[jira] [Created] (IGNITE-12161) [ML] Add support of different classloaders for client code
Alexey Platonov created IGNITE-12161: Summary: [ML] Add support of different classloaders for client code Key: IGNITE-12161 URL: https://issues.apache.org/jira/browse/IGNITE-12161 Project: Ignite Issue Type: Improvement Components: ml Reporter: Alexey Platonov Assignee: Alexey Platonov Currently we support just one classloader for unknown classes on server side. Potentially client can handle several classloaders and we should support this situation. -- This message was sent by Atlassian Jira (v8.3.2#803003)
[jira] [Created] (IGNITE-12157) [ML] Implement distributed ROC AUC computation
Alexey Platonov created IGNITE-12157: Summary: [ML] Implement distributed ROC AUC computation Key: IGNITE-12157 URL: https://issues.apache.org/jira/browse/IGNITE-12157 Project: Ignite Issue Type: Improvement Components: ml Reporter: Alexey Platonov Assignee: Alexey Platonov Currently, we don't have valid ROC AUC computation at all. We should implement it with predict proba interface in models. It is desirable that ROC AUC computation will be distributed. -- This message was sent by Atlassian Jira (v8.3.2#803003)
[jira] [Created] (IGNITE-12156) [ML] Add meta information to models
Alexey Platonov created IGNITE-12156: Summary: [ML] Add meta information to models Key: IGNITE-12156 URL: https://issues.apache.org/jira/browse/IGNITE-12156 Project: Ignite Issue Type: Improvement Components: ml Reporter: Alexey Platonov Assignee: Alexey Platonov Current models don't contain any information about their learning process or a features meta-information or information about the type of model (for example RegressionTree doesn't differ from ClassificationTree in the interface). It leads to extra work in other APIs. For example, we cannot define automatically set of metrics for a user-passed model in Evaluator. -- This message was sent by Atlassian Jira (v8.3.2#803003)
[jira] [Created] (IGNITE-12155) [ML] Implementation of distributed estimator
Alexey Platonov created IGNITE-12155: Summary: [ML] Implementation of distributed estimator Key: IGNITE-12155 URL: https://issues.apache.org/jira/browse/IGNITE-12155 Project: Ignite Issue Type: Improvement Components: ml Reporter: Alexey Platonov Assignee: Alexey Platonov Currently, we don't have an ability to compute metrics in a distributed manner and it leads to reading all data from partitions to a client using Qursor. We should develop a framework for distributed computing of metrics. -- This message was sent by Atlassian Jira (v8.3.2#803003)
[jira] [Updated] (IGNITE-12024) [ML] PeerClassloading for ml related lambdas
[ https://issues.apache.org/jira/browse/IGNITE-12024?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-12024: - Remaining Estimate: 24h (was: 72h) Original Estimate: 24h (was: 72h) > [ML] PeerClassloading for ml related lambdas > > > Key: IGNITE-12024 > URL: https://issues.apache.org/jira/browse/IGNITE-12024 > Project: Ignite > Issue Type: Improvement > Components: ml >Reporter: Alexey Platonov >Assignee: Alexey Platonov >Priority: Major > Original Estimate: 24h > Remaining Estimate: 24h > > The current implementation of peerClassloading doesn't fulfill all ml > requirements. We want to provide ability of implementation custom vectorizers > and preprocessors. -- This message was sent by Atlassian JIRA (v7.6.14#76016)
[jira] [Created] (IGNITE-12024) [ML] PeerClassloading for ml related lambdas
Alexey Platonov created IGNITE-12024: Summary: [ML] PeerClassloading for ml related lambdas Key: IGNITE-12024 URL: https://issues.apache.org/jira/browse/IGNITE-12024 Project: Ignite Issue Type: Improvement Components: ml Reporter: Alexey Platonov Assignee: Alexey Platonov The current implementation of peerClassloading doesn't fulfill all ml requirements. We want to provide ability of implementation custom vectorizers and preprocessors. -- This message was sent by Atlassian JIRA (v7.6.14#76016)
[jira] [Assigned] (IGNITE-11759) [ML] Duplicate depenpecies for ml artifacts
[ https://issues.apache.org/jira/browse/IGNITE-11759?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov reassigned IGNITE-11759: Assignee: Alexey Platonov > [ML] Duplicate depenpecies for ml artifacts > --- > > Key: IGNITE-11759 > URL: https://issues.apache.org/jira/browse/IGNITE-11759 > Project: Ignite > Issue Type: Improvement > Components: ml >Affects Versions: 2.7 >Reporter: Yury Babak >Assignee: Alexey Platonov >Priority: Major > -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Assigned] (IGNITE-11504) [ML] Preprocessor trainers should support new feature-label extraction API
[ https://issues.apache.org/jira/browse/IGNITE-11504?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov reassigned IGNITE-11504: Assignee: Aleksey Zinoviev > [ML] Preprocessor trainers should support new feature-label extraction API > -- > > Key: IGNITE-11504 > URL: https://issues.apache.org/jira/browse/IGNITE-11504 > Project: Ignite > Issue Type: Improvement > Components: ml >Reporter: Alexey Platonov >Assignee: Aleksey Zinoviev >Priority: Major > Labels: stability > > Problem is same as feature extractors serialization bug. We should narrow our > API. (see parent task) -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Assigned] (IGNITE-11581) [ML] Adapt tutorial to new vectorizer API
[ https://issues.apache.org/jira/browse/IGNITE-11581?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov reassigned IGNITE-11581: Assignee: Aleksey Zinoviev > [ML] Adapt tutorial to new vectorizer API > - > > Key: IGNITE-11581 > URL: https://issues.apache.org/jira/browse/IGNITE-11581 > Project: Ignite > Issue Type: Bug > Components: ml >Reporter: Alexey Platonov >Assignee: Aleksey Zinoviev >Priority: Major > Labels: stability > > Currently tutorial uses old feature-labels extraction API -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Assigned] (IGNITE-11582) [ML] Pipelines should work with Vectorizers
[ https://issues.apache.org/jira/browse/IGNITE-11582?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov reassigned IGNITE-11582: Assignee: Aleksey Zinoviev > [ML] Pipelines should work with Vectorizers > --- > > Key: IGNITE-11582 > URL: https://issues.apache.org/jira/browse/IGNITE-11582 > Project: Ignite > Issue Type: Bug > Components: ml >Reporter: Alexey Platonov >Assignee: Aleksey Zinoviev >Priority: Major > Labels: stability > > Currently Pipelines are implemented using feature/label extraction functions > with generic label value. We should adapt pipelines for vectorizers (maybe > after this ticket - IGNITE-11481). -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Assigned] (IGNITE-11642) [ML] Umbrella: API for Feature/Label extracting (part 2)
[ https://issues.apache.org/jira/browse/IGNITE-11642?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov reassigned IGNITE-11642: Assignee: Aleksey Zinoviev > [ML] Umbrella: API for Feature/Label extracting (part 2) > > > Key: IGNITE-11642 > URL: https://issues.apache.org/jira/browse/IGNITE-11642 > Project: Ignite > Issue Type: Improvement > Components: ml >Reporter: Alexey Platonov >Assignee: Aleksey Zinoviev >Priority: Critical > Labels: stability > Fix For: 2.8 > > > Replace current lambdas with fixed API -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Assigned] (IGNITE-11580) [ML] Evaluators should accept Vectorizers
[ https://issues.apache.org/jira/browse/IGNITE-11580?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov reassigned IGNITE-11580: Assignee: Aleksey Zinoviev > [ML] Evaluators should accept Vectorizers > - > > Key: IGNITE-11580 > URL: https://issues.apache.org/jira/browse/IGNITE-11580 > Project: Ignite > Issue Type: Bug > Components: ml >Reporter: Alexey Platonov >Assignee: Aleksey Zinoviev >Priority: Major > Labels: stability > > Currently evaluation API uses old interface with separated feature-label > extractors. In context of IGNITE-11449 we should change this API. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Assigned] (IGNITE-11664) [ML] Use Double.NaN as default values for missing values in Vector
