[jira] [Commented] (CASSANDRA-15397) IntervalTree performance comparison with Linear Walk and Binary Search based Elimination.
[
https://issues.apache.org/jira/browse/CASSANDRA-15397?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17055108#comment-17055108
]
Chandrasekhar Thumuluru commented on CASSANDRA-15397:
-
{quote}
I'm not sure if assuming long will be a good idea.
{quote}
I meant in the context of generics and about the performance.
I'll make necessary changes, compare it again and post the results.
> IntervalTree performance comparison with Linear Walk and Binary Search based
> Elimination.
> --
>
> Key: CASSANDRA-15397
> URL: https://issues.apache.org/jira/browse/CASSANDRA-15397
> Project: Cassandra
> Issue Type: Improvement
> Components: Local/SSTable
>Reporter: Chandrasekhar Thumuluru
>Assignee: Chandrasekhar Thumuluru
>Priority: Low
> Labels: pull-request-available
> Attachments: 90p_100k_sstables_with_1000_searches.png,
> 90p_1million_sstables_with_1000_searches.png,
> 90p_250k_sstables_with_1000_searches.png,
> 90p_500k_sstables_with_1000_searches.png,
> 90p_750k_sstables_with_1000_searches.png,
> 95p_1_SSTable_with_5000_Searches.png,
> 95p_100k_sstables_with_1000_searches.png,
> 95p_15000_SSTable_with_5000_Searches.png,
> 95p_1million_sstables_with_1000_searches.png,
> 95p_2_SSTable_with_5000_Searches.png,
> 95p_25000_SSTable_with_5000_Searches.png,
> 95p_250k_sstables_with_1000_searches.png,
> 95p_3_SSTable_with_5000_Searches.png,
> 95p_5000_SSTable_with_5000_Searches.png,
> 95p_500k_sstables_with_1000_searches.png,
> 95p_750k_sstables_with_1000_searches.png,
> 99p_1_SSTable_with_5000_Searches.png,
> 99p_100k_sstables_with_1000_searches.png,
> 99p_15000_SSTable_with_5000_Searches.png,
> 99p_1million_sstables_with_1000_searches.png,
> 99p_2_SSTable_with_5000_Searches.png,
> 99p_25000_SSTable_with_5000_Searches.png,
> 99p_250k_sstables_with_1000_searches.png,
> 99p_3_SSTable_with_5000_Searches.png,
> 99p_5000_SSTable_with_5000_Searches.png,
> 99p_500k_sstables_with_1000_searches.png,
> 99p_750k_sstables_with_1000_searches.png, IntervalList.java,
> IntervalListWithElimination.java, IntervalTreeSimplified.java,
> Mean_1_SSTable_with_5000_Searches.png,
> Mean_100k_sstables_with_1000_searches.png,
> Mean_15000_SSTable_with_5000_Searches.png,
> Mean_1million_sstables_with_1000_searches.png,
> Mean_2_SSTable_with_5000_Searches.png,
> Mean_25000_SSTable_with_5000_Searches.png,
> Mean_250k_sstables_with_1000_searches.png,
> Mean_3_SSTable_with_5000_Searches.png,
> Mean_5000_SSTable_with_5000_Searches.png,
> Mean_500k_sstables_with_1000_searches.png,
> Mean_750k_sstables_with_1000_searches.png, TESTS-TestSuites.xml.lz4,
> replace_intervaltree_with_intervallist.patch
>
> Time Spent: 0.5h
> Remaining Estimate: 0h
>
> Cassandra uses IntervalTrees to identify the SSTables that overlap with
> search interval. In Cassandra, IntervalTrees are not mutated. They are
> recreated each time a mutation is required. This can be an issue during
> repairs. In fact we noticed such issues during repair.
> Since lists are cache friendly compared to linked lists and trees, I decided
> to compare the search performance with:
> * Linear Walk.
> * Elimination using Binary Search (idea is to eliminate intervals using start
> and end points of search interval).
> Based on the tests I ran, I noticed Binary Search based elimination almost
> always performs similar to IntervalTree or out performs IntervalTree based
> search. The cost of IntervalTree construction is also substantial and
> produces lot of garbage during repairs.
> I ran the tests using random intervals to build the tree/lists and another
> randomly generated search interval with 5000 iterations. I'm attaching all
> the relevant graphs. The x-axis in the graphs is the search interval
> coverage. 10p means the search interval covered 10% of the intervals. The
> y-axis is the time the search took in nanos.
> PS:
> # For the purpose of test, I simplified the IntervalTree by removing the data
> portion of the interval. Modified the template version (Java generics) to a
> specialized version.
> # I used the code from Cassandra version _3.11_.
> # Time in the graph is in nanos.
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[jira] [Commented] (CASSANDRA-15397) IntervalTree performance comparison with Linear Walk and Binary Search based Elimination.
[
https://issues.apache.org/jira/browse/CASSANDRA-15397?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17054782#comment-17054782
]
Benedict Elliott Smith commented on CASSANDRA-15397:
bq. I couldn't do so since the code uses a generic that's comparable
The {{IntervalTree}} is used in precisely one place in the codebase, so it
would be possible to hardcode to this use case for improved performance.
bq. I'm not sure if assuming long will be a good idea
I would be very surprised if it is not significantly faster.
> IntervalTree performance comparison with Linear Walk and Binary Search based
> Elimination.
