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From "Mingliang Liu (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
Date Sat, 10 Oct 2015 01:10:07 GMT

     [ https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel

Mingliang Liu updated HDFS-9184:
    Attachment: HDFS-9184.002.patch

To address some offline comments, the v2 patch makes the caller context's length limit configurable.
The default size is 128 bytes. Any comment is welcome.

> Logging HDFS operation's caller context into audit logs
> -------------------------------------------------------
>                 Key: HDFS-9184
>                 URL: https://issues.apache.org/jira/browse/HDFS-9184
>             Project: Hadoop HDFS
>          Issue Type: Task
>            Reporter: Mingliang Liu
>            Assignee: Mingliang Liu
>         Attachments: HDFS-9184.000.patch, HDFS-9184.001.patch, HDFS-9184.002.patch
> For a given HDFS operation (e.g. delete file), it's very helpful to track which upper
level job issues it. The upper level callers may be specific Oozie tasks, MR jobs, and hive
queries. One scenario is that the namenode (NN) is abused/spammed, the operator may want to
know immediately which MR job should be blamed so that she can kill it. To this end, the caller
context contains at least the application-dependent "tracking id".
> There are several existing techniques that may be related to this problem.
> 1. Currently the HDFS audit log tracks the users of the the operation which is obviously
not enough. It's common that the same user issues multiple jobs at the same time. Even for
a single top level task, tracking back to a specific caller in a chain of operations of the
whole workflow (e.g.Oozie -> Hive -> Yarn) is hard, if not impossible.
> 2. HDFS integrated {{htrace}} support for providing tracing information across multiple
layers. The span is created in many places interconnected like a tree structure which relies
on offline analysis across RPC boundary. For this use case, {{htrace}} has to be enabled at
100% sampling rate which introduces significant overhead. Moreover, passing additional information
(via annotations) other than span id from root of the tree to leaf is a significant additional
> 3. In [HDFS-4680 | https://issues.apache.org/jira/browse/HDFS-4680], there are some related
discussion on this topic. The final patch implemented the tracking id as a part of delegation
token. This protects the tracking information from being changed or impersonated. However,
kerberos authenticated connections or insecure connections don't have tokens. [HADOOP-8779]
proposes to use tokens in all the scenarios, but that might mean changes to several upstream
projects and is a major change in their security implementation.
> We propose another approach to address this problem. We also treat HDFS audit log as
a good place for after-the-fact root cause analysis. We propose to put the caller id (e.g.
Hive query id) in threadlocals. Specially, on client side the threadlocal object is passed
to NN as a part of RPC header (optional), while on sever side NN retrieves it from header
and put it to {{Handler}}'s threadlocals. Finally in {{FSNamesystem}}, HDFS audit logger will
record the caller context for each operation. In this way, the existing code is not affected.
> It is still challenging to keep "lying" client from abusing the caller context. Our proposal
is to add a {{signature}} field to the caller context. The client choose to provide its signature
along with the caller id. The operator may need to validate the signature at the time of offline
analysis. The NN is not responsible for validating the signature online.

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