[ https://issues.apache.org/jira/browse/IGNITE-11664?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov reassigned IGNITE-11664: Assignee: Alexey Platonov > [ML] Use Double.NaN as default values for missing values in Vector > -- > > Key: IGNITE-11664 > URL: https://issues.apache.org/jira/browse/IGNITE-11664 > Project: Ignite > Issue Type: Improvement > Components: ml >Reporter: Alexey Platonov >Assignee: Alexey Platonov >Priority: Major > Labels: stability > > Currently, we use 0.0 value for default values in vectors if a value is > missing. But this way contradicts to preprocessors politics where for missing > values Double.NaN is using. Moreover, Double.NaN is a more convenient value > for missing feature values. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11675) [ML] Create additional examples for linear regressions, knn and kmeans
Alexey Platonov created IGNITE-11675: Summary: [ML] Create additional examples for linear regressions, knn and kmeans Key: IGNITE-11675 URL: https://issues.apache.org/jira/browse/IGNITE-11675 Project: Ignite Issue Type: Improvement Components: documentation, ml Reporter: Alexey Platonov Assignee: Alexey Platonov We should create additional examples for linear regressions, knn and kmeans in examples module for ebook about ML in Ignite. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11664) [ML] Use Double.NaN as default values for missing values in Vector
Alexey Platonov created IGNITE-11664: Summary: [ML] Use Double.NaN as default values for missing values in Vector Key: IGNITE-11664 URL: https://issues.apache.org/jira/browse/IGNITE-11664 Project: Ignite Issue Type: Improvement Components: ml Reporter: Alexey Platonov Currently, we use 0.0 value for default values in vectors if a value is missing. But this way contradicts to preprocessors politics where for missing values Double.NaN is using. Moreover, Double.NaN is a more convenient value for missing feature values. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11647) [ML] ML Vectors should work with all Serializable objects besides double
Alexey Platonov created IGNITE-11647: Summary: [ML] ML Vectors should work with all Serializable objects besides double Key: IGNITE-11647 URL: https://issues.apache.org/jira/browse/IGNITE-11647 Project: Ignite Issue Type: Improvement Components: ml Reporter: Alexey Platonov Assignee: Alexey Platonov Such refactoring allows us to reduce hierarchy parallelism between preprocessors and dataset trainers. Also, support of types besides double allows improving some algorithms like decision trees. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Resolved] (IGNITE-11477) [ML] Create tests for ML algorithms stability check against binary builds
[ https://issues.apache.org/jira/browse/IGNITE-11477?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov resolved IGNITE-11477. -- Resolution: Won't Fix > [ML] Create tests for ML algorithms stability check against binary builds > -- > > Key: IGNITE-11477 > URL: https://issues.apache.org/jira/browse/IGNITE-11477 > Project: Ignite > Issue Type: Improvement > Components: ml >Reporter: Alexey Platonov >Assignee: Alexey Platonov >Priority: Major > Labels: stability > > After new feature API creation we should create tests for ML algorithms > stability check against binary builds (or on other JVMs without common > classpath). All new algorithms should be delivered with such test. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Assigned] (IGNITE-11642) [ML] Umbrella: API for Feature/Label extracting (part 2)
[ https://issues.apache.org/jira/browse/IGNITE-11642?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov reassigned IGNITE-11642: Assignee: (was: Alexey Platonov) > [ML] Umbrella: API for Feature/Label extracting (part 2) > > > Key: IGNITE-11642 > URL: https://issues.apache.org/jira/browse/IGNITE-11642 > Project: Ignite > Issue Type: Improvement > Components: ml >Reporter: Alexey Platonov >Priority: Critical > Labels: stability > Fix For: 2.8 > > > Replace current lambdas with fixed API -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11642) [ML] Umbrella: API for Feature/Label extracting (part 2)
Alexey Platonov created IGNITE-11642: Summary: [ML] Umbrella: API for Feature/Label extracting (part 2) Key: IGNITE-11642 URL: https://issues.apache.org/jira/browse/IGNITE-11642 Project: Ignite Issue Type: Improvement Components: ml Reporter: Alexey Platonov Assignee: Alexey Platonov Fix For: 2.8 Replace current lambdas with fixed API -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Resolved] (IGNITE-11481) [ML] Prototype of DatasetRow for Vectorizer
[ https://issues.apache.org/jira/browse/IGNITE-11481?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov resolved IGNITE-11481. -- Resolution: Won't Fix > [ML] Prototype of DatasetRow for Vectorizer > --- > > Key: IGNITE-11481 > URL: https://issues.apache.org/jira/browse/IGNITE-11481 > Project: Ignite > Issue Type: Improvement > Components: ml >Reporter: Alexey Platonov >Assignee: Alexey Platonov >Priority: Major > Labels: stability > > Vectorizer shold produce DatasetRow object that can contains columns with > different types (double, string, etc.). It needs for preprocessors working > with non-double values. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-11449) [ML] Umbrella: API for Feature/Label extracting (part 1)
[ https://issues.apache.org/jira/browse/IGNITE-11449?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-11449: - Summary: [ML] Umbrella: API for Feature/Label extracting (part 1) (was: [ML] Umbrella: API for Feature/Label extracting) > [ML] Umbrella: API for Feature/Label extracting (part 1) > > > Key: IGNITE-11449 > URL: https://issues.apache.org/jira/browse/IGNITE-11449 > Project: Ignite > Issue Type: Improvement > Components: ml >Reporter: Yury Babak >Assignee: Alexey Platonov >Priority: Critical > Labels: stability > Time Spent: 1h 20m > Remaining Estimate: 0h > > Replace current lambdas with fixed API -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Resolved] (IGNITE-11478) [ML] Use new vectorizer API in Trainers
[ https://issues.apache.org/jira/browse/IGNITE-11478?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov resolved IGNITE-11478. -- Resolution: Duplicate dup of IGNITE-11480 > [ML] Use new vectorizer API in Trainers > --- > > Key: IGNITE-11478 > URL: https://issues.apache.org/jira/browse/IGNITE-11478 > Project: Ignite > Issue Type: Improvement > Components: ml >Reporter: Alexey Platonov >Assignee: Alexey Platonov >Priority: Critical > Labels: stability > > We should rewrite current trainers - exclude all "free"-feature/labels > extractors from APIs and use new vectorizer in them. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Resolved] (IGNITE-11480) [ML] Use only Vectorizer API in DatasetTrainer API
[ https://issues.apache.org/jira/browse/IGNITE-11480?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov resolved IGNITE-11480. -- Resolution: Fixed > [ML] Use only Vectorizer API in DatasetTrainer API > > > Key: IGNITE-11480 > URL: https://issues.apache.org/jira/browse/IGNITE-11480 > Project: Ignite > Issue Type: Improvement > Components: ml >Reporter: Alexey Platonov >Assignee: Alexey Platonov >Priority: Critical > Labels: stability > > Use only Vectorizer API in DatasetTrainer API to avoid problems with user > classes serialization. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11582) [ML] Pipelines should work with Vectorizers
