[Cassandra Wiki] Trivial Update of Omar9973 by Omar9973
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[Cassandra Wiki] Trivial Update of Felipe08D by Felipe08D
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[Cassandra Wiki] Trivial Update of MaximoPur by MaximoPur
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[jira] [Commented] (CASSANDRA-5074) Add an official way to disable compaction
[ https://issues.apache.org/jira/browse/CASSANDRA-5074?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=13583140#comment-13583140 ] Andrea Gazzarini commented on CASSANDRA-5074: - Probably that wasn't clear, but honestly I believe it's a problem of mine: I have just a little bit of experience on Cassandra source code and its internal architecture. Ok, now I think I got the point about your idea, so I will continue investigating the code in order to implement that. A question: in case the logic is moved on the CompactionMananger, what should be, from client point of view, a nice and good way to indicate that the (background) compaction must be disabled? I believe the command line of my previous post is no longer appropriate create column family XYZ with compaction_strategy=NoCompactionStrategy Add an official way to disable compaction - Key: CASSANDRA-5074 URL: https://issues.apache.org/jira/browse/CASSANDRA-5074 Project: Cassandra Issue Type: Bug Reporter: Jonathan Ellis Priority: Minor Fix For: 1.2.2 We've traditionally used min or max compaction threshold = 0 to disable compaction, but this isn't exactly intuitive and it's inconsistently implemented -- allowed from jmx, not allowed from cli. -- This message is automatically generated by JIRA. If you think it was sent incorrectly, please contact your JIRA administrators For more information on JIRA, see: http://www.atlassian.com/software/jira
[Cassandra Wiki] Trivial Update of Valeria43 by Valeria43
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[jira] [Updated] (CASSANDRA-3430) Break Big Compaction Lock apart
[ https://issues.apache.org/jira/browse/CASSANDRA-3430?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Jonathan Ellis updated CASSANDRA-3430: -- Attachment: 3430-v2.txt v2 attached that removes compactionLock entirely, instead relying on disabling + cancelling current compactions for exceptional operations (vis., major compaction + truncate). reloading the CompactionStrategy is synchronized vs runWithCompactionsDisabled; otherwise, we're okay with allowing an old compaction strategy to finish in-progress work after installing a new one: markCompacting, which we respect more thoroughly after CASSANDRA-5256, keeps this from being dangerous, and it may end up saving us some work. Break Big Compaction Lock apart --- Key: CASSANDRA-3430 URL: https://issues.apache.org/jira/browse/CASSANDRA-3430 Project: Cassandra Issue Type: Improvement Components: Core Reporter: Jonathan Ellis Assignee: Jonathan Ellis Priority: Minor Labels: compaction Fix For: 2.0 Attachments: 3430-1.0.txt, 3430-1.1.txt, 3430-v2.txt -- This message is automatically generated by JIRA. If you think it was sent incorrectly, please contact your JIRA administrators For more information on JIRA, see: http://www.atlassian.com/software/jira
[jira] [Issue Comment Deleted] (CASSANDRA-5051) Allow automatic cleanup after gc_grace
[
https://issues.apache.org/jira/browse/CASSANDRA-5051?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Jonathan Ellis updated CASSANDRA-5051:
--
Comment: was deleted
(was: v3 adds an extra assert that is failing in CompactionsTest. Not sure why.
{code}
.
CompactionManager.instance.interruptCompactionFor(Collections.singleton(metadata));
while (CompactionManager.instance.isCompacting(metadata))
FBUtilities.sleep(100);
assert data.getCompacting().isEmpty();
{code})
Allow automatic cleanup after gc_grace
--
Key: CASSANDRA-5051
URL: https://issues.apache.org/jira/browse/CASSANDRA-5051
Project: Cassandra
Issue Type: New Feature
Components: Core
Reporter: Brandon Williams
Assignee: Vijay
Labels: vnodes
Fix For: 2.0
Attachments: 0001-CASSANDRA-5051.patch, 3430-v3.txt
When using vnodes, after adding a new node you have to run cleanup on all the
machines, because you don't know which are affected and chances are it was
most if not all of them. As an alternative to this intensive process, we
could allow cleanup during compaction if the data is older than gc_grace (or
perhaps some other time period since people tend to use gc_grace hacks to get
rid of tombstones.)
