[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mingliang Liu updated HDFS-9184:
Issue Type: New Feature (was: Task)
> 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: New Feature
>Reporter: Mingliang Liu
>Assignee: Mingliang Liu
> Fix For: 2.8.0
>
> Attachments: HDFS-9184.000.patch, HDFS-9184.001.patch,
> HDFS-9184.002.patch, HDFS-9184.003.patch, HDFS-9184.004.patch,
> HDFS-9184.005.patch, HDFS-9184.006.patch, HDFS-9184.007.patch,
> HDFS-9184.008.patch, HDFS-9184.009.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 work.
> 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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[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Xiaobing Zhou updated HDFS-9184:
Assignee: Mingliang Liu (was: Xiaobing Zhou)
> 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
> Fix For: 2.8.0
>
> Attachments: HDFS-9184.000.patch, HDFS-9184.001.patch,
> HDFS-9184.002.patch, HDFS-9184.003.patch, HDFS-9184.004.patch,
> HDFS-9184.005.patch, HDFS-9184.006.patch, HDFS-9184.007.patch,
> HDFS-9184.008.patch, HDFS-9184.009.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 work.
> 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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[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Jitendra Nath Pandey updated HDFS-9184:
---
Fix Version/s: 2.8.0
> 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
> Fix For: 2.8.0
>
> Attachments: HDFS-9184.000.patch, HDFS-9184.001.patch,
> HDFS-9184.002.patch, HDFS-9184.003.patch, HDFS-9184.004.patch,
> HDFS-9184.005.patch, HDFS-9184.006.patch, HDFS-9184.007.patch,
> HDFS-9184.008.patch, HDFS-9184.009.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 work.
> 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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[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Jitendra Nath Pandey updated HDFS-9184:
---
Resolution: Fixed
Release Note: The feature needs to enabled by setting
"hadoop.caller.context.enabled" to true. When the feature is used, additional
fields are written into namenode audit log records.
Status: Resolved (was: Patch Available)
I have committed this to trunk and branch-2. Thanks to Mingliang Liu.
> 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
> Fix For: 2.8.0
>
> Attachments: HDFS-9184.000.patch, HDFS-9184.001.patch,
> HDFS-9184.002.patch, HDFS-9184.003.patch, HDFS-9184.004.patch,
> HDFS-9184.005.patch, HDFS-9184.006.patch, HDFS-9184.007.patch,
> HDFS-9184.008.patch, HDFS-9184.009.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 work.
> 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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[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mingliang Liu updated HDFS-9184:
Attachment: HDFS-9184.009.patch
The v9 patch rebases from {{trunk}} branch and resolves trivial conflicts.
> 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, HDFS-9184.003.patch, HDFS-9184.004.patch,
> HDFS-9184.005.patch, HDFS-9184.006.patch, HDFS-9184.007.patch,
> HDFS-9184.008.patch, HDFS-9184.009.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 work.
> 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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[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mingliang Liu updated HDFS-9184:
Attachment: HDFS-9184.008.patch
Per offline discussion, the {{signature}} is changed from {{String}} to
{{byte[]}}. We also use {{LogCapture}} for testing end-to-end caller context
logging.
> 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, HDFS-9184.003.patch, HDFS-9184.004.patch,
> HDFS-9184.005.patch, HDFS-9184.006.patch, HDFS-9184.007.patch,
> HDFS-9184.008.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 work.
> 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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[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mingliang Liu updated HDFS-9184:
Attachment: HDFS-9184.007.patch
Thanks for your view, [~jnp]. The v7 patch addresses the latest comments.
> 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, HDFS-9184.003.patch, HDFS-9184.004.patch,
> HDFS-9184.005.patch, HDFS-9184.006.patch, HDFS-9184.007.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 work.
> 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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[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mingliang Liu updated HDFS-9184:
Status: Patch Available (was: Open)
> 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, HDFS-9184.003.patch, HDFS-9184.004.patch,
> HDFS-9184.005.patch, HDFS-9184.006.patch, HDFS-9184.007.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 work.
> 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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[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mingliang Liu updated HDFS-9184:
Status: Open (was: Patch Available)
> 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, HDFS-9184.003.patch, HDFS-9184.004.patch,
> HDFS-9184.005.patch, HDFS-9184.006.patch, HDFS-9184.007.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 work.
> 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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[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mingliang Liu updated HDFS-9184:
Attachment: HDFS-9184.006.patch
The v6 patch fixes checkstyle and findbugs warnings.
> 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, HDFS-9184.003.patch, HDFS-9184.004.patch,
> HDFS-9184.005.patch, HDFS-9184.006.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 work.
> 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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[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Jitendra Nath Pandey updated HDFS-9184:
---
Status: Open (was: Patch Available)
> 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 work.
> 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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[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Jitendra Nath Pandey updated HDFS-9184:
---
Status: Patch Available (was: Open)
> 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 work.
> 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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[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mingliang Liu updated HDFS-9184:
Attachment: HDFS-9184.004.patch
The v4 patch fixes the audit log format, separating the caller context and
signature with colon :
> 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, HDFS-9184.003.patch, HDFS-9184.004.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 work.
> 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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[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mingliang Liu updated HDFS-9184:
Attachment: HDFS-9184.005.patch
Thanks for your comment [~leftnoteasy]. it makes perfect sense to me that the
caller context is inherited in the child thread, as we don't support caller
context hierarchy (which was by-design). Please note that the child thread is
free to override its own current caller context.
The v5 patch addresses this with updated unit test.
> 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, HDFS-9184.003.patch, HDFS-9184.004.patch,
> HDFS-9184.005.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 work.
> 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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[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mingliang Liu updated HDFS-9184:
Attachment: HDFS-9184.003.patch
The failing tests seem unrelated. While the "cancel patch" and "submit patch"
trick did not trigger the Jenkins again, I simply rebase the v2 patch from
{{trunk}} branch and submit again, which is called v3.
Thanks [~jnp] for reviewing the code.
> 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, HDFS-9184.003.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 work.
> 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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[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mingliang Liu updated HDFS-9184:
Status: Patch Available (was: Open)
> 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 work.
> 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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[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mingliang Liu updated HDFS-9184:
Status: Open (was: Patch Available)
> 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 work.
> 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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[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
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 work.
> 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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[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mingliang Liu updated HDFS-9184:
Status: Patch Available (was: Open)
> 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 work.
> 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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[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mingliang Liu updated HDFS-9184:
Attachment: HDFS-9184.001.patch
Thanks all for the input.
Before we have a perfect solution, we consider this approach a feasible option
for the heavily needed goal. In terms of security, it seems flawed. There is a
signature field when building the caller context which may be useful for the
offline analysis and validation.
The v1 patch aims to address the incompatible concern. We don't think there is
"significant compatibility" issue here. Specially,
* We won't record the caller context unless its config key is explicitly turned
on by users
* NO existing API is changed to implement this feature
* The current layout of the audit log is not changed as there will be an
*optional* kvp in the end of the line.
Just for the record: it's good to make audit log itself have well-defined
structure and format in the future.
As using {{htrace}}, which depends on 100% sampling across many spans, is
totally different from this approach, this patch does not adopt it. If
performance problem is really a concern, I don't expect {{htrace}} can do
better.
> 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
>
>
> 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 work.
> 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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[jira] [Updated] (HDFS-9184) Logging HDFS operation's caller context into audit logs
[
https://issues.apache.org/jira/browse/HDFS-9184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mingliang Liu updated HDFS-9184:
Attachment: HDFS-9184.000.patch
The v0 patch implements this idea as early effort.
> 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
>
>
> 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 work.
> 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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