> --
>
> Key: CASSANDRA-15397
> URL: https://issues.apache.org/jira/browse/CASSANDRA-15397
> Project: Cassandra
> Issue Type: Improvement
> Components: Local/SSTable
>Reporter: Chandrasekhar Thumuluru
>Assignee: Chandrasekhar Thumuluru
>Priority: Low
> Labels: pull-request-available
> Attachments: 90p_100k_sstables_with_1000_searches.png,
> 90p_1million_sstables_with_1000_searches.png,
> 90p_250k_sstables_with_1000_searches.png,
> 90p_500k_sstables_with_1000_searches.png,
> 90p_750k_sstables_with_1000_searches.png,
> 95p_1_SSTable_with_5000_Searches.png,
> 95p_100k_sstables_with_1000_searches.png,
> 95p_15000_SSTable_with_5000_Searches.png,
> 95p_1million_sstables_with_1000_searches.png,
> 95p_2_SSTable_with_5000_Searches.png,
> 95p_25000_SSTable_with_5000_Searches.png,
> 95p_250k_sstables_with_1000_searches.png,
> 95p_3_SSTable_with_5000_Searches.png,
> 95p_5000_SSTable_with_5000_Searches.png,
> 95p_500k_sstables_with_1000_searches.png,
> 95p_750k_sstables_with_1000_searches.png,
> 99p_1_SSTable_with_5000_Searches.png,
> 99p_100k_sstables_with_1000_searches.png,
> 99p_15000_SSTable_with_5000_Searches.png,
> 99p_1million_sstables_with_1000_searches.png,
> 99p_2_SSTable_with_5000_Searches.png,
> 99p_25000_SSTable_with_5000_Searches.png,
> 99p_250k_sstables_with_1000_searches.png,
> 99p_3_SSTable_with_5000_Searches.png,
> 99p_5000_SSTable_with_5000_Searches.png,
> 99p_500k_sstables_with_1000_searches.png,
> 99p_750k_sstables_with_1000_searches.png, IntervalList.java,
> IntervalListWithElimination.java, IntervalTreeSimplified.java,
> Mean_1_SSTable_with_5000_Searches.png,
> Mean_100k_sstables_with_1000_searches.png,
> Mean_15000_SSTable_with_5000_Searches.png,
> Mean_1million_sstables_with_1000_searches.png,
> Mean_2_SSTable_with_5000_Searches.png,
> Mean_25000_SSTable_with_5000_Searches.png,
> Mean_250k_sstables_with_1000_searches.png,
> Mean_3_SSTable_with_5000_Searches.png,
> Mean_5000_SSTable_with_5000_Searches.png,
> Mean_500k_sstables_with_1000_searches.png,
> Mean_750k_sstables_with_1000_searches.png, TESTS-TestSuites.xml.lz4,
> replace_intervaltree_with_intervallist.patch
>
> Time Spent: 0.5h
> Remaining Estimate: 0h
>
> Cassandra uses IntervalTrees to identify the SSTables that overlap with
> search interval. In Cassandra, IntervalTrees are not mutated. They are
> recreated each time a mutation is required. This can be an issue during
> repairs. In fact we noticed such issues during repair.
> Since lists are cache friendly compared to linked lists and trees, I decided
> to compare the search performance with:
> * Linear Walk.
> * Elimination using Binary Search (idea is to eliminate intervals using start
> and end points of search interval).
> Based on the tests I ran, I noticed Binary Search based elimination almost
> always performs similar to IntervalTree or out performs IntervalTree based
> search. The cost of IntervalTree construction is also substantial and
> produces lot of garbage during repairs.
> I ran the tests using random intervals to build the tree/lists and another
> randomly generated search interval with 5000 iterations. I'm attaching all
> the relevant graphs. The x-axis in the graphs is the search interval
> coverage. 10p means the search interval covered 10% of the intervals. The
> y-axis is the time the search took in nanos.
> PS:
> # For the purpose of test, I simplified the IntervalTree by removing the data
> portion of the interval. Modified the template version (Java generics) to a
> specialized version.
> # I used the code from Cassandra version _3.11_.
> # Time in the graph is in nanos.
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[jira] [Commented] (CASSANDRA-15397) IntervalTree performance comparison with Linear Walk and Binary Search based Elimination.
[ https://issues.apache.org/jira/browse/CASSANDRA-15397?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17054593#comment-17054593 ] Chandrasekhar Thumuluru commented on CASSANDRA-15397: - [~benedict] — Sorry for the delayed update on this ticket. I made necessary changes to IntervalList implementation based on your feedback. The previous submission was moved to IntervalList2. I also refactored the other code to use the IntervalList instead of IntervalTree. You suggested to use 4 long[] arrays but I couldn't do so since the code uses a generic that's comparable. I'm not sure if assuming long will be a good idea. Instead I changed the implementation to use two lists one to store the interval points and the other to store the data. Based on my performance comparison, I see the previous submission performs better. It could be partly because the previous implementation packs all the relevant items together. I also added the performance comparison for 100k, 250k, 500k, 750k and 1 million SSTables based on 1000 searches. Based on my analysis, the performance of Interval list with (250k and above) huge number of SSTables falls behind Interval tree by a small margin but the trade-off is less construction cost and less garbage creation during construction. Please take a look and let me know what you think. > IntervalTree performance comparison with Linear Walk and Binary Search based > Elimination. > -- > > Key: CASSANDRA-15397 > URL: https://issues.apache.org/jira/browse/CASSANDRA-15397 > Project: Cassandra > Issue Type: Improvement > Components: Local/SSTable >Reporter: Chandrasekhar Thumuluru >Assignee: Chandrasekhar Thumuluru >Priority: Low > Labels: pull-request-available > Attachments: 90p_100k_sstables_with_1000_searches.png, > 90p_1million_sstables_with_1000_searches.png, > 90p_250k_sstables_with_1000_searches.png, > 90p_500k_sstables_with_1000_searches.png, > 90p_750k_sstables_with_1000_searches.png, > 95p_1_SSTable_with_5000_Searches.png, > 95p_100k_sstables_with_1000_searches.png, > 95p_15000_SSTable_with_5000_Searches.png, > 95p_1million_sstables_with_1000_searches.png, > 95p_2_SSTable_with_5000_Searches.png, > 95p_25000_SSTable_with_5000_Searches.png, > 95p_250k_sstables_with_1000_searches.png, > 95p_3_SSTable_with_5000_Searches.png, > 95p_5000_SSTable_with_5000_Searches.png, > 95p_500k_sstables_with_1000_searches.png, > 95p_750k_sstables_with_1000_searches.png, > 99p_1_SSTable_with_5000_Searches.png, > 99p_100k_sstables_with_1000_searches.png, > 99p_15000_SSTable_with_5000_Searches.png, > 99p_1million_sstables_with_1000_searches.png, > 99p_2_SSTable_with_5000_Searches.png, > 99p_25000_SSTable_with_5000_Searches.png, > 