[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
Github user jkbradley commented on the issue: https://github.com/apache/spark/pull/15874 Well, I'm having trouble merging b/c of bad wifi during travel. Ping @yanboliang @MLnick @mengxr would one of you mind merging this with master and branch-2.1? @sethah and I having both given LGTMs. Thanks! --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
Github user jkbradley commented on the issue: https://github.com/apache/spark/pull/15874 LGTM Thanks everyone! Merging with master and branch-2.1 --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
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[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
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[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
Github user SparkQA commented on the issue: https://github.com/apache/spark/pull/15874 **[Test build #69215 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/69215/consoleFull)** for PR 15874 at commit [`e198080`](https://github.com/apache/spark/commit/e198080557c598286363184855a6f368d60b45e3). * This patch passes all tests. * This patch merges cleanly. * This patch adds the following public classes _(experimental)_: * `class ClusteringSummary(JavaWrapper):` * `class GaussianMixtureSummary(ClusteringSummary):` * `class BisectingKMeansSummary(ClusteringSummary):` * `trait CollectionGenerator extends Generator ` * `case class Stack(children: Seq[Expression]) extends Generator ` * `abstract class ExplodeBase extends UnaryExpression with CollectionGenerator with Serializable ` * `case class Explode(child: Expression) extends ExplodeBase ` * `case class PosExplode(child: Expression) extends ExplodeBase ` * `case class Inline(child: Expression) extends UnaryExpression with CollectionGenerator ` * `case class OuterReference(e: NamedExpression)` * `trait InvokeLike extends Expression with NonSQLExpression ` * `case class ColumnStat(` * `case class UncacheTableCommand(` * `case class OffsetSeq(offsets: Seq[Option[Offset]], metadata: Option[String] = None) ` * `case class SparkListenerDriverAccumUpdates(` --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
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[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
Github user Yunni commented on the issue: https://github.com/apache/spark/pull/15874 @jkbradley If you don't have more comments, can we merge this because I need to change the examples in #15795 ? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
Github user Yunni commented on the issue: https://github.com/apache/spark/pull/15874 Thanks @sethah ! Your comment was very helpful and detailed :-) --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
Github user sethah commented on the issue: https://github.com/apache/spark/pull/15874 LGTM. I think we've made JIRAs for all of the follow-up items. Thanks! --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
Github user Yunni commented on the issue: https://github.com/apache/spark/pull/15874 @sethah PTAL --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
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[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
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[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
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[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
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[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
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[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
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[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
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[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
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[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
Github user Yunni commented on the issue: https://github.com/apache/spark/pull/15874 Hi @sethah, grouping to a number of buckets does not really affect the independence since p is a mach larger prime. For example, in http://people.csail.mit.edu/mip/papers/kwise-lb/kwise-lb.pdf, they use "mod b". Since we don't care about the hash universe here, I am OK with changing to `(ax + b mod p)` if you think that makes more sense? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
Github user sethah commented on the issue: https://github.com/apache/spark/pull/15874 @jkbradley Thanks for checking that, that is the conclusion I drew as well. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
Github user Yunni commented on the issue: https://github.com/apache/spark/pull/15874 @jkbradley Awesome, thanks so much! :) Now that the API is finalized, I will work on the User Doc --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
Github user sethah commented on the issue: https://github.com/apache/spark/pull/15874 I will take a look. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
Github user jkbradley commented on the issue: https://github.com/apache/spark/pull/15874 @Yunni Thanks for the updates! I don't think we should include AND-amplification for 2.1 since we're already in QA. But it'd be nice to get it in 2.2. Also, 2.2 will give us plenty of time to discuss distributed approxNearestNeighbors. FYI: I asked around about the managed memory leak warning/failure. It is usually just a warning, but some test suites are set to fail upon seeing that warning. That was apparently useful for debugging some memory leak bugs but is not cause to worry. I recommend we make tests small enough to avoid them for now. If the warning becomes an issue, we could configure ML suites to ignore the warning, or we could even downgrade the warning to a lower-priority log message for all of Spark. This LGTM. What does everyone think? For 2.1, the main thing I'd still like to do is to send a PR to clarify terminology. That could be done in [https://github.com/apache/spark/pull/15795] --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
Github user MLnick commented on the issue: https://github.com/apache/spark/pull/15874 @Yunni I think if we are using this 2-independent hash family we should provide that reference you mention in the Scaladoc, and also mention it approximates min-wise independent. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
Github user Yunni commented on the issue: https://github.com/apache/spark/pull/15874 Hi @jkbradley, **MinHash** Yes, I agree that I shouldn't have said it's perfect hashing. Theoretically, it should be Min-wise Independent Permutation Family. What we used here is 2-independent (or 2-universal) hash families, which is approximately min-wise independent. Reference: http://people.csail.mit.edu/mip/papers/kwise-lb/kwise-lb.pdf **approxNearestNeighbors** I still think in the case of OR-amplification, the only way is to scan a number of candidates k times the average bucket size. I would like to understand more about what you proposed. I have left the note in the scaladoc and let us have more discussion in future releases. **AND-amplification** I've open a ticket in SPARK-18450 for AND-amplification. I am wondering if we are including it in 2.1.0? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] spark issue #15874: [Spark-18408][ML] API Improvements for LSH
Github user jkbradley commented on the issue: https://github.com/apache/spark/pull/15874 Other comments: **MinHash** Looking yet again at this, I think it's using a technically incorrect hash function. It is *not* a perfect hash function. It can hash 2 input indices to the same hash bucket. (As before, check out the Wikipedia page to see how it's missing the 2nd stage in the construction of a perfect hash function.) If we want to fix this, then we could alternatively precompute a random permutation of indices, which also serves as a perfect hash function. That said, perhaps it does not matter in practice. If numEntries (inputDim) is large enough, then the current hash function will probably behave similarly to a perfect hash function. **approxNearestNeighbors** This is still not what I proposed, even for single-probe queries. It will still have the potential to consider (and sort) a number of candidates much larger than numNearestNeighbors. Since we're running out of time, I'm fine with leaving it as is for now and just changing the behavior for the next release. However, can you please add a note to the method documentation that this method is experimental and will likely change behavior in the next release? Thanks! --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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Github user jkbradley commented on the issue: https://github.com/apache/spark/pull/15874 I'll take a look --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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