Alexey Platonov created IGNITE-11582: Summary: [ML] Pipelines should work with Vectorizers Key: IGNITE-11582 URL: https://issues.apache.org/jira/browse/IGNITE-11582 Project: Ignite Issue Type: Bug Components: ml Reporter: Alexey Platonov Currently Pipelines are implemented using feature/label extraction functions with generic label value. We should adapt pipelines for vectorizers (maybe after this ticket - IGNITE-11481). -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11581) [ML] Adapt tutorial to new vectorizer API
Alexey Platonov created IGNITE-11581: Summary: [ML] Adapt tutorial to new vectorizer API Key: IGNITE-11581 URL: https://issues.apache.org/jira/browse/IGNITE-11581 Project: Ignite Issue Type: Bug Components: ml Reporter: Alexey Platonov Currently tutorial uses old feature-labels extraction API -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11580) [ML] Evaluators should accept Vectorizers
Alexey Platonov created IGNITE-11580: Summary: [ML] Evaluators should accept Vectorizers Key: IGNITE-11580 URL: https://issues.apache.org/jira/browse/IGNITE-11580 Project: Ignite Issue Type: Bug Components: ml Reporter: Alexey Platonov Currently evaluation API uses old interface with separated feature-label extractors. In context of IGNITE-11449 we should change this API. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Resolved] (IGNITE-11479) [ML] Use new vectorizer API in PartitionDatasetBuilders
[ https://issues.apache.org/jira/browse/IGNITE-11479?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov resolved IGNITE-11479. -- Resolution: Fixed > [ML] Use new vectorizer API in PartitionDatasetBuilders > --- > > Key: IGNITE-11479 > URL: https://issues.apache.org/jira/browse/IGNITE-11479 > Project: Ignite > Issue Type: Improvement > Components: ml >Reporter: Alexey Platonov >Assignee: Alexey Platonov >Priority: Critical > Labels: stability > > We need to exclude current feature extractors from partition building API and > replace old extractors with new vectorizer. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Resolved] (IGNITE-11476) [ML] Use new feature extraction API in examples
[ https://issues.apache.org/jira/browse/IGNITE-11476?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov resolved IGNITE-11476. -- Resolution: Fixed > [ML] Use new feature extraction API in examples > --- > > Key: IGNITE-11476 > URL: https://issues.apache.org/jira/browse/IGNITE-11476 > Project: Ignite > Issue Type: Improvement > Components: ml >Reporter: Alexey Platonov >Assignee: Alexey Platonov >Priority: Critical > Labels: stability > > Introduce new feature/label extraction API to all examples. These examples > should work on binary builds without sharing additional jars to libs > directory (except ml-jar). -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-11561) [ML] IgniteDistributedModel for XGBoost doesn't work in example
[ https://issues.apache.org/jira/browse/IGNITE-11561?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-11561: - Labels: stability (was: ) > [ML] IgniteDistributedModel for XGBoost doesn't work in example > --- > > Key: IGNITE-11561 > URL: https://issues.apache.org/jira/browse/IGNITE-11561 > Project: Ignite > Issue Type: Bug > Components: ml >Affects Versions: 2.7, 2.8 >Reporter: Alexey Platonov >Assignee: Anton Dmitriev >Priority: Major > Labels: stability > > Distributed inference model for XGBoost doesn't work in example > (XGBoostModelParserExample). It always returns same value. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11561) [ML] IgniteDistributedModel for XGBoost doesn't work in example
Alexey Platonov created IGNITE-11561: Summary: [ML] IgniteDistributedModel for XGBoost doesn't work in example Key: IGNITE-11561 URL: https://issues.apache.org/jira/browse/IGNITE-11561 Project: Ignite Issue Type: Bug Components: ml Affects Versions: 2.7, 2.8 Reporter: Alexey Platonov Assignee: Anton Dmitriev Distributed inference model for XGBoost doesn't work in example (XGBoostModelParserExample). It always returns same value. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11504) [ML] Preprocessor trainers should support new feature-label extraction API
Alexey Platonov created IGNITE-11504: Summary: [ML] Preprocessor trainers should support new feature-label extraction API Key: IGNITE-11504 URL: https://issues.apache.org/jira/browse/IGNITE-11504 Project: Ignite Issue Type: Improvement Components: ml Reporter: Alexey Platonov Problem is same as feature extractors serialization bug. We should narrow our API. (see parent task) -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Resolved] (IGNITE-11475) [ML] Vectorizer API prototype with POC
[ https://issues.apache.org/jira/browse/IGNITE-11475?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov resolved IGNITE-11475. -- Resolution: Fixed > [ML] Vectorizer API prototype with POC > --- > > Key: IGNITE-11475 > URL: https://issues.apache.org/jira/browse/IGNITE-11475 > Project: Ignite > Issue Type: Improvement > Components: ml >Reporter: Alexey Platonov >Assignee: Alexey Platonov >Priority: Critical > Labels: stability > > We need to create a prototype of API for features/labels extraction and > introduce it to one or two already existing examples. This prototype should > show that new API works on binary builds. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-11479) [ML] Use new vectorizer API in PartitionDatasetBuilders
[ https://issues.apache.org/jira/browse/IGNITE-11479?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-11479: - Priority: Critical (was: Major) > [ML] Use new vectorizer API in PartitionDatasetBuilders > --- > > Key: IGNITE-11479 > URL: https://issues.apache.org/jira/browse/IGNITE-11479 > Project: Ignite > Issue Type: Improvement > Components: ml >Reporter: Alexey Platonov >Assignee: Alexey Platonov >Priority: Critical > Labels: stability > > We need to exclude current feature extractors from partition building API and > replace old extractors with new vectorizer. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11481) [ML] Prototype of DatasetRow for Vectorizer
Alexey Platonov created IGNITE-11481: Summary: [ML] Prototype of DatasetRow for Vectorizer Key: IGNITE-11481 URL: https://issues.apache.org/jira/browse/IGNITE-11481 Project: Ignite Issue Type: Improvement Components: ml Reporter: Alexey Platonov Assignee: Alexey Platonov Vectorizer shold produce DatasetRow object that can contains columns with different types (double, string, etc.). It needs for preprocessors working with non-double values. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-11480) [ML] Use only Vectorizer API in DatasetTrainer API
[ https://issues.apache.org/jira/browse/IGNITE-11480?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-11480: - Priority: Critical (was: Major) > [ML] Use only Vectorizer API in DatasetTrainer API > > > Key: IGNITE-11480 > URL: https://issues.apache.org/jira/browse/IGNITE-11480 > Project: Ignite > Issue Type: Improvement > Components: ml >Reporter: Alexey Platonov >Assignee: Alexey Platonov >Priority: Critical > Labels: stability > > Use only Vectorizer API in DatasetTrainer API to avoid problems with user > classes serialization. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11480) [ML] Use only Vectorizer API in DatasetTrainer API
Alexey Platonov created IGNITE-11480: Summary: [ML] Use only Vectorizer API in DatasetTrainer API Key: IGNITE-11480 URL: https://issues.apache.org/jira/browse/IGNITE-11480 Project: Ignite Issue Type: Improvement Components: ml Reporter: Alexey Platonov Assignee: Alexey Platonov Use only Vectorizer API in DatasetTrainer API to avoid problems with user classes serialization. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11479) [ML] Use new vectorizer API in PartitionDatasetBuilders