99p_250k_sstables_with_1000_searches.png, > 99p_3_SSTable_with_5000_Searches.png, > 99p_5000_SSTable_with_5000_Searches.png, > 99p_500k_sstables_with_1000_searches.png, > 99p_750k_sstables_with_1000_searches.png, IntervalList.java, > IntervalListWithElimination.java, IntervalTreeSimplified.java, > Mean_1_SSTable_with_5000_Searches.png, > Mean_100k_sstables_with_1000_searches.png, > Mean_15000_SSTable_with_5000_Searches.png, > Mean_1million_sstables_with_1000_searches.png, > Mean_2_SSTable_with_5000_Searches.png, > Mean_25000_SSTable_with_5000_Searches.png, > Mean_250k_sstables_with_1000_searches.png, > Mean_3_SSTable_with_5000_Searches.png, > Mean_5000_SSTable_with_5000_Searches.png, > Mean_500k_sstables_with_1000_searches.png, > Mean_750k_sstables_with_1000_searches.png, TESTS-TestSuites.xml.lz4, > replace_intervaltree_with_intervallist.patch > > Time Spent: 0.5h > Remaining Estimate: 0h > > Cassandra uses IntervalTrees to identify the SSTables that overlap with > search interval. In Cassandra, IntervalTrees are not mutated. They are > recreated each time a mutation is required. This can be an issue during > repairs. In fact we noticed such issues during repair. > Since lists are cache friendly compared to linked lists and trees, I decided > to compare the search performance with: > * Linear Walk. > * Elimination using Binary Search (idea is to eliminate intervals using start > and end points of search interval). > Based on the tests I ran, I noticed Binary Search based elimination almost > always performs similar to IntervalTree or out performs IntervalTree based > search. The cost of IntervalTree construction is also substantial and > produces lot of garbage during repairs. > I ran the tests using random intervals to build the tree/lists and another > randomly generated search interval with 5000 iterations. I'm attaching all > the relevant graphs. The x-axis in the graphs is the
[jira] [Commented] (CASSANDRA-15397) IntervalTree performance comparison with Linear Walk and Binary Search based Elimination.
[ https://issues.apache.org/jira/browse/CASSANDRA-15397?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17001037#comment-17001037 ] Chandrasekhar Thumuluru commented on CASSANDRA-15397: - [~benedict] — Thanks for your inputs. * I'll rename the class. I intentionally didn't do it in the first version of PR so it looks less distracting. * I'll definitely do the performance comparison with million+ SSTables. Please note, my previous tests were not produced from read SSTables. The SSTable metadata was generated with random distributions. You can refer to the test files attached and let me know if you have any suggestions. I guess not using the real SSTables is fair to compare the performance of IntervalTree? * I definitely share your concern on potential slowness due to linear scan, but I shared some code reference in this [doc|https://docs.google.com/document/d/1vwo9ArZbtgWUwJcvZGes_69YVh4yiP9c7NQFgI0iynQ/edit?usp=sharing] which makes me believe we are still good. Let me know your thought on that too. * I'm willing to try the improvement proposed to the algorithm. I'll talk to my team to gather context around what you are suggesting and get back to you if I've any questions. * I'm definitely willing to try the proposed changes and don't mind even it the assumption turns out to be wrong. > IntervalTree performance comparison with Linear Walk and Binary Search based > Elimination. > -- > > Key: CASSANDRA-15397 > URL: https://issues.apache.org/jira/browse/CASSANDRA-15397 > Project: Cassandra > Issue Type: Improvement > Components: Local/SSTable >Reporter: Chandrasekhar Thumuluru >Assignee: Chandrasekhar Thumuluru >Priority: Low > Labels: pull-request-available > Attachments: 95p_1_SSTable_with_5000_Searches.png, > 95p_15000_SSTable_with_5000_Searches.png, > 95p_2_SSTable_with_5000_Searches.png, > 95p_25000_SSTable_with_5000_Searches.png, > 95p_3_SSTable_with_5000_Searches.png, > 95p_5000_SSTable_with_5000_Searches.png, > 99p_1_SSTable_with_5000_Searches.png, > 99p_15000_SSTable_with_5000_Searches.png, > 99p_2_SSTable_with_5000_Searches.png, > 99p_25000_SSTable_with_5000_Searches.png, > 99p_3_SSTable_with_5000_Searches.png, > 99p_5000_SSTable_with_5000_Searches.png, IntervalList.java, > IntervalListWithElimination.java, IntervalTreeSimplified.java, > Mean_1_SSTable_with_5000_Searches.png, > Mean_15000_SSTable_with_5000_Searches.png, > Mean_2_SSTable_with_5000_Searches.png, > Mean_25000_SSTable_with_5000_Searches.png, > Mean_3_SSTable_with_5000_Searches.png, > Mean_5000_SSTable_with_5000_Searches.png, TESTS-TestSuites.xml.lz4, > replace_intervaltree_with_intervallist.patch > > Time Spent: 10m > Remaining Estimate: 0h > > Cassandra uses IntervalTrees to identify the SSTables that overlap with > search interval. In Cassandra, IntervalTrees are not mutated. They are > recreated each time a mutation is required. This can be an issue during > repairs. In fact we noticed such issues during repair. > Since lists are cache friendly compared to linked lists and trees, I decided > to compare the search performance with: > * Linear Walk. > * Elimination using Binary Search (idea is to eliminate intervals using start > and end points of search interval). > Based on the tests I ran, I noticed Binary Search based elimination almost > always performs similar to IntervalTree or out performs IntervalTree based > search. The cost of IntervalTree construction is also substantial and > produces lot of garbage during repairs. > I ran the tests using random intervals to build the tree/lists and another > randomly generated search interval with 5000 iterations. I'm attaching all > the relevant graphs. The x-axis in the graphs is the search interval > coverage. 10p means the search interval covered 10% of the intervals. The > y-axis is the time the search took in nanos. > PS: > # For the purpose of test, I simplified the IntervalTree by removing the data > portion of the interval. Modified the template version (Java generics) to a > specialized version. > # I used the code from Cassandra version _3.11_. > # Time in the graph is in nanos. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: commits-unsubscr...@cassandra.apache.org For additional commands, e-mail: commits-h...@cassandra.apache.org
[jira] [Commented] (CASSANDRA-15397) IntervalTree performance comparison with Linear Walk and Binary Search based Elimination.
