README.md

Ignite cluster & node lifecycle

This document describes user-level and component-level cluster lifecycles and their mutual interaction.

Node lifecycle

A node maintains its local state in the local persistent key-value storage named vault. The data stored in the vault is semantically divided in the following categories:

• User-level local configuration properties (such as memory limits, network timeouts, etc). User-level configuration properties can be written both at runtime (not all properties will be applied at runtime, however, - some of them will require a full node restart) and when a node is shut down (in order to be able to change properties that prevent node startup for some reason)
• System-level private properties (such as computed local statistics, node-local commin paths, etc). System-level private properties are computed locally based on the information available at node locally (not based on metastorage watched values)
• System-level distributed metastorage projected properties (such as paths to partition files, etc). System-level projected properties are associated with one or more metastorage properties and are computed based on the local node state and the metastorage properties values. System-level projected properties values are semantically bound to a particular revision of the dependee properties and must be recalculated when dependees are changed (see reliable watch processing).

The vault is created during the first node startup and optionally populated with the paremeters from the configuration file passed in to the ignite node start [command](TODO link to CLI readme). Only user-level properties can be written via the provided file.

System-level properties are written to the storage during the first vault initialization by the node start process. Projected properties are not initialized during the initial node startup because at this point the local node is not aware of the distributed metastorage. The node remains in a 'zombie' state until after it learns that there is an initialized metastorage (either via the ignite cluster init [command](TODO link to CLI readme) during the initial cluster initialization) or from the group membershup service via gossip (implying that group membership protocol is working at this point).

Node components startup

For testability purposes, we require that component dependencies are defined upfront and provided at the construction time. This additionaly requires that component dependencies form no cycles. Therefore, components form an acyclic directed graph that is constructed in topological sort order wrt root.

Components created and initialized also in an order consistent with a topological sort of the components graph. This enforces serveral rules related to the components interaction:

• Since metastorage watches can only be added during the component startup, the watch notification order is consistent with the component initialization order. I.e. if a component B depdends on a component A, then A receives watch notification prior to B.
• Dependent component can directly call an API method on a dependee component (because it can obtain the dependee reference during construction). Direct inverse calls are prohibited (this is enforced by only acquiring component references during the components construction). Nevertheless, inverse call can be implemented by means of listeners or callbacks: the dependent component installs a listener to a dependeee, which can be later invoked.

The diagram above shows the component dependency diagram and provides an order in which compomnents may be initialized.

Cluster lifecycle

For a cluster to become operational, the metastorage instance must be initialized first. The initialization command chooses a set of nodes (normally, 3 - 5 nodes) to host the distributed metastorage Raft group. When a node receives the initialization command, it either creates a bootstrapped Raft instance with the given members (if this is a metastorage group node), or writes the metastorage group member IDs to the vault as a private system-level property.

After the metastorage is initialized, components start to receive and process watch events, updating the local state according to the changes received from the watch.

An entry point to user-initiated cluster state changes is cluster configuration. Configuration module provides convenient ways for managing configuration both as Java API, as well as from ignite command line utility.

Reliable configuration changes

Any configuration change is translated to a metastorage multi-update and has a single configuration change ID. This ID is used to enforce CAS-style configuration changes and to ensure no duplicate configuration changes are executed during the cluster runtime. To reliably process cluster configuration changes, we introduce an additional metastorage key

internal.configuration.applied=<change ID>

that indicates the configuration change ID that was already processed and corresponding changes are written to the metastorage. Whenever a node processes a configuration change, it must also conditionally update the internal.configuration.applied value checking that the previous value is smaller than the change ID being applied. This prevents configuration changes being processed more than once. Any metastorage update that processes configuration change must update this key to indicate that this configuraion change has been already processed. It is safe to process the same configuration change more than once since only one update will be applied.

Reliable watch processing

All cluster state is written and maintained in the metastorage. Nodes may update some state in the metastorage, which may require a recomputation of some other metastorage properties (for example, when cluster baseline changes, Ignite needs to recalculate table partition assignments). In other words, some properties in the metastore are dependent on each other and we may need to reliably update one property in response to an update to another.

To facilitate this pattern, Ignite uses the metastorage ability to replay metastorage changes from a certain revision called [watch](TODO link to metastorage watch). To process watch updates reliably, we associate a special persistent value called applied revision (stored in the vault) with each watch. We rely on the following assumptions about the reliable watch processing:

• Watch execution is idempotent (if the same watch event is processed twice, the second watch invocation will have no effect on the system). This is usually enforced by conditional multi-update operations for the metastorage and deterministic projected properties calculations. The conditional multi-update should check that the revision of the key being updated matches the revision observed with the watch's event upper bound.
• All properties read inside the watch must be read with the upper bound equal to the watch event revision.
• If watch processing initiates a metastorage update, the applied revision is propagated only after the metastorage confirmed that the proposed change is committed (note that in this case it does not matter whether this particular multi-update succeeds or not: we know that the first multi-update will succeed, and all further updates are idempotent, so we need to make sure that at least one multi-update is committed).
• If watch processing initiates projected keys writes to the vault, the keys must be written atomically with the updated applied revision value.
• If a watch initiates metastorage properties update, it should only be deployed on the metastorage group members to avoid massive identical updates being issued to the metastorage (TODO: should really be only the leader of the metastorage Raft group).

In a case of a crash, each watch is restared from the revision stored in the corresponding applied revision variable of the watch, and not processed events are replayed.

Stop node flow.

It's possible to stop node both when node was already started or during the startup process, in that case node stop will prevent any new components startup and stop already started ones.

Following method was added to Ignition interface:

    /**
     * Stops the node with given {@code name}.
     * It's possible to stop both already started node or node that is currently starting.
     * Has no effect if node with specified name doesn't exist.
     *
     * @param name Node name to stop.
     * @throws IllegalArgumentException if null is specified instead of node name.
     */
    public void stop(String name);

It's also possible to stop a node by calling close() on an already started Ignite instance.

As a starting point stop process checks node status:

• If it's STOPPING - nothing happens, cause previous intention to stop node was already detected.
• If it's STARTING (means that node is somewhere in the middle of the startup process) - node status will be updated to STOPPING and later on startup process will detect status change on attempt of starting next component, prevent further startup process and stop already started managers and corresponding inner components.
• if it's STARTED - explicit stop will take an action. All components will be stopped.

In all cases the node stop process consists of two phases:

• At phase one onNodeStop() will be called on all started components in reverse order, meaning that the last started component will run onNodeStop() first. For most components onNodeStop() will be No-op. Core idea here is to stop network communication on onNodeStop() in order to terminate distributed operations gracefully: no network communication is allowed but node local logic still remains consistent.
• At phase two within a write busy lock, stop() will be called on all started components also in reverse order, here thread stopping logic, inner structures cleanup and other related logic takes it time. Please pay attention that at this point network communication isn't possible.

Besides local node stopping logic two more actions took place on a cluster as a result of node left event:

• Both range and watch cursors will be removed on server side. Given process is linearized with meta storage operations by using a meta storage raft.
• Baseline update and corresponding baseline recalculation with ongoing partition raft groups redeployment.