Alexey Platonov created IGNITE-11479: Summary: [ML] Use new vectorizer API in PartitionDatasetBuilders Key: IGNITE-11479 URL: https://issues.apache.org/jira/browse/IGNITE-11479 Project: Ignite Issue Type: Improvement Components: ml Reporter: Alexey Platonov Assignee: Alexey Platonov We need to exclude current feature extractors from partition building API and replace old extractors with new vectorizer. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11478) [ML] Use new vectorizer API in Trainers
Alexey Platonov created IGNITE-11478: Summary: [ML] Use new vectorizer API in Trainers Key: IGNITE-11478 URL: https://issues.apache.org/jira/browse/IGNITE-11478 Project: Ignite Issue Type: Improvement Components: ml Reporter: Alexey Platonov Assignee: Alexey Platonov We should rewrite current trainers - exclude all "free"-feature/labels extractors from APIs and use new vectorizer in them. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11477) [ML] Create tests for ML algorithms stability check against binary builds
Alexey Platonov created IGNITE-11477: Summary: [ML] Create tests for ML algorithms stability check against binary builds Key: IGNITE-11477 URL: https://issues.apache.org/jira/browse/IGNITE-11477 Project: Ignite Issue Type: Improvement Components: ml Reporter: Alexey Platonov Assignee: Alexey Platonov After new feature API creation we should create tests for ML algorithms stability check against binary builds (or on other JVMs without common classpath). All new algorithms should be delivered with such test. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11476) [ML] Use new feature extraction API in examples
Alexey Platonov created IGNITE-11476: Summary: [ML] Use new feature extraction API in examples Key: IGNITE-11476 URL: https://issues.apache.org/jira/browse/IGNITE-11476 Project: Ignite Issue Type: Improvement Components: ml Reporter: Alexey Platonov Assignee: Alexey Platonov Introduce new feature/label extraction API to all examples. These examples should work on binary builds without sharing additional jars to libs directory (except ml-jar). -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11475) [ML] Vectorizer API prototype with POC
Alexey Platonov created IGNITE-11475: Summary: [ML] Vectorizer API prototype with POC Key: IGNITE-11475 URL: https://issues.apache.org/jira/browse/IGNITE-11475 Project: Ignite Issue Type: Improvement Components: ml Reporter: Alexey Platonov Assignee: Alexey Platonov We need to create a prototype of API for features/labels extraction and introduce it to one or two already existing examples. This prototype should show that new API works on binary builds. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-11449) [ML] Umbrella: API for Feature/Label extracting
[ https://issues.apache.org/jira/browse/IGNITE-11449?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-11449: - Summary: [ML] Umbrella: API for Feature/Label extracting (was: [ML] API for Feature/Label extracting) > [ML] Umbrella: API for Feature/Label extracting > --- > > Key: IGNITE-11449 > URL: https://issues.apache.org/jira/browse/IGNITE-11449 > Project: Ignite > Issue Type: Improvement > Components: ml >Reporter: Yury Babak >Assignee: Alexey Platonov >Priority: Critical > Labels: stability > > Replace current lambdas with fixed API -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Commented] (IGNITE-11401) [ML] Labmdas doesn't work in binary builds
[
https://issues.apache.org/jira/browse/IGNITE-11401?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16780313#comment-16780313
]
Alexey Platonov commented on IGNITE-11401:
--
[2019-02-28 11:48:26,437][ERROR][sys-#46][GridTaskWorker] Failed to obtain
remote job result policy for result from ComputeTask.result(..) method (will
fail the whole task): GridJobResultImpl [job=C2
[c=o.a.i.ml.compute.IgniteCallableWrapper@63f34b70], sib=GridJobSiblingImpl
[sesId=dbf0a433961-68c23d76-98bb-403c-bd19-f1aede32f245,
jobId=fbf0a433961-68c23d76-98bb-403c-bd19-f1aede32f245,
nodeId=28bab0e6-b041-42f4-8669-7e297fd2dce2, isJobDone=false],
jobCtx=GridJobContextImpl
[jobId=fbf0a433961-68c23d76-98bb-403c-bd19-f1aede32f245, timeoutObj=null,
attrs=HashMap {}], node=TcpDiscoveryNode
[id=28bab0e6-b041-42f4-8669-7e297fd2dce2, addrs=ArrayList [0:0:0:0:0:0:0:1%lo,
127.0.0.1, 172.17.0.1, 172.25.4.139, 172.25.4.25], sockAddrs=HashSet
[/172.25.4.25:47500, /172.17.0.1:47500, /0:0:0:0:0:0:0:1%lo:47500,
/127.0.0.1:47500, /172.25.4.139:47500], discPort=47500, order=1, intOrder=1,
lastExchangeTime=1551343692014, loc=false, ver=2.8.0#20190228-sha1:e5538a10,
isClient=false], ex=class o.a.i.IgniteException: Failed to deserialize object
[typeName=o.a.i.i.processors.closure.GridClosureProcessor$C2], hasRes=true,
isCancelled=false, isOccupied=true]
class org.apache.ignite.IgniteException: Remote job threw user exception
(override or implement ComputeTask.result(..) method if you would like to have
automatic failover for this exception): Failed to deserialize object
[typeName=org.apache.ignite.internal.processors.closure.GridClosureProcessor$C2]
at
org.apache.ignite.compute.ComputeTaskAdapter.result(ComputeTaskAdapter.java:102)
at
org.apache.ignite.internal.processors.task.GridTaskWorker$5.apply(GridTaskWorker.java:1062)
at
org.apache.ignite.internal.processors.task.GridTaskWorker$5.apply(GridTaskWorker.java:1055)
at
org.apache.ignite.internal.util.IgniteUtils.wrapThreadLoader(IgniteUtils.java:6877)
at
org.apache.ignite.internal.processors.task.GridTaskWorker.result(GridTaskWorker.java:1055)
at
org.apache.ignite.internal.processors.task.GridTaskWorker.onResponse(GridTaskWorker.java:862)
at
org.apache.ignite.internal.processors.task.GridTaskProcessor.processJobExecuteResponse(GridTaskProcessor.java:1125)
at
org.apache.ignite.internal.processors.task.GridTaskProcessor$JobMessageListener.onMessage(GridTaskProcessor.java:1358)
at
org.apache.ignite.internal.managers.communication.GridIoManager.invokeListener(GridIoManager.java:1561)
at
org.apache.ignite.internal.managers.communication.GridIoManager.processRegularMessage0(GridIoManager.java:1189)
at
org.apache.ignite.internal.managers.communication.GridIoManager.access$4200(GridIoManager.java:127)
at
org.apache.ignite.internal.managers.communication.GridIoManager$8.run(GridIoManager.java:1086)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: class org.apache.ignite.IgniteException: Failed to deserialize
object
[typeName=org.apache.ignite.internal.processors.closure.GridClosureProcessor$C2]
at
org.apache.ignite.internal.processors.job.GridJobWorker.initialize(GridJobWorker.java:460)
at
org.apache.ignite.internal.processors.job.GridJobProcessor.processJobExecuteRequest(GridJobProcessor.java:1119)
at
org.apache.ignite.internal.processors.job.GridJobProcessor$JobExecutionListener.onMessage(GridJobProcessor.java:1923)
... 7 more
Caused by: class org.apache.ignite.IgniteCheckedException: Failed to
deserialize object
[typeName=org.apache.ignite.internal.processors.closure.GridClosureProcessor$C2]
at
org.apache.ignite.internal.util.IgniteUtils.unmarshal(IgniteUtils.java:10018)
at
org.apache.ignite.internal.processors.job.GridJobWorker.initialize(GridJobWorker.java:441)
... 9 more
Caused by: class org.apache.ignite.binary.BinaryObjectException: Failed to
deserialize object
[typeName=org.apache.ignite.internal.processors.closure.GridClosureProcessor$C2]
at
org.apache.ignite.internal.binary.BinaryClassDescriptor.read(BinaryClassDescriptor.java:913)
at
org.apache.ignite.internal.binary.BinaryReaderExImpl.deserialize0(BinaryReaderExImpl.java:1763)
at
org.apache.ignite.internal.binary.BinaryReaderExImpl.deserialize(BinaryReaderExImpl.java:1715)
at
org.apache.ignite.internal.binary.GridBinaryMarshaller.deserialize(GridBinaryMarshaller.java:307)
at
org.apache.ignite.internal.binary.BinaryMarshaller.unmarshal0(BinaryMarshaller.java:101)
at
org.apache.ignite.marshaller.AbstractNodeNameAwareMarshaller.unmarshal(AbstractNodeNameAwareMarshaller.java:81)
at
[jira] [Created] (IGNITE-11401) [ML] Labmdas doesn't work in binary builds