[
https://issues.apache.org/jira/browse/CASSANDRA-15397?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17000505#comment-17000505
]
Benedict Elliott Smith commented on CASSANDRA-15397:
The code looks pretty simple and clean, though I will need to look more
carefully before we consider merging. We would want to rename the class, since
it's no longer a tree, and we would probably want to avoid the extra work of
going via streams (which looks like it would allocate O(n) extra data).
As it stands, I would probably want to see more performance comparisons,
particularly out to more outlandish numbers of sstables (at least one million),
and also for excessively skewed distributions. Since the benefits shown in your
graphs are modest in absolute terms, and the potential algorithmic harms of a
linear scan could have significant downside risk. So we need to be sure we have
properly established what that might be.
There are some potential simple improvements to this approach that would make
it more desirable: instead of maintaining two lists of interval objects, we
could maintain four {{long[]}}; two matches pairs of {{long[]}} each
representing the two current sorted lists. One would be used for binary search,
the other for the linear scan. This should dramatically improve the constant
factors, only needing to support post-filtering for e.g. {{RandomPartitioner}},
as we would only be able to filter on a prefix for those tokens > 8 bytes.
Although this approach would require slightly more involved modifications, and
a bit more verification, the win should be much more pronounced. Is this
something you'd be willing to try?
> IntervalTree performance comparison with Linear Walk and Binary Search based
> Elimination.
> --
>
> Key: CASSANDRA-15397
> URL: https://issues.apache.org/jira/browse/CASSANDRA-15397
> Project: Cassandra
> Issue Type: Improvement
> Components: Local/SSTable
>Reporter: Chandrasekhar Thumuluru
>Assignee: Chandrasekhar Thumuluru
>Priority: Low
> Labels: pull-request-available
> Attachments: 95p_1_SSTable_with_5000_Searches.png,
> 95p_15000_SSTable_with_5000_Searches.png,
> 95p_2_SSTable_with_5000_Searches.png,
> 95p_25000_SSTable_with_5000_Searches.png,
> 95p_3_SSTable_with_5000_Searches.png,
> 95p_5000_SSTable_with_5000_Searches.png,
> 99p_1_SSTable_with_5000_Searches.png,
> 99p_15000_SSTable_with_5000_Searches.png,
> 99p_2_SSTable_with_5000_Searches.png,
> 99p_25000_SSTable_with_5000_Searches.png,
> 99p_3_SSTable_with_5000_Searches.png,
> 99p_5000_SSTable_with_5000_Searches.png, IntervalList.java,
> IntervalListWithElimination.java, IntervalTreeSimplified.java,
> Mean_1_SSTable_with_5000_Searches.png,
> Mean_15000_SSTable_with_5000_Searches.png,
> Mean_2_SSTable_with_5000_Searches.png,
> Mean_25000_SSTable_with_5000_Searches.png,
> Mean_3_SSTable_with_5000_Searches.png,
> Mean_5000_SSTable_with_5000_Searches.png, TESTS-TestSuites.xml.lz4,
> replace_intervaltree_with_intervallist.patch
>
> Time Spent: 10m
> Remaining Estimate: 0h
>
> Cassandra uses IntervalTrees to identify the SSTables that overlap with
> search interval. In Cassandra, IntervalTrees are not mutated. They are
> recreated each time a mutation is required. This can be an issue during
> repairs. In fact we noticed such issues during repair.
> Since lists are cache friendly compared to linked lists and trees, I decided
> to compare the search performance with:
> * Linear Walk.
> * Elimination using Binary Search (idea is to eliminate intervals using start
> and end points of search interval).
> Based on the tests I ran, I noticed Binary Search based elimination almost
> always performs similar to IntervalTree or out performs IntervalTree based
> search. The cost of IntervalTree construction is also substantial and
> produces lot of garbage during repairs.
> I ran the tests using random intervals to build the tree/lists and another
> randomly generated search interval with 5000 iterations. I'm attaching all
> the relevant graphs. The x-axis in the graphs is the search interval
> coverage. 10p means the search interval covered 10% of the intervals. The
> y-axis is the time the search took in nanos.
> PS:
> # For the purpose of test, I simplified the IntervalTree by removing the data
> portion of the interval. Modified the template version (Java generics) to a
> specialized version.
> # I used the code from Cassandra version _3.11_.
> # Time in the graph is in nanos.
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[jira] [Commented] (CASSANDRA-15397) IntervalTree performance comparison with Linear Walk and Binary Search based Elimination.
