[
https://issues.apache.org/jira/browse/HDFS-5751?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Arpit Agarwal updated HDFS-5751:
--------------------------------
Description:
The in-memory block map and disk interface portions of the DataNode have been
abstracted out into an {{FsDatasetpSpi}} interface, which further uses
{{FsVolumeSpi}} to represent individual volumes.
The abstraction is useful as it allows DataNode tests to use a
{{SimulatedFSDataset}} which does not write any data to disk. Instead it just
stores block metadata in memory and returns zeroes for all reads. This is
useful for both unit testing and for simulating arbitrarily large datanodes
without having to provision real disk capacity.
A 'real' DataNode uses {{FsDataSetImpl}}. Both {{FsDatasetImpl}} and
{{SimulatedFSDataset}} implement {{FsDatasetSpi}}.
However there are a few problems with this approach:
# Using the factory class significantly complicates the code flow for the
common case. This makes the code harder to understand and debug.
# There is additional burden of maintaining two different dataset
implementations.
# Fidelity between the two implementations is poor.
Instead we can eliminate the SPIs and just hide the disk read/write routines
with a dependency injection framework like Google Guice.
was:
The in-memory block map and disk interface portions of the DataNode have been
abstracted out into an {{FsDatasetpSpi}} interface, which further uses
{{FsVolumeSpi}} to represent individual volumes.
The abstraction is useful as it allows DataNode tests to use a
{{SimulatedFSDataset}} which does not write any data to disk. Instead it just
stores block metadata in memory and returns zeroes for all reads. This is
useful for both unit testing and for simulating arbitrarily large datanodes
without having to provision real disk capacity.
A 'real' DataNode uses {{FsDataSetImpl}}. Both {{FsDatasetImpl}} and
{{SimulatedFSDataset}} implement {{FsDatasetSpi}}.
However there are a few problems with this approach:
# Using the factory class significantly complicates the code flow for the
common case. This makes the code harder to understand and debug.
# There is additional burden of maintaining two different dataset
implementations.
# Fidelity between the two implementations is poor.
Instead we can get eliminate the SPIs and just hide the disk read/write
routines with a dependency injection framework like Google Guice.
> Remove the FsDatasetSpi and FsVolumeImpl interfaces
> ---------------------------------------------------
>
> Key: HDFS-5751
> URL: https://issues.apache.org/jira/browse/HDFS-5751
> Project: Hadoop HDFS
> Issue Type: Improvement
> Components: datanode, test
> Affects Versions: 3.0.0
> Reporter: Arpit Agarwal
>
> The in-memory block map and disk interface portions of the DataNode have been
> abstracted out into an {{FsDatasetpSpi}} interface, which further uses
> {{FsVolumeSpi}} to represent individual volumes.
> The abstraction is useful as it allows DataNode tests to use a
> {{SimulatedFSDataset}} which does not write any data to disk. Instead it just
> stores block metadata in memory and returns zeroes for all reads. This is
> useful for both unit testing and for simulating arbitrarily large datanodes
> without having to provision real disk capacity.
> A 'real' DataNode uses {{FsDataSetImpl}}. Both {{FsDatasetImpl}} and
> {{SimulatedFSDataset}} implement {{FsDatasetSpi}}.
> However there are a few problems with this approach:
> # Using the factory class significantly complicates the code flow for the
> common case. This makes the code harder to understand and debug.
> # There is additional burden of maintaining two different dataset
> implementations.
> # Fidelity between the two implementations is poor.
> Instead we can eliminate the SPIs and just hide the disk read/write routines
> with a dependency injection framework like Google Guice.
--
This message was sent by Atlassian JIRA
(v6.1.5#6160)