--
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[jira] [Updated] (CASSANDRA-5051) Allow automatic cleanup after gc_grace
[
https://issues.apache.org/jira/browse/CASSANDRA-5051?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Jonathan Ellis updated CASSANDRA-5051:
--
Attachment: 3430-v3.txt
v3 adds an extra assert that is failing in CompactionsTest. Not sure why.
{code}
.
CompactionManager.instance.interruptCompactionFor(Collections.singleton(metadata));
while (CompactionManager.instance.isCompacting(metadata))
FBUtilities.sleep(100);
assert data.getCompacting().isEmpty();
{code}
Allow automatic cleanup after gc_grace
--
Key: CASSANDRA-5051
URL: https://issues.apache.org/jira/browse/CASSANDRA-5051
Project: Cassandra
Issue Type: New Feature
Components: Core
Reporter: Brandon Williams
Assignee: Vijay
Labels: vnodes
Fix For: 2.0
Attachments: 0001-CASSANDRA-5051.patch, 3430-v3.txt
When using vnodes, after adding a new node you have to run cleanup on all the
machines, because you don't know which are affected and chances are it was
most if not all of them. As an alternative to this intensive process, we
could allow cleanup during compaction if the data is older than gc_grace (or
perhaps some other time period since people tend to use gc_grace hacks to get
rid of tombstones.)
--
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[jira] [Updated] (CASSANDRA-3430) Break Big Compaction Lock apart
[
https://issues.apache.org/jira/browse/CASSANDRA-3430?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Jonathan Ellis updated CASSANDRA-3430:
--
Attachment: 3430-v3.txt
v3 adds an extra assert that is failing in CompactionsTest. Not sure why.
{code}
.
CompactionManager.instance.interruptCompactionFor(Collections.singleton(metadata));
while (CompactionManager.instance.isCompacting(metadata))
FBUtilities.sleep(100);
assert data.getCompacting().isEmpty();
{code}
Break Big Compaction Lock apart
---
Key: CASSANDRA-3430
URL: https://issues.apache.org/jira/browse/CASSANDRA-3430
Project: Cassandra
Issue Type: Improvement
Components: Core
Reporter: Jonathan Ellis
Assignee: Jonathan Ellis
Priority: Minor
Labels: compaction
Fix For: 2.0
Attachments: 3430-1.0.txt, 3430-1.1.txt, 3430-v2.txt, 3430-v3.txt
--
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[jira] [Updated] (CASSANDRA-5051) Allow automatic cleanup after gc_grace
[ https://issues.apache.org/jira/browse/CASSANDRA-5051?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Jonathan Ellis updated CASSANDRA-5051: -- Attachment: (was: 3430-v3.txt) Allow automatic cleanup after gc_grace -- Key: CASSANDRA-5051 URL: https://issues.apache.org/jira/browse/CASSANDRA-5051 Project: Cassandra Issue Type: New Feature Components: Core Reporter: Brandon Williams Assignee: Vijay Labels: vnodes Fix For: 2.0 Attachments: 0001-CASSANDRA-5051.patch When using vnodes, after adding a new node you have to run cleanup on all the machines, because you don't know which are affected and chances are it was most if not all of them. As an alternative to this intensive process, we could allow cleanup during compaction if the data is older than gc_grace (or perhaps some other time period since people tend to use gc_grace hacks to get rid of tombstones.) -- This message is automatically generated by JIRA. If you think it was sent incorrectly, please contact your JIRA administrators For more information on JIRA, see: http://www.atlassian.com/software/jira
[jira] [Commented] (CASSANDRA-4131) Integrate Hive support to be in core cassandra