[ https://issues.apache.org/jira/browse/CASSANDRA-15397?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17000219#comment-17000219 ] Chandrasekhar Thumuluru commented on CASSANDRA-15397: - [~benedict] — I posted the changes to my branch and created a [PR|https://github.com/apache/cassandra/pull/400]. Please provide your comments when you find free time. Thanks. > IntervalTree performance comparison with Linear Walk and Binary Search based > Elimination. > -- > > Key: CASSANDRA-15397 > URL: https://issues.apache.org/jira/browse/CASSANDRA-15397 > Project: Cassandra > Issue Type: Improvement > Components: Local/SSTable >Reporter: Chandrasekhar Thumuluru >Assignee: Chandrasekhar Thumuluru >Priority: Low > Labels: pull-request-available > Attachments: 95p_1_SSTable_with_5000_Searches.png, > 95p_15000_SSTable_with_5000_Searches.png, > 95p_2_SSTable_with_5000_Searches.png, > 95p_25000_SSTable_with_5000_Searches.png, > 95p_3_SSTable_with_5000_Searches.png, > 95p_5000_SSTable_with_5000_Searches.png, > 99p_1_SSTable_with_5000_Searches.png, > 99p_15000_SSTable_with_5000_Searches.png, > 99p_2_SSTable_with_5000_Searches.png, > 99p_25000_SSTable_with_5000_Searches.png, > 99p_3_SSTable_with_5000_Searches.png, > 99p_5000_SSTable_with_5000_Searches.png, IntervalList.java, > IntervalListWithElimination.java, IntervalTreeSimplified.java, > Mean_1_SSTable_with_5000_Searches.png, > Mean_15000_SSTable_with_5000_Searches.png, > Mean_2_SSTable_with_5000_Searches.png, > Mean_25000_SSTable_with_5000_Searches.png, > Mean_3_SSTable_with_5000_Searches.png, > Mean_5000_SSTable_with_5000_Searches.png, TESTS-TestSuites.xml.lz4, > replace_intervaltree_with_intervallist.patch > > Time Spent: 10m > Remaining Estimate: 0h > > Cassandra uses IntervalTrees to identify the SSTables that overlap with > search interval. In Cassandra, IntervalTrees are not mutated. They are > recreated each time a mutation is required. This can be an issue during > repairs. In fact we noticed such issues during repair. > Since lists are cache friendly compared to linked lists and trees, I decided > to compare the search performance with: > * Linear Walk. > * Elimination using Binary Search (idea is to eliminate intervals using start > and end points of search interval). > Based on the tests I ran, I noticed Binary Search based elimination almost > always performs similar to IntervalTree or out performs IntervalTree based > search. The cost of IntervalTree construction is also substantial and > produces lot of garbage during repairs. > I ran the tests using random intervals to build the tree/lists and another > randomly generated search interval with 5000 iterations. I'm attaching all > the relevant graphs. The x-axis in the graphs is the search interval > coverage. 10p means the search interval covered 10% of the intervals. The > y-axis is the time the search took in nanos. > PS: > # For the purpose of test, I simplified the IntervalTree by removing the data > portion of the interval. Modified the template version (Java generics) to a > specialized version. > # I used the code from Cassandra version _3.11_. > # Time in the graph is in nanos. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: commits-unsubscr...@cassandra.apache.org For additional commands, e-mail: commits-h...@cassandra.apache.org
[jira] [Commented] (CASSANDRA-15397) IntervalTree performance comparison with Linear Walk and Binary Search based Elimination.
[ https://issues.apache.org/jira/browse/CASSANDRA-15397?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16993458#comment-16993458 ] Benedict Elliott Smith commented on CASSANDRA-15397: Hi [~cthumuluru], sorry I'm unsure when I'll have time to take a proper look at this; I have work piling up. If you could post a branch to github with your patch applied, I will see if I can sneak in at least some initial thoughts. > IntervalTree performance comparison with Linear Walk and Binary Search based > Elimination. > -- > > Key: CASSANDRA-15397 > URL: https://issues.apache.org/jira/browse/CASSANDRA-15397 > Project: Cassandra > Issue Type: Improvement > Components: Local/SSTable >Reporter: Chandrasekhar Thumuluru >Assignee: Chandrasekhar Thumuluru >Priority: Low > Attachments: 95p_1_SSTable_with_5000_Searches.png, > 95p_15000_SSTable_with_5000_Searches.png, > 95p_2_SSTable_with_5000_Searches.png, > 95p_25000_SSTable_with_5000_Searches.png, > 95p_3_SSTable_with_5000_Searches.png, > 95p_5000_SSTable_with_5000_Searches.png, > 99p_1_SSTable_with_5000_Searches.png, > 99p_15000_SSTable_with_5000_Searches.png, > 99p_2_SSTable_with_5000_Searches.png, > 99p_25000_SSTable_with_5000_Searches.png, > 99p_3_SSTable_with_5000_Searches.png, > 99p_5000_SSTable_with_5000_Searches.png, IntervalList.java, > IntervalListWithElimination.java, IntervalTreeSimplified.java, > Mean_1_SSTable_with_5000_Searches.png, > Mean_15000_SSTable_with_5000_Searches.png, > Mean_2_SSTable_with_5000_Searches.png, > Mean_25000_SSTable_with_5000_Searches.png, > Mean_3_SSTable_with_5000_Searches.png, > Mean_5000_SSTable_with_5000_Searches.png, TESTS-TestSuites.xml.lz4, > replace_intervaltree_with_intervallist.patch > > > Cassandra uses IntervalTrees to identify the SSTables that overlap with > search interval. In Cassandra, IntervalTrees are not mutated. They are > recreated each time a mutation is required. This can be an issue during > repairs. In fact we noticed such issues during repair. > Since lists are cache friendly compared to linked lists and trees, I decided > to compare the search performance with: > * Linear Walk. > * Elimination using Binary Search (idea is to eliminate intervals using start > and end points of search interval). > Based on the tests I ran, I noticed Binary Search based elimination almost > always performs similar to IntervalTree or out performs IntervalTree based > search. The cost of IntervalTree construction is also substantial and > produces lot of garbage during repairs. > I ran the tests using random intervals to build the tree/lists and another > randomly generated search interval with 5000 iterations. I'm attaching all > the relevant graphs. The x-axis in the graphs is the search interval > coverage. 10p means the search interval covered 10% of the intervals. The > y-axis is the time the search took in nanos. > PS: > # For the purpose of test, I simplified the IntervalTree by removing the data > portion of the interval. Modified the template version (Java generics) to a > specialized version. > # I used the code from Cassandra version _3.11_. > # Time in the graph is in nanos. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: commits-unsubscr...@cassandra.apache.org For additional commands, e-mail: commits-h...@cassandra.apache.org
[jira] [Commented] (CASSANDRA-15397) IntervalTree performance comparison with Linear Walk and Binary Search based Elimination.