Alexey Platonov created IGNITE-11401: Summary: [ML] Labmdas doesn't work in binary builds Key: IGNITE-11401 URL: https://issues.apache.org/jira/browse/IGNITE-11401 Project: Ignite Issue Type: Bug Components: ml Reporter: Alexey Platonov Assignee: Alexey Platonov Fix For: 2.8 Current lambdas for feature extraction doesn't work in binary builds and fail with such errors: Caused by: class org.apache.ignite.binary.BinaryObjectException: Failed to deserialize object [typeName=org.apache.ignite.ml.regressions.linear.FeatureExtractorWrapper] at org.apache.ignite.internal.binary.BinaryClassDescriptor.read(BinaryClassDescriptor.java:913) at org.apache.ignite.internal.binary.BinaryReaderExImpl.deserialize0(BinaryReaderExImpl.java:1763) at org.apache.ignite.internal.binary.BinaryReaderExImpl.deserialize(BinaryReaderExImpl.java:1715) at org.apache.ignite.internal.binary.BinaryReaderExImpl.readField(BinaryReaderExImpl.java:1983) at org.apache.ignite.internal.binary.BinaryFieldAccessor$DefaultFinalClassAccessor.read0(BinaryFieldAccessor.java:703) at org.apache.ignite.internal.binary.BinaryFieldAccessor.read(BinaryFieldAccessor.java:188) ... 40 more Caused by: class org.apache.ignite.binary.BinaryObjectException: Failed to read field [name=featureExtractor] at org.apache.ignite.internal.binary.BinaryFieldAccessor.read(BinaryFieldAccessor.java:192) at org.apache.ignite.internal.binary.BinaryClassDescriptor.read(BinaryClassDescriptor.java:874) ... 45 more Caused by: class org.apache.ignite.binary.BinaryObjectException: Failed to deserialize object [typeName=java.lang.invoke.SerializedLambda] at org.apache.ignite.internal.binary.BinaryClassDescriptor.read(BinaryClassDescriptor.java:913) at org.apache.ignite.internal.binary.BinaryReaderExImpl.deserialize0(BinaryReaderExImpl.java:1763) at org.apache.ignite.internal.binary.BinaryReaderExImpl.deserialize(BinaryReaderExImpl.java:1715) at org.apache.ignite.internal.binary.BinaryReaderExImpl.readField(BinaryReaderExImpl.java:1983) at org.apache.ignite.internal.binary.BinaryFieldAccessor$DefaultFinalClassAccessor.read0(BinaryFieldAccessor.java:703) at org.apache.ignite.internal.binary.BinaryFieldAccessor.read(BinaryFieldAccessor.java:188) ... 46 more Caused by: class org.apache.ignite.binary.BinaryObjectException: Failed to read field [name=capturedArgs] at org.apache.ignite.internal.binary.BinaryFieldAccessor.read(BinaryFieldAccessor.java:192) at org.apache.ignite.internal.binary.BinaryClassDescriptor.read(BinaryClassDescriptor.java:874) ... 51 more Caused by: class org.apache.ignite.binary.BinaryInvalidTypeException: org.apache.ignite.examples.ml.regression.linear.StaticFun -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11372) [ML] Fix javadoc in VectorWithDistributionId
Alexey Platonov created IGNITE-11372: Summary: [ML] Fix javadoc in VectorWithDistributionId Key: IGNITE-11372 URL: https://issues.apache.org/jira/browse/IGNITE-11372 Project: Ignite Issue Type: Bug Components: ml Reporter: Alexey Platonov Assignee: Alexey Platonov "mvn initialize -Pjavadoc" fails with error "[ERROR] Failed to execute goal org.apache.maven.plugins:maven-antrun-plugin:1.7:run (javadoc-postprocessing-new) on project apache-ignite: An Ant BuildException has occured: Execution failed due to: Class doesn't have description in file: <..>/ml/util/generators/primitives/vector/VectorGeneratorsFamily.VectorWithDistributionId.html" -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Assigned] (IGNITE-11328) Ignite binary build is too big
[
https://issues.apache.org/jira/browse/IGNITE-11328?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Alexey Platonov reassigned IGNITE-11328:
Assignee: Alexey Platonov (was: Yury Babak)
> Ignite binary build is too big
> --
>
> Key: IGNITE-11328
> URL: https://issues.apache.org/jira/browse/IGNITE-11328
> Project: Ignite
> Issue Type: Bug
>Affects Versions: 2.8
>Reporter: Sergey Kozlov
>Assignee: Alexey Platonov
>Priority: Blocker
> Fix For: 2.8
>
>
> I built Apache Ignite and get zip file is ~ 800MB.
> +400MB added by 4 ML modules in {{libs/optional}}
> Looks like it should be redesigned (join in a single module and at least it
> will remove same deps)
--
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[jira] [Resolved] (IGNITE-10545) [ML] Kullback–Leibler divergence
[ https://issues.apache.org/jira/browse/IGNITE-10545?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov resolved IGNITE-10545. -- Resolution: Won't Fix In my opinion this task is redundant because Kullback-Leibler divergence in most cases are theoretical metric used as target for classifiers. From requirement of apriori distribution for metric computing point of view this task can be closed with status 'won't fix'. > [ML] Kullback–Leibler divergence > > > Key: IGNITE-10545 > URL: https://issues.apache.org/jira/browse/IGNITE-10545 > Project: Ignite > Issue Type: New Feature > Components: ml >Reporter: Yury Babak >Assignee: Alexey Platonov >Priority: Major > > For comparing several distributions we need to implement such metric. > > [wiki link|https://en.wikipedia.org/wiki/Kullback%E2%80%93Leibler_divergence] -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Assigned] (IGNITE-10548) [ML] Classificator based on GMM
[ https://issues.apache.org/jira/browse/IGNITE-10548?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov reassigned IGNITE-10548: Assignee: Alexey Platonov > [ML] Classificator based on GMM > --- > > Key: IGNITE-10548 > URL: https://issues.apache.org/jira/browse/IGNITE-10548 > Project: Ignite > Issue Type: New Feature > Components: ml >Reporter: Yury Babak >Assignee: Alexey Platonov >Priority: Major > > Implement supervised classifier learning over GMM. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Assigned] (IGNITE-10545) [ML] Kullback–Leibler divergence
[ https://issues.apache.org/jira/browse/IGNITE-10545?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov reassigned IGNITE-10545: Assignee: Alexey Platonov > [ML] Kullback–Leibler divergence > > > Key: IGNITE-10545 > URL: https://issues.apache.org/jira/browse/IGNITE-10545 > Project: Ignite > Issue Type: New Feature > Components: ml >Reporter: Yury Babak >Assignee: Alexey Platonov >Priority: Major > > For comparing several distributions we need to implement such metric. > > [wiki link|https://en.wikipedia.org/wiki/Kullback%E2%80%93Leibler_divergence] -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Assigned] (IGNITE-10546) [ML] GMM with adding and removal of components
[ https://issues.apache.org/jira/browse/IGNITE-10546?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov reassigned IGNITE-10546: Assignee: Alexey Platonov > [ML] GMM with adding and removal of components > -- > > Key: IGNITE-10546 > URL: https://issues.apache.org/jira/browse/IGNITE-10546 > Project: Ignite > Issue Type: New Feature > Components: ml >Reporter: Yury Babak >Assignee: Alexey Platonov >Priority: Major > > Improve fixed GMM by adding changeable number of components ability. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Assigned] (IGNITE-10547) [ML] Examples of GMM usage
[ https://issues.apache.org/jira/browse/IGNITE-10547?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov reassigned IGNITE-10547: Assignee: Alexey Platonov > [ML] Examples of GMM usage > -- > > Key: IGNITE-10547 > URL: https://issues.apache.org/jira/browse/IGNITE-10547 > Project: Ignite > Issue Type: New Feature > Components: ml >Reporter: Yury Babak >Assignee: Alexey Platonov >Priority: Major > > Prepare several examples of GMM with/without fixed components number using > test sample generators and Kulback-Leibler distance. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Assigned] (IGNITE-10544) [ML] GMM with fixed components