[ https://issues.apache.org/jira/browse/CASSANDRA-4131?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=13583263#comment-13583263 ] Chris Romary commented on CASSANDRA-4131: - Wondering about the status of Cassandra/Hive integration... is it a 'left-for-dead external shim' or something that's still actively being worked on? None of the githubs mentioned above have commits in the last 10 months or so. What is the status of Hive/Cassandra 1.2? Integrate Hive support to be in core cassandra -- Key: CASSANDRA-4131 URL: https://issues.apache.org/jira/browse/CASSANDRA-4131 Project: Cassandra Issue Type: Improvement Reporter: Jeremy Hanna Assignee: Edward Capriolo Labels: hadoop, hive The standalone hive support (at https://github.com/riptano/hive) would be great to have in-tree so that people don't have to go out to github to download it and wonder if it's a left-for-dead external shim. -- This message is automatically generated by JIRA. If you think it was sent incorrectly, please contact your JIRA administrators For more information on JIRA, see: http://www.atlassian.com/software/jira
[jira] [Comment Edited] (CASSANDRA-5271) Create tool to drop sstables to level 0
[ https://issues.apache.org/jira/browse/CASSANDRA-5271?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=13583351#comment-13583351 ] Marcus Eriksson edited comment on CASSANDRA-5271 at 2/21/13 4:55 PM: - v2 also contains debian packaging i added sstablemetadata as well was (Author: krummas): debian packaging Create tool to drop sstables to level 0 --- Key: CASSANDRA-5271 URL: https://issues.apache.org/jira/browse/CASSANDRA-5271 Project: Cassandra Issue Type: Improvement Reporter: Marcus Eriksson Assignee: Marcus Eriksson Priority: Trivial Labels: tools Fix For: 2.0 Attachments: 0001-Add-tool-to-drop-sstables-back-to-level-0.patch, 0001-Add-tool-to-drop-sstables-back-to-level-0-v2.patch after CASSANDRA-4872 we need a way to reset all sstables to level 0, previously we did this by removing the .json file from the data-directory. -- This message is automatically generated by JIRA. If you think it was sent incorrectly, please contact your JIRA administrators For more information on JIRA, see: http://www.atlassian.com/software/jira
[jira] [Updated] (CASSANDRA-5271) Create tool to drop sstables to level 0
[ https://issues.apache.org/jira/browse/CASSANDRA-5271?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Marcus Eriksson updated CASSANDRA-5271: --- Attachment: 0001-Add-tool-to-drop-sstables-back-to-level-0-v2.patch debian packaging Create tool to drop sstables to level 0 --- Key: CASSANDRA-5271 URL: https://issues.apache.org/jira/browse/CASSANDRA-5271 Project: Cassandra Issue Type: Improvement Reporter: Marcus Eriksson Assignee: Marcus Eriksson Priority: Trivial Labels: tools Fix For: 2.0 Attachments: 0001-Add-tool-to-drop-sstables-back-to-level-0.patch, 0001-Add-tool-to-drop-sstables-back-to-level-0-v2.patch after CASSANDRA-4872 we need a way to reset all sstables to level 0, previously we did this by removing the .json file from the data-directory. -- This message is automatically generated by JIRA. If you think it was sent incorrectly, please contact your JIRA administrators For more information on JIRA, see: http://www.atlassian.com/software/jira
[jira] [Commented] (CASSANDRA-2699) continuous incremental anti-entropy
[
https://issues.apache.org/jira/browse/CASSANDRA-2699?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=13583453#comment-13583453
]
Benjamin Coverston commented on CASSANDRA-2699:
---
From CASSANDRA-4482
{quote}
Instead, we maintain a Merkle Tree (MT) in memory and update it with every
single column insert in ColumnFamilyStore.apply(). We use
column.updateDigest(digest) on all the changes in order to create a hash per
column update and then XOR this hash with the existing one in the Merkle Tree
bucket for the corresponding row.
This Merkle Tree is created with the column family (one per range), initialized
with zeros, and persisted to disk with regular snapshots.
The commutative properties of XOR make it possible to update the MT
incrementally without having to read on write.
{quote}
I'm pretty sure this means that we should be able to XOR the buckets together
from pre-computed merkle tree SSTable components.
