- #Apache hadoop common github vs gitbox upgrade#
- #Apache hadoop common github vs gitbox full#
- #Apache hadoop common github vs gitbox code#
Minimum resources: While there are no guarantees on the minimum resources required by Hadoop daemons, the community attempts to not increase requirements within a minor release. Architecture: The community has no plans to restrict Hadoop to specific architectures, but can have family-specific optimizations. Field numbers are cheap and changing and reusing is not a good idea. Reuse an old field that was previously deleted. The following changes are incompatible and hence never allowed. Delete an optional field as long as the optional field has reasonable defaults to allow deletions. Modify a field type in an incompatible way (as defined recursively). Change the rpc/method parameter type or return type. The following changes are incompatible but can be considered only at a major release. #Apache hadoop common github vs gitbox code#
proto annotations that effect code generation (e.g.
Add a new optional request to a Message. Add an optional field, with the expectation that the code deals with the field missing due to communication with an older version of the code. The following changes are compatible and are allowed at any time:. proto file is marked as stable it means that changes should be made in a compatible fashion as described below: Client-Server protocols and Server-Server protocol. Compatibility can be broken only at a major release, though breaking compatibility even at major releases has grave consequences and should be discussed in the Hadoop community. (Different policies for different categories are yet to be considered.) Both Client-Server and Server-Server compatibility is preserved within a major release. Server-Server compatibility is required to allow mixed versions within an active cluster so the cluster may be upgraded without downtime in a rolling fashion. #Apache hadoop common github vs gitbox upgrade#
For example, upgrade HDFS from version 2.1.0 to 2.2.0 without upgrading MapReduce. Client-Server compatibility is also required to allow upgrading individual components without upgrading others.YARN applications that attempt to use new APIs (including new fields in data structures) that have not yet been deployed to the cluster can expect link exceptions. Note that new cluster features invoked by new client APIs or shell commands will not be usable.
#Apache hadoop common github vs gitbox full#
This allows deployment of client-side bug fixes ahead of full cluster upgrades. For example, a Hadoop 2.4.0 client talking to a Hadoop 2.3.0 cluster.
Client-Server compatibility is also required to allow users to upgrade the client before upgrading the server (cluster). For example, a Hadoop 2.1.0 client talking to a Hadoop 2.3.0 cluster. Client-Server compatibility is required to allow users to continue using the old clients even after upgrading the server (cluster) to a later version (or vice versa). Server-Server: communication between servers (e.g., the protocol between the DataNode and NameNode, or NodeManager and ResourceManager). Client-Server (Admin): It is worth distinguishing a subset of the Client-Server protocols used solely by administrative commands (e.g., the HAAdmin protocol) as these protocols only impact administrators who can tolerate changes that end users (which use general Client-Server protocols) can not. Client-Server: communication between Hadoop clients and servers (e.g., the HDFS client to NameNode protocol, or the YARN client to ResourceManager protocol). 
The potential communications can be categorized as follows: Non-RPC communication should be considered as well, for example using HTTP to transfer an HDFS image as part of snapshotting or transferring MapTask output. Preserving compatibility requires prohibiting modification as described below. Hadoop uses Protocol Buffers for most RPC communication. Wire compatibility concerns data being transmitted over the wire between Hadoop processes. Running Applications in Docker Containers.
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