[ https://issues.apache.org/jira/browse/CASSANDRA-15397?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16993222#comment-16993222 ] Chandrasekhar Thumuluru commented on CASSANDRA-15397: - [~benedict] — When you get a chance, can you review the changes and let me know your feedback? > IntervalTree performance comparison with Linear Walk and Binary Search based > Elimination. > -- > > Key: CASSANDRA-15397 > URL: https://issues.apache.org/jira/browse/CASSANDRA-15397 > Project: Cassandra > Issue Type: Improvement > Components: Local/SSTable >Reporter: Chandrasekhar Thumuluru >Assignee: Chandrasekhar Thumuluru >Priority: Low > Attachments: 95p_1_SSTable_with_5000_Searches.png, > 95p_15000_SSTable_with_5000_Searches.png, > 95p_2_SSTable_with_5000_Searches.png, > 95p_25000_SSTable_with_5000_Searches.png, > 95p_3_SSTable_with_5000_Searches.png, > 95p_5000_SSTable_with_5000_Searches.png, > 99p_1_SSTable_with_5000_Searches.png, > 99p_15000_SSTable_with_5000_Searches.png, > 99p_2_SSTable_with_5000_Searches.png, > 99p_25000_SSTable_with_5000_Searches.png, > 99p_3_SSTable_with_5000_Searches.png, > 99p_5000_SSTable_with_5000_Searches.png, IntervalList.java, > IntervalListWithElimination.java, IntervalTreeSimplified.java, > Mean_1_SSTable_with_5000_Searches.png, > Mean_15000_SSTable_with_5000_Searches.png, > Mean_2_SSTable_with_5000_Searches.png, > Mean_25000_SSTable_with_5000_Searches.png, > Mean_3_SSTable_with_5000_Searches.png, > Mean_5000_SSTable_with_5000_Searches.png, TESTS-TestSuites.xml.lz4, > replace_intervaltree_with_intervallist.patch > > > Cassandra uses IntervalTrees to identify the SSTables that overlap with > search interval. In Cassandra, IntervalTrees are not mutated. They are > recreated each time a mutation is required. This can be an issue during > repairs. In fact we noticed such issues during repair. > Since lists are cache friendly compared to linked lists and trees, I decided > to compare the search performance with: > * Linear Walk. > * Elimination using Binary Search (idea is to eliminate intervals using start > and end points of search interval). > Based on the tests I ran, I noticed Binary Search based elimination almost > always performs similar to IntervalTree or out performs IntervalTree based > search. The cost of IntervalTree construction is also substantial and > produces lot of garbage during repairs. > I ran the tests using random intervals to build the tree/lists and another > randomly generated search interval with 5000 iterations. I'm attaching all > the relevant graphs. The x-axis in the graphs is the search interval > coverage. 10p means the search interval covered 10% of the intervals. The > y-axis is the time the search took in nanos. > PS: > # For the purpose of test, I simplified the IntervalTree by removing the data > portion of the interval. Modified the template version (Java generics) to a > specialized version. > # I used the code from Cassandra version _3.11_. > # Time in the graph is in nanos. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: commits-unsubscr...@cassandra.apache.org For additional commands, e-mail: commits-h...@cassandra.apache.org
[jira] [Commented] (CASSANDRA-15397) IntervalTree performance comparison with Linear Walk and Binary Search based Elimination.
[ https://issues.apache.org/jira/browse/CASSANDRA-15397?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16974574#comment-16974574 ] Chandrasekhar Thumuluru commented on CASSANDRA-15397: - [~benedict] — * Attached the patch file with my changes [^replace_intervaltree_with_intervallist.patch]. I used trunk for the patch. * Attached the unit test run results [^TESTS-TestSuites.xml.lz4] . * [Link|https://docs.google.com/document/d/1vwo9ArZbtgWUwJcvZGes_69YVh4yiP9c7NQFgI0iynQ/edit?usp=sharing] to google doc with some details about the proposed algorithm. Please review the changes when you get a chance and let me know your feedback. > IntervalTree performance comparison with Linear Walk and Binary Search based > Elimination. > -- > > Key: CASSANDRA-15397 > URL: https://issues.apache.org/jira/browse/CASSANDRA-15397 > Project: Cassandra > Issue Type: Improvement > Components: Local/SSTable >Reporter: Chandrasekhar Thumuluru >Assignee: Chandrasekhar Thumuluru >Priority: Low > Attachments: 95p_1_SSTable_with_5000_Searches.png, > 95p_15000_SSTable_with_5000_Searches.png, > 95p_2_SSTable_with_5000_Searches.png, > 95p_25000_SSTable_with_5000_Searches.png, > 95p_3_SSTable_with_5000_Searches.png, > 95p_5000_SSTable_with_5000_Searches.png, > 99p_1_SSTable_with_5000_Searches.png, > 99p_15000_SSTable_with_5000_Searches.png, > 99p_2_SSTable_with_5000_Searches.png, > 99p_25000_SSTable_with_5000_Searches.png, > 99p_3_SSTable_with_5000_Searches.png, > 99p_5000_SSTable_with_5000_Searches.png, IntervalList.java, > IntervalListWithElimination.java, IntervalTreeSimplified.java, > Mean_1_SSTable_with_5000_Searches.png, > Mean_15000_SSTable_with_5000_Searches.png, > Mean_2_SSTable_with_5000_Searches.png, > Mean_25000_SSTable_with_5000_Searches.png, > Mean_3_SSTable_with_5000_Searches.png, > Mean_5000_SSTable_with_5000_Searches.png, TESTS-TestSuites.xml.lz4, > replace_intervaltree_with_intervallist.patch > > > Cassandra uses IntervalTrees to identify the SSTables that overlap with > search interval. In Cassandra, IntervalTrees are not mutated. They are > recreated each time a mutation is required. This can be an issue during > repairs. In fact we noticed such issues during repair. > Since lists are cache friendly compared to linked lists and trees, I decided > to compare the search performance with: > * Linear Walk. > * Elimination using Binary Search (idea is to eliminate intervals using start > and end points of search interval). > Based on the tests I ran, I noticed Binary Search based elimination almost > always performs similar to IntervalTree or out performs IntervalTree based > search. The cost of IntervalTree construction is also substantial and > produces lot of garbage during repairs. > I ran the tests using random intervals to build the tree/lists and another > randomly generated search interval with 5000 iterations. I'm attaching all > the relevant graphs. The x-axis in the graphs is the search interval > coverage. 10p means the search interval covered 10% of the intervals. The > y-axis is the time the search took in nanos. > PS: > # For the purpose of test, I simplified the IntervalTree by removing the data > portion of the interval. Modified the template version (Java generics) to a > specialized version. > # I used the code from Cassandra version _3.11_. > # Time in the graph is in nanos. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: commits-unsubscr...@cassandra.apache.org For additional commands, e-mail: commits-h...@cassandra.apache.org
[jira] [Commented] (CASSANDRA-15397) IntervalTree performance comparison with Linear Walk and Binary Search based Elimination.