[ https://issues.apache.org/jira/browse/IGNITE-10544?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov reassigned IGNITE-10544: Assignee: Alexey Platonov > [ML] GMM with fixed components > -- > > Key: IGNITE-10544 > URL: https://issues.apache.org/jira/browse/IGNITE-10544 > Project: Ignite > Issue Type: New Feature > Components: ml >Reporter: Yury Babak >Assignee: Alexey Platonov >Priority: Major > > For clusterization needs we need to implement EM-algorithm for GMM. > Related links: > # Gaussian [Mixture Model|https://en.wikipedia.org/wiki/Mixture_model] (GMM) > # > [EM-algorithm|https://en.wikipedia.org/wiki/Expectation%E2%80%93maximization_algorithm] -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11241) [ML] blas NoClassDefFoundError exception
Alexey Platonov created IGNITE-11241: Summary: [ML] blas NoClassDefFoundError exception Key: IGNITE-11241 URL: https://issues.apache.org/jira/browse/IGNITE-11241 Project: Ignite Issue Type: Bug Components: ml Affects Versions: 2.7, 2.6, 2.5, 2.4, 2.3, 2.2, 2.1, 2.0, 2.8 Reporter: Alexey Platonov Assignee: Alexey Platonov Fix For: 2.8 Caused by: java.lang.NoClassDefFoundError: org/netlib/blas/Dnrm2 at com.github.fommil.netlib.F2jBLAS.dnrm2(F2jBLAS.java:121) at org.apache.ignite.ml.math.isolve.lsqr.LSQROnHeap.lambda$bnorm$7b55d622$1(LSQROnHeap.java:53) at org.apache.ignite.ml.dataset.Dataset.lambda$computeWithCtx$96d91738$1(Dataset.java:143) at org.apache.ignite.ml.dataset.impl.cache.CacheBasedDataset.lambda$computeWithCtx$62946a87$1(CacheBasedDataset.java:112) at org.apache.ignite.ml.dataset.impl.cache.util.ComputeUtils.lambda$affinityCallWithRetries$b46c4136$1(ComputeUtils.java:90) at org.apache.ignite.internal.processors.closure.GridClosureProcessor$C2.execute(GridClosureProcessor.java:1855) at org.apache.ignite.internal.processors.job.GridJobWorker$2.call(GridJobWorker.java:568) at org.apache.ignite.internal.util.IgniteUtils.wrapThreadLoader(IgniteUtils.java:6816) at org.apache.ignite.internal.processors.job.GridJobWorker.execute0(GridJobWorker.java:562) ... 11 more -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-11232) [ML] Random Forest, NodeId exception (Failed to serialize object)
[ https://issues.apache.org/jira/browse/IGNITE-11232?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-11232: - Affects Version/s: 2.7 > [ML] Random Forest, NodeId exception (Failed to serialize object) > - > > Key: IGNITE-11232 > URL: https://issues.apache.org/jira/browse/IGNITE-11232 > Project: Ignite > Issue Type: Bug > Components: ml >Affects Versions: 2.7 >Reporter: Alexey Platonov >Assignee: Alexey Platonov >Priority: Major > Fix For: 2.7, 2.8 > > Time Spent: 50m > Remaining Estimate: 0h > > Caused by: class org.apache.ignite.IgniteCheckedException: Failed to > serialize object: IgniteBiTuple [val1=0, val2=1] > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedMarshaller.marshal0(OptimizedMarshaller.java:207) > at > > org.apache.ignite.marshaller.AbstractNodeNameAwareMarshaller.marshal(AbstractNodeNameAwareMarshaller.java:58) > at > org.apache.ignite.internal.util.IgniteUtils.marshal(IgniteUtils.java:10222) > at > > org.apache.ignite.internal.binary.BinaryWriterExImpl.marshal0(BinaryWriterExImpl.java:196) > ... 99 more > Caused by: java.io.IOException: Externalizable class doesn't have default > constructor: class org.apache.ignite.ml.tree.randomforest.data.NodeId > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedClassDescriptor.(OptimizedClassDescriptor.java:408) > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedMarshallerUtils.classDescriptor(OptimizedMarshallerUtils.java:210) > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedObjectOutputStream.writeObject0(OptimizedObjectOutputStream.java:201) > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedObjectOutputStream.writeObjectOverride(OptimizedObjectOutputStream.java:159) > at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:344) > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedMarshaller.marshal0(OptimizedMarshaller.java:202) > ... 102 more > Caused by: java.lang.NoSuchMethodException: > org.apache.ignite.ml.tree.randomforest.data.NodeId.() > at java.lang.Class.getConstructor0(Class.java:3082) > at java.lang.Class.getDeclaredConstructor(Class.java:2178) > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedClassDescriptor.(OptimizedClassDescriptor.java:403) > ... 107 more -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-11232) [ML] Random Forest, NodeId exception (Failed to serialize object)
[ https://issues.apache.org/jira/browse/IGNITE-11232?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-11232: - Fix Version/s: 2.7 > [ML] Random Forest, NodeId exception (Failed to serialize object) > - > > Key: IGNITE-11232 > URL: https://issues.apache.org/jira/browse/IGNITE-11232 > Project: Ignite > Issue Type: Bug > Components: ml >Reporter: Alexey Platonov >Assignee: Alexey Platonov >Priority: Major > Fix For: 2.7, 2.8 > > Time Spent: 50m > Remaining Estimate: 0h > > Caused by: class org.apache.ignite.IgniteCheckedException: Failed to > serialize object: IgniteBiTuple [val1=0, val2=1] > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedMarshaller.marshal0(OptimizedMarshaller.java:207) > at > > org.apache.ignite.marshaller.AbstractNodeNameAwareMarshaller.marshal(AbstractNodeNameAwareMarshaller.java:58) > at > org.apache.ignite.internal.util.IgniteUtils.marshal(IgniteUtils.java:10222) > at > > org.apache.ignite.internal.binary.BinaryWriterExImpl.marshal0(BinaryWriterExImpl.java:196) > ... 99 more > Caused by: java.io.IOException: Externalizable class doesn't have default > constructor: class org.apache.ignite.ml.tree.randomforest.data.NodeId > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedClassDescriptor.(OptimizedClassDescriptor.java:408) > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedMarshallerUtils.classDescriptor(OptimizedMarshallerUtils.java:210) > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedObjectOutputStream.writeObject0(OptimizedObjectOutputStream.java:201) > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedObjectOutputStream.writeObjectOverride(OptimizedObjectOutputStream.java:159) > at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:344) > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedMarshaller.marshal0(OptimizedMarshaller.java:202) > ... 102 more > Caused by: java.lang.NoSuchMethodException: > org.apache.ignite.ml.tree.randomforest.data.NodeId.() > at java.lang.Class.getConstructor0(Class.java:3082) > at java.lang.Class.getDeclaredConstructor(Class.java:2178) > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedClassDescriptor.(OptimizedClassDescriptor.java:403) > ... 107 more -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-11232) [ML] Random Forest, NodeId exception (Failed to serialize object)