We could just create these on flush, merge them on compaction, then validation
compaction is just a read, MT components and merge.
continuous incremental anti-entropy
---
Key: CASSANDRA-2699
URL: https://issues.apache.org/jira/browse/CASSANDRA-2699
Project: Cassandra
Issue Type: Improvement
Reporter: Peter Schuller
Assignee: Peter Schuller
Currently, repair works by periodically running bulk jobs that (1)
performs a validating compaction building up an in-memory merkle tree,
and (2) streaming ring segments as needed according to differences
indicated by the merkle tree.
There are some disadvantages to this approach:
* There is a trade-off between memory usage and the precision of the
merkle tree. Less precision means more data streamed relative to
what is strictly required.
* Repair is a periodic bulk process that runs for a significant
period and, although possibly rate limited as compaction (if 0.8 or
backported throttling patch applied), is a divergence in terms of
performance characteristics from normal operation of the cluster.
* The impact of imprecision can be huge on a workload dominated by I/O
and with cache locality being critical, since you will suddenly
transfers lots of data to the target node.
I propose a more incremental process whereby anti-entropy is
incremental and continuous over time. In order to avoid being
seek-bound one still wants to do work in some form of bursty fashion,
but the amount of data processed at a time could be sufficiently small
that the impact on the cluster feels a lot more continuous, and that
the page cache allows us to avoid re-reading differing data twice.
Consider a process whereby a node is constantly performing a per-CF
repair operation for each CF. The current state of the repair process
is defined by:
* A starting timestamp of the current iteration through the token
range the node is responsible for.
* A finger indicating the current position along the token ring to
which iteration has completed.
This information, other than being in-memory, could periodically (every
few minutes or something) be stored persistently on disk.
The finger advances by the node selecting the next small bit of the
ring and doing whatever merkling/hashing/checksumming is necessary on
that small part, and then asking neighbors to do the same, and
arranging for neighbors to send the node data for mismatching
ranges. The data would be sent either by way of mutations like with
read repair, or by streaming sstables. But it would be small amounts
of data that will act roughly the same as regular writes for the
perspective of compaction.
Some nice properties of this approach:
* It's always on; no periodic sudden effects on cluster performance.
* Restarting nodes never cancels or breaks anti-entropy.
* Huge compactions of entire CF:s never clog up the compaction queue
(not necessarily a non-issue even with concurrent compactions in
0.8).
* Because we're always operating on small chunks, there is never the
same kind of trade-off for memory use. A merkel tree or similar
could be calculated at a very detailed level potentially. Although
the precision from the perspective of reading from disk would likely
not matter much if we are in page cache anyway, very high precision
could be *very* useful when doing anti-entropy across data centers
on slow links.
There are devils in details, like how to select an appropriate ring
segment given that you don't have knowledge of the data density on
other nodes. But I feel that the overall idea/process seems very
promising.
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[jira] [Comment Edited] (CASSANDRA-2699) continuous incremental anti-entropy
[
https://issues.apache.org/jira/browse/CASSANDRA-2699?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=13583453#comment-13583453
]
Benjamin Coverston edited comment on CASSANDRA-2699 at 2/21/13 7:19 PM:
From CASSANDRA-4482
{quote}
Instead, we maintain a Merkle Tree (MT) in memory and update it with every
single column insert in ColumnFamilyStore.apply(). We use
column.updateDigest(digest) on all the changes in order to create a hash per
column update and then XOR this hash with the existing one in the Merkle Tree
bucket for the corresponding row.
This Merkle Tree is created with the column family (one per range), initialized
with zeros, and persisted to disk with regular snapshots.
The commutative properties of XOR make it possible to update the MT
incrementally without having to read on write.
{quote}
I'm pretty sure this means that we should be able to XOR the buckets together
from pre-computed merkle tree SSTable components.
We could just create these on flush, merge them on compaction, then validation
compaction is just a read of MT components and merge.
was (Author: bcoverston):
From CASSANDRA-4482
{quote}
Instead, we maintain a Merkle Tree (MT) in memory and update it with every
single column insert in ColumnFamilyStore.apply(). We use
column.updateDigest(digest) on all the changes in order to create a hash per
column update and then XOR this hash with the existing one in the Merkle Tree
bucket for the corresponding row.