[
https://issues.apache.org/jira/browse/CASSANDRA-15397?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16967802#comment-16967802
]
Benedict Elliott Smith commented on CASSANDRA-15397:
It's true that the costs of constructing a new {{IntervalTree}} are
non-trivial, and it isn't necessarily reasonable to assume that it occurs
sufficiently infrequent to not matter eitherr. The lookup cost is not a
terribly significant cost to worry about, but reducing construction cost could
be a win for some users, and this modification might improve that. If we
really cared about construction costs, it would be possible to introduce an
immutable but updatable {{IntervalTree}} instead of building it from scratch
every time. But that's likely to be a lot more work.
It's worth noting that the {{OverlapIterator}} we already have in tree is very
similar in principle, I assume (but with different assumptions about usage),
though I haven't had a chance to look at your proposal yet.
> IntervalTree performance comparison with Linear Walk and Binary Search based
> Elimination.
> --
>
> Key: CASSANDRA-15397
> URL: https://issues.apache.org/jira/browse/CASSANDRA-15397
> Project: Cassandra
> Issue Type: Improvement
> Components: Local/SSTable
>Reporter: Chandrasekhar Thumuluru
>Assignee: Chandrasekhar Thumuluru
>Priority: Low
> Attachments: 95p_1_SSTable_with_5000_Searches.png,
> 95p_15000_SSTable_with_5000_Searches.png,
> 95p_2_SSTable_with_5000_Searches.png,
> 95p_25000_SSTable_with_5000_Searches.png,
> 95p_3_SSTable_with_5000_Searches.png,
> 95p_5000_SSTable_with_5000_Searches.png,
> 99p_1_SSTable_with_5000_Searches.png,
> 99p_15000_SSTable_with_5000_Searches.png,
> 99p_2_SSTable_with_5000_Searches.png,
> 99p_25000_SSTable_with_5000_Searches.png,
> 99p_3_SSTable_with_5000_Searches.png,
> 99p_5000_SSTable_with_5000_Searches.png, IntervalList.java,
> IntervalListWithElimination.java, IntervalTreeSimplified.java,
> Mean_1_SSTable_with_5000_Searches.png,
> Mean_15000_SSTable_with_5000_Searches.png,
> Mean_2_SSTable_with_5000_Searches.png,
> Mean_25000_SSTable_with_5000_Searches.png,
> Mean_3_SSTable_with_5000_Searches.png,
> Mean_5000_SSTable_with_5000_Searches.png
>
>
> Cassandra uses IntervalTrees to identify the SSTables that overlap with
> search interval. In Cassandra, IntervalTrees are not mutated. They are
> recreated each time a mutation is required. This can be an issue during
> repairs. In fact we noticed such issues during repair.
> Since lists are cache friendly compared to linked lists and trees, I decided
> to compare the search performance with:
> * Linear Walk.
> * Elimination using Binary Search (idea is to eliminate intervals using start
> and end points of search interval).
> Based on the tests I ran, I noticed Binary Search based elimination almost
> always performs similar to IntervalTree or out performs IntervalTree based
> search. The cost of IntervalTree construction is also substantial and
> produces lot of garbage during repairs.
> I ran the tests using random intervals to build the tree/lists and another
> randomly generated search interval with 5000 iterations. I'm attaching all
> the relevant graphs. The x-axis in the graphs is the search interval
> coverage. 10p means the search interval covered 10% of the intervals. The
> y-axis is the time the search took in nanos.
> PS:
> # For the purpose of test, I simplified the IntervalTree by removing the data
> portion of the interval. Modified the template version (Java generics) to a
> specialized version.
> # I used the code from Cassandra version _3.11_.
> # Time in the graph is in nanos.
--
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[jira] [Commented] (CASSANDRA-15397) IntervalTree performance comparison with Linear Walk and Binary Search based Elimination.