[ https://issues.apache.org/jira/browse/IGNITE-11232?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-11232: - Fix Version/s: 2.8 > [ML] Random Forest, NodeId exception (Failed to serialize object) > - > > Key: IGNITE-11232 > URL: https://issues.apache.org/jira/browse/IGNITE-11232 > Project: Ignite > Issue Type: Bug > Components: ml >Reporter: Alexey Platonov >Assignee: Alexey Platonov >Priority: Major > Fix For: 2.8 > > Time Spent: 20m > Remaining Estimate: 0h > > Caused by: class org.apache.ignite.IgniteCheckedException: Failed to > serialize object: IgniteBiTuple [val1=0, val2=1] > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedMarshaller.marshal0(OptimizedMarshaller.java:207) > at > > org.apache.ignite.marshaller.AbstractNodeNameAwareMarshaller.marshal(AbstractNodeNameAwareMarshaller.java:58) > at > org.apache.ignite.internal.util.IgniteUtils.marshal(IgniteUtils.java:10222) > at > > org.apache.ignite.internal.binary.BinaryWriterExImpl.marshal0(BinaryWriterExImpl.java:196) > ... 99 more > Caused by: java.io.IOException: Externalizable class doesn't have default > constructor: class org.apache.ignite.ml.tree.randomforest.data.NodeId > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedClassDescriptor.(OptimizedClassDescriptor.java:408) > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedMarshallerUtils.classDescriptor(OptimizedMarshallerUtils.java:210) > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedObjectOutputStream.writeObject0(OptimizedObjectOutputStream.java:201) > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedObjectOutputStream.writeObjectOverride(OptimizedObjectOutputStream.java:159) > at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:344) > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedMarshaller.marshal0(OptimizedMarshaller.java:202) > ... 102 more > Caused by: java.lang.NoSuchMethodException: > org.apache.ignite.ml.tree.randomforest.data.NodeId.() > at java.lang.Class.getConstructor0(Class.java:3082) > at java.lang.Class.getDeclaredConstructor(Class.java:2178) > at > > org.apache.ignite.internal.marshaller.optimized.OptimizedClassDescriptor.(OptimizedClassDescriptor.java:403) > ... 107 more -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11234) [ML] Add fillCache method to DataStreamGenerator
Alexey Platonov created IGNITE-11234: Summary: [ML] Add fillCache method to DataStreamGenerator Key: IGNITE-11234 URL: https://issues.apache.org/jira/browse/IGNITE-11234 Project: Ignite Issue Type: Improvement Components: ml Reporter: Alexey Platonov Assignee: Alexey Platonov We need to add fillCache(sampleSize, cache) method to DataStreamGenerator for a more convenient interface in terms of cache filling + add example for such method. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11232) [ML] Random Forest, NodeId exception (Failed to serialize object)
Alexey Platonov created IGNITE-11232: Summary: [ML] Random Forest, NodeId exception (Failed to serialize object) Key: IGNITE-11232 URL: https://issues.apache.org/jira/browse/IGNITE-11232 Project: Ignite Issue Type: Bug Components: ml Reporter: Alexey Platonov Assignee: Alexey Platonov Caused by: class org.apache.ignite.IgniteCheckedException: Failed to serialize object: IgniteBiTuple [val1=0, val2=1] at org.apache.ignite.internal.marshaller.optimized.OptimizedMarshaller.marshal0(OptimizedMarshaller.java:207) at org.apache.ignite.marshaller.AbstractNodeNameAwareMarshaller.marshal(AbstractNodeNameAwareMarshaller.java:58) at org.apache.ignite.internal.util.IgniteUtils.marshal(IgniteUtils.java:10222) at org.apache.ignite.internal.binary.BinaryWriterExImpl.marshal0(BinaryWriterExImpl.java:196) ... 99 more Caused by: java.io.IOException: Externalizable class doesn't have default constructor: class org.apache.ignite.ml.tree.randomforest.data.NodeId at org.apache.ignite.internal.marshaller.optimized.OptimizedClassDescriptor.(OptimizedClassDescriptor.java:408) at org.apache.ignite.internal.marshaller.optimized.OptimizedMarshallerUtils.classDescriptor(OptimizedMarshallerUtils.java:210) at org.apache.ignite.internal.marshaller.optimized.OptimizedObjectOutputStream.writeObject0(OptimizedObjectOutputStream.java:201) at org.apache.ignite.internal.marshaller.optimized.OptimizedObjectOutputStream.writeObjectOverride(OptimizedObjectOutputStream.java:159) at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:344) at org.apache.ignite.internal.marshaller.optimized.OptimizedMarshaller.marshal0(OptimizedMarshaller.java:202) ... 102 more Caused by: java.lang.NoSuchMethodException: org.apache.ignite.ml.tree.randomforest.data.NodeId.() at java.lang.Class.getConstructor0(Class.java:3082) at java.lang.Class.getDeclaredConstructor(Class.java:2178) at org.apache.ignite.internal.marshaller.optimized.OptimizedClassDescriptor.(OptimizedClassDescriptor.java:403) ... 107 more -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11192) [ML] Use nd4j for matrix inversions and determinants
Alexey Platonov created IGNITE-11192: Summary: [ML] Use nd4j for matrix inversions and determinants Key: IGNITE-11192 URL: https://issues.apache.org/jira/browse/IGNITE-11192 Project: Ignite Issue Type: Improvement Components: ml Reporter: Alexey Platonov Assignee: Alexey Platonov >From optimization point of view we should use matrix inversions and >determinant computations of dl4j instead of own realization. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Resolved] (IGNITE-9745) [ML] Add Multinomial Naive Bayes
[ https://issues.apache.org/jira/browse/IGNITE-9745?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov resolved IGNITE-9745. - Resolution: Duplicate This logic was implemented in Ignite-9747 > [ML] Add Multinomial Naive Bayes > > > Key: IGNITE-9745 > URL: https://issues.apache.org/jira/browse/IGNITE-9745 > Project: Ignite > Issue Type: Sub-task > Components: ml >Reporter: Ravil Galeyev >Priority: Major > > Naive Bayes classifiers are a family of simple probabilistic classifiers > based on applying Bayes' theorem with strong (naive) independence assumptions > between the features. > So we want to add this algorithm to Apache Ignite ML module. > [Multinomial Naive > Bayes|http://scikit-learn.org/stable/modules/naive_bayes.html#multinomial-naive-bayes] > implements the naive Bayes algorithm for multinomially distributed data. > Requirements for successful PR: > # PartitionedDataset usage > # Trainer-Model paradigm support > # Tests for Model and for Trainer (and other stuff) > # Example of usage with a small, but a famous dataset like IRIS, Titanic or > House Prices > # Javadocs/codestyle according guidelines -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Comment Edited] (IGNITE-9979) [ML] Implement Naive Bayes classifier over Discrete Disctribution
[ https://issues.apache.org/jira/browse/IGNITE-9979?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16759672#comment-16759672 ] Alexey Platonov edited comment on IGNITE-9979 at 2/4/19 7:34 AM: - This logic was implemented in Ignite-9747 was (Author: aplatonov): This logic was implemented in Ignite-6878 > [ML] Implement Naive Bayes classifier over Discrete Disctribution > - > > Key: IGNITE-9979 > URL: https://issues.apache.org/jira/browse/IGNITE-9979 > Project: Ignite > Issue Type: Sub-task > Components: ml >Reporter: Alexey Platonov >Priority: Major > Labels: new-feature > Fix For: 2.8 > > > There is need to create Naive Bayes classifier over simple Discrete > Distribution for non-continuous features in dataset. As naive implementation > it may be set of histograms of feature values for each feature in dataset. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Resolved] (IGNITE-9979) [ML] Implement Naive Bayes classifier over Discrete Disctribution
[ https://issues.apache.org/jira/browse/IGNITE-9979?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov resolved IGNITE-9979. - Resolution: Duplicate This logic was implemented in Ignite-6878 > [ML] Implement Naive Bayes classifier over Discrete Disctribution > - > > Key: IGNITE-9979 > URL: https://issues.apache.org/jira/browse/IGNITE-9979 > Project: Ignite > Issue Type: Sub-task > Components: ml >Reporter: Alexey Platonov >Priority: Major > Labels: new-feature > Fix For: 2.8 > > > There is need to create Naive Bayes classifier over simple Discrete > Distribution for non-continuous features in dataset. As naive implementation > it may be set of histograms of feature values for each feature in dataset. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-11133) Refactoring of compatibility framework
Alexey Platonov created IGNITE-11133: Summary: Refactoring of compatibility framework Key: IGNITE-11133 URL: https://issues.apache.org/jira/browse/IGNITE-11133 Project: Ignite Issue Type: Improvement Reporter: Alexey Platonov Assignee: Alexey Platonov We need to refactor current compatibility framework with the aim of reducing maven management logic, simplification adding new versions to check. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-10793) [ML] Create comprehensive example for dataset generators
