}}}
Here a region server is live
{"entry":{"org.apache.hoya.avro.RoleHistoryFooter":{"count":2}}}{"entry":{"org.apache.hoya.avro.RoleHistoryHeader":{"version":1,"saved":1384183512199,"savedx":"14247c43c87","roles":3}}}
{"entry":{"org.apache.hoya.avro.NodeEntryRecord":{"host":"192.168.1.85","role":1,"active":true,"last_used":1384183476028}}}
{"entry":{"org.apache.hoya.avro.NodeEntryRecord":{"host":"192.168.1.85","role":2,"active":true,"last_used":1384183476028}}}
And here, another region server has started. This does not actually change the contents of the file
{"entry":{"org.apache.hoya.avro.RoleHistoryFooter":{"count":2}}}{"entry":{"org.apache.hoya.avro.RoleHistoryHeader":{"version":1,"saved":1384183512217,"savedx":"14247c43c99","roles":3}}}
{"entry":{"org.apache.hoya.avro.NodeEntryRecord":{"host":"192.168.1.85","role":1,"active":true,"last_used":1384183476028}}}
{"entry":{"org.apache.hoya.avro.NodeEntryRecord":{"host":"192.168.1.85","role":2,"active":true,"last_used":1384183476028}}}
The last_used timestamps will not be changed until the cluster is shrunk or thawed, as the active flag being set implies that the server is running both roles at the save time of 1384183512217.
How best to distinguish at thaw time from nodes used just before thawing from nodes used some period before? Should the RoleHistory simply forget about nodes which are older than some threshold when reading in the history?
we just track last used times
Is there a way to avoid tracking the outstanding requests?
No
What will the strategy of picking the most-recently-used node do if that node creates the container and then fails to start it up. Do we need to add blacklisting too? Or actually monitor the container start time, and if a container hasn‘t been there for very long, don’t pick it.
Startup failures drop the node from the ready-to-use list; the node is no longer trusted. We don't blacklist it (yet)
Should we prioritise a node that was used for a long session ahead of a node that was used more recently for a shorter session? Maybe, but it complicates selection as generating a strict order of nodes gets significantly harder.
No: you need to start tracking aggregate execution time, for the last session. In a stable state, all servers recorded in the history will have spread the data amongst them, so its irrelevant.