This Merkle Tree is created with the column family (one per range), initialized
with zeros, and persisted to disk with regular snapshots.
The commutative properties of XOR make it possible to update the MT
incrementally without having to read on write.
{quote}
I'm pretty sure this means that we should be able to XOR the buckets together
from pre-computed merkle tree SSTable components.
We could just create these on flush, merge them on compaction, then validation
compaction is just a read, MT components and merge.
continuous incremental anti-entropy
---
Key: CASSANDRA-2699
URL: https://issues.apache.org/jira/browse/CASSANDRA-2699
Project: Cassandra
Issue Type: Improvement
Reporter: Peter Schuller
Assignee: Peter Schuller
Currently, repair works by periodically running bulk jobs that (1)
performs a validating compaction building up an in-memory merkle tree,
and (2) streaming ring segments as needed according to differences
indicated by the merkle tree.
There are some disadvantages to this approach:
* There is a trade-off between memory usage and the precision of the
merkle tree. Less precision means more data streamed relative to
what is strictly required.
* Repair is a periodic bulk process that runs for a significant
period and, although possibly rate limited as compaction (if 0.8 or
backported throttling patch applied), is a divergence in terms of
performance characteristics from normal operation of the cluster.
* The impact of imprecision can be huge on a workload dominated by I/O
and with cache locality being critical, since you will suddenly
transfers lots of data to the target node.
I propose a more incremental process whereby anti-entropy is
incremental and continuous over time. In order to avoid being
seek-bound one still wants to do work in some form of bursty fashion,
but the amount of data processed at a time could be sufficiently small
that the impact on the cluster feels a lot more continuous, and that
the page cache allows us to avoid re-reading differing data twice.
Consider a process whereby a node is constantly performing a per-CF
repair operation for each CF. The current state of the repair process
is defined by:
* A starting timestamp of the current iteration through the token
range the node is responsible for.
* A finger indicating the current position along the token ring to
which iteration has completed.
This information, other than being in-memory, could periodically (every
few minutes or something) be stored persistently on disk.
The finger advances by the node selecting the next small bit of the
ring and doing whatever merkling/hashing/checksumming is necessary on
that small part, and then asking neighbors to do the same, and
arranging for neighbors to send the node data for mismatching
ranges. The data would be sent either by way of mutations like with
read repair, or by streaming sstables. But it would be small amounts
of data that will act roughly the same as regular writes for the
perspective of compaction.
Some nice properties of this approach:
* It's always on; no periodic sudden effects on cluster performance.
* Restarting nodes never cancels or breaks anti-entropy.
* Huge compactions
[Cassandra Wiki] Trivial Update of ChastityM by ChastityM
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[jira] [Created] (CASSANDRA-5279) Provide a nodetool command to close stream sessions
Ahmed Bashir created CASSANDRA-5279: --- Summary: Provide a nodetool command to close stream sessions Key: CASSANDRA-5279 URL: https://issues.apache.org/jira/browse/CASSANDRA-5279 Project: Cassandra Issue Type: Improvement Components: Core, Tools Affects Versions: 1.1.9 Reporter: Ahmed Bashir It would be quite useful to be able to close stream sessions (derived from AbstractStreamSession) via nodetool. This could be done in total or by session ID (all stream sessions have an ID). Stream sessions can be long-running, cause load on the network, send a very large amount of data to endpoints, and trigger large amount of pending compaction tasks. Just like we make it possible to cancel compaction, it is very useful to be able to close these sessions via nodetool (close() is if such sessions are affecting cluster stability (which they can) -- This message is automatically generated by JIRA. If you think it was sent incorrectly, please contact your JIRA administrators For more information on JIRA, see: http://www.atlassian.com/software/jira
[Cassandra Wiki] Trivial Update of MaxineVVY by MaxineVVY
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[Cassandra Wiki] Trivial Update of EllenBeat by EllenBeat
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[Cassandra Wiki] Trivial Update of BrandyOPT by BrandyOPT
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[Cassandra Wiki] Trivial Update of Ethan73G by Ethan73G
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