[ https://issues.apache.org/jira/browse/CASSANDRA-15397?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16967732#comment-16967732 ] Chandrasekhar Thumuluru commented on CASSANDRA-15397: - Sure [~benedict]. I can make the changes and update the ticket with Github links. As you can see I simplified the IntervalTree implementation for comparison purposes. I'll make the final changes with tests and push them to my fork by weekend. I completely agree with you it's not a pressing change but given the construction cost and immutable nature of IntervalTree usage I felt it's worth a shot. > IntervalTree performance comparison with Linear Walk and Binary Search based > Elimination. > -- > > Key: CASSANDRA-15397 > URL: https://issues.apache.org/jira/browse/CASSANDRA-15397 > Project: Cassandra > Issue Type: Improvement > Components: Local/SSTable >Reporter: Chandrasekhar Thumuluru >Assignee: Chandrasekhar Thumuluru >Priority: Low > Attachments: 95p_1_SSTable_with_5000_Searches.png, > 95p_15000_SSTable_with_5000_Searches.png, > 95p_2_SSTable_with_5000_Searches.png, > 95p_25000_SSTable_with_5000_Searches.png, > 95p_3_SSTable_with_5000_Searches.png, > 95p_5000_SSTable_with_5000_Searches.png, > 99p_1_SSTable_with_5000_Searches.png, > 99p_15000_SSTable_with_5000_Searches.png, > 99p_2_SSTable_with_5000_Searches.png, > 99p_25000_SSTable_with_5000_Searches.png, > 99p_3_SSTable_with_5000_Searches.png, > 99p_5000_SSTable_with_5000_Searches.png, IntervalList.java, > IntervalListWithElimination.java, IntervalTreeSimplified.java, > Mean_1_SSTable_with_5000_Searches.png, > Mean_15000_SSTable_with_5000_Searches.png, > Mean_2_SSTable_with_5000_Searches.png, > Mean_25000_SSTable_with_5000_Searches.png, > Mean_3_SSTable_with_5000_Searches.png, > Mean_5000_SSTable_with_5000_Searches.png > > > Cassandra uses IntervalTrees to identify the SSTables that overlap with > search interval. In Cassandra, IntervalTrees are not mutated. They are > recreated each time a mutation is required. This can be an issue during > repairs. In fact we noticed such issues during repair. > Since lists are cache friendly compared to linked lists and trees, I decided > to compare the search performance with: > * Linear Walk. > * Elimination using Binary Search (idea is to eliminate intervals using start > and end points of search interval). > Based on the tests I ran, I noticed Binary Search based elimination almost > always performs similar to IntervalTree or out performs IntervalTree based > search. The cost of IntervalTree construction is also substantial and > produces lot of garbage during repairs. > I ran the tests using random intervals to build the tree/lists and another > randomly generated search interval with 5000 iterations. I'm attaching all > the relevant graphs. The x-axis in the graphs is the search interval > coverage. 10p means the search interval covered 10% of the intervals. The > y-axis is the time the search took in nanos. > PS: > # For the purpose of test, I simplified the IntervalTree by removing the data > portion of the interval. Modified the template version (Java generics) to a > specialized version. > # I used the code from Cassandra version _3.11_. > # Time in the graph is in nanos. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: commits-unsubscr...@cassandra.apache.org For additional commands, e-mail: commits-h...@cassandra.apache.org
[jira] [Commented] (CASSANDRA-15397) IntervalTree performance comparison with Linear Walk and Binary Search based Elimination.
[ https://issues.apache.org/jira/browse/CASSANDRA-15397?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16967715#comment-16967715 ] Benedict Elliott Smith commented on CASSANDRA-15397: Hi [~cthumuluru], this sounds like a plausible optimisation (without having thought about it much myself yet). Unfortunately it's not a very _pressing_ optimisation, but I will try to find time within the next couple of weeks to give you some feedback. If possible, we generally prefer links to GitHub branches. Could you push your fork with these changes somewhere to look at? > IntervalTree performance comparison with Linear Walk and Binary Search based > Elimination. > -- > > Key: CASSANDRA-15397 > URL: https://issues.apache.org/jira/browse/CASSANDRA-15397 > Project: Cassandra > Issue Type: Improvement > Components: Local/SSTable >Reporter: Chandrasekhar Thumuluru >Assignee: Chandrasekhar Thumuluru >Priority: Low > Attachments: 95p_1_SSTable_with_5000_Searches.png, > 95p_15000_SSTable_with_5000_Searches.png, > 95p_2_SSTable_with_5000_Searches.png, > 95p_25000_SSTable_with_5000_Searches.png, > 95p_3_SSTable_with_5000_Searches.png, > 95p_5000_SSTable_with_5000_Searches.png, > 99p_1_SSTable_with_5000_Searches.png, > 99p_15000_SSTable_with_5000_Searches.png, > 99p_2_SSTable_with_5000_Searches.png, > 99p_25000_SSTable_with_5000_Searches.png, > 99p_3_SSTable_with_5000_Searches.png, > 99p_5000_SSTable_with_5000_Searches.png, IntervalList.java, > IntervalListWithElimination.java, IntervalTreeSimplified.java, > Mean_1_SSTable_with_5000_Searches.png, > Mean_15000_SSTable_with_5000_Searches.png, > Mean_2_SSTable_with_5000_Searches.png, > Mean_25000_SSTable_with_5000_Searches.png, > Mean_3_SSTable_with_5000_Searches.png, > Mean_5000_SSTable_with_5000_Searches.png > > > Cassandra uses IntervalTrees to identify the SSTables that overlap with > search interval. In Cassandra, IntervalTrees are not mutated. They are > recreated each time a mutation is required. This can be an issue during > repairs. In fact we noticed such issues during repair. > Since lists are cache friendly compared to linked lists and trees, I decided > to compare the search performance with: > * Linear Walk. > * Elimination using Binary Search (idea is to eliminate intervals using start > and end points of search interval). > Based on the tests I ran, I noticed Binary Search based elimination almost > always performs similar to IntervalTree or out performs IntervalTree based > search. The cost of IntervalTree construction is also substantial and > produces lot of garbage during repairs. > I ran the tests using random intervals to build the tree/lists and another > randomly generated search interval with 5000 iterations. I'm attaching all > the relevant graphs. The x-axis in the graphs is the search interval > coverage. 10p means the search interval covered 10% of the intervals. The > y-axis is the time the search took in nanos. > PS: > # For the purpose of test, I simplified the IntervalTree by removing the data > portion of the interval. Modified the template version (Java generics) to a > specialized version. > # I used the code from Cassandra version _3.11_. > # Time in the graph is in nanos. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: commits-unsubscr...@cassandra.apache.org For additional commands, e-mail: commits-h...@cassandra.apache.org