Alexey Platonov created IGNITE-10793: Summary: [ML] Create comprehensive example for dataset generators Key: IGNITE-10793 URL: https://issues.apache.org/jira/browse/IGNITE-10793 Project: Ignite Issue Type: Sub-task Components: ml Reporter: Alexey Platonov Assignee: Alexey Platonov Fix For: 2.8 We need to create well documented example for generators. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-10746) [ML] Participate in TensorFlow 2.0 preparation
[ https://issues.apache.org/jira/browse/IGNITE-10746?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-10746: - Affects Version/s: 2.7 > [ML] Participate in TensorFlow 2.0 preparation > -- > > Key: IGNITE-10746 > URL: https://issues.apache.org/jira/browse/IGNITE-10746 > Project: Ignite > Issue Type: Task > Components: ml >Affects Versions: 2.7 >Reporter: Anton Dmitriev >Assignee: Anton Dmitriev >Priority: Major > > The next TensorFlow releases starting from 2.0 introduce significant > structure changes: all code from contribution module will be moved into > separate sub-projects. Our "TensorFlow on Apache Ignite" integration code in > contribution module is also moving into so called "tensorflow/io" sub-project > (see [https://github.com/tensorflow/io]). > Almost all things related to this movement is already done by community > members. We need to check that "TensorFlow on Apache Ignite" is still working > after the movement, clarify details about "tensorflow/io" > review/build/publish procedures including Windows build which is not > supported so far. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-10746) [ML] Participate in TensorFlow 2.0 preparation
[ https://issues.apache.org/jira/browse/IGNITE-10746?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-10746: - Summary: [ML] Participate in TensorFlow 2.0 preparation (was: ML: Participate in TensorFlow 2.0 preparation) > [ML] Participate in TensorFlow 2.0 preparation > -- > > Key: IGNITE-10746 > URL: https://issues.apache.org/jira/browse/IGNITE-10746 > Project: Ignite > Issue Type: Task > Components: ml >Reporter: Anton Dmitriev >Assignee: Anton Dmitriev >Priority: Major > > The next TensorFlow releases starting from 2.0 introduce significant > structure changes: all code from contribution module will be moved into > separate sub-projects. Our "TensorFlow on Apache Ignite" integration code in > contribution module is also moving into so called "tensorflow/io" sub-project > (see [https://github.com/tensorflow/io]). > Almost all things related to this movement is already done by community > members. We need to check that "TensorFlow on Apache Ignite" is still working > after the movement, clarify details about "tensorflow/io" > review/build/publish procedures including Windows build which is not > supported so far. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Assigned] (IGNITE-10697) [ML] Add Frequency Encoding
[ https://issues.apache.org/jira/browse/IGNITE-10697?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov reassigned IGNITE-10697: Assignee: Aleksey Zinoviev (was: Alexey Platonov) > [ML] Add Frequency Encoding > --- > > Key: IGNITE-10697 > URL: https://issues.apache.org/jira/browse/IGNITE-10697 > Project: Ignite > Issue Type: New Feature > Components: ml >Affects Versions: 2.8 >Reporter: Aleksey Zinoviev >Assignee: Aleksey Zinoviev >Priority: Critical > Fix For: 2.8 > > > Encode the values to a fraction of all the labels. Can work with linear > models if the frequency is correlated with the target value. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Assigned] (IGNITE-10697) [ML] Add Frequency Encoding
[ https://issues.apache.org/jira/browse/IGNITE-10697?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov reassigned IGNITE-10697: Assignee: Alexey Platonov (was: Aleksey Zinoviev) > [ML] Add Frequency Encoding > --- > > Key: IGNITE-10697 > URL: https://issues.apache.org/jira/browse/IGNITE-10697 > Project: Ignite > Issue Type: New Feature > Components: ml >Affects Versions: 2.8 >Reporter: Aleksey Zinoviev >Assignee: Alexey Platonov >Priority: Critical > Fix For: 2.8 > > > Encode the values to a fraction of all the labels. Can work with linear > models if the frequency is correlated with the target value. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-10727) [ML] InfModel and Model merging
Alexey Platonov created IGNITE-10727: Summary: [ML] InfModel and Model merging Key: IGNITE-10727 URL: https://issues.apache.org/jira/browse/IGNITE-10727 Project: Ignite Issue Type: Improvement Components: ml Reporter: Alexey Platonov Assignee: Anton Dmitriev Fix For: 2.8 Currently "InfModel" and "Model" provide parallel architecture in terms of using of "InfModels" in after-learning steps like compositions, estimations etc. I propose to move "InfModel" to top of models hierarchy and rename it to just "Model" and current "Model" rename to "LearnedModel/LocalModel/Your_ad_may_be_here". So in this way "InfModel" will be just model with apply-function for generic I-O values and "Model" will be serializable thing on Vector-Double. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-10700) [ML] Working with Binary Objects
[ https://issues.apache.org/jira/browse/IGNITE-10700?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-10700: - Labels: (was: ml) > [ML] Working with Binary Objects > > > Key: IGNITE-10700 > URL: https://issues.apache.org/jira/browse/IGNITE-10700 > Project: Ignite > Issue Type: Improvement > Components: ml >Reporter: Yury Babak >Assignee: Yury Babak >Priority: Major > Fix For: 2.8 > > > Currently, we do not support working with caches which contains Binary > Objects, we should add support of building datasets from those objects. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-10700) [ML] Working with Binary Objects
[ https://issues.apache.org/jira/browse/IGNITE-10700?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-10700: - Component/s: ml > [ML] Working with Binary Objects > > > Key: IGNITE-10700 > URL: https://issues.apache.org/jira/browse/IGNITE-10700 > Project: Ignite > Issue Type: Improvement > Components: ml >Reporter: Yury Babak >Assignee: Yury Babak >Priority: Major > Fix For: 2.8 > > > Currently, we do not support working with caches which contains Binary > Objects, we should add support of building datasets from those objects. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-10700) [ML] Working with Binary Objects
[ https://issues.apache.org/jira/browse/IGNITE-10700?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-10700: - Labels: ml (was: ) > [ML] Working with Binary Objects > > > Key: IGNITE-10700 > URL: https://issues.apache.org/jira/browse/IGNITE-10700 > Project: Ignite > Issue Type: Improvement >Reporter: Yury Babak >Assignee: Yury Babak >Priority: Major > Labels: ml > Fix For: 2.8 > > > Currently, we do not support working with caches which contains Binary > Objects, we should add support of building datasets from those objects. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Assigned] (IGNITE-10543) [ML] Test/train sample generator
[ https://issues.apache.org/jira/browse/IGNITE-10543?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov reassigned IGNITE-10543: Assignee: Alexey Platonov > [ML] Test/train sample generator > > > Key: IGNITE-10543 > URL: https://issues.apache.org/jira/browse/IGNITE-10543 > Project: Ignite > Issue Type: New Feature > Components: ml >Reporter: Yury Babak >Assignee: Alexey Platonov >Priority: Major > > Need to design and implement sample generators for standard distributions and > user defined functions/points. It is useful for test regressions and > statistic package examples. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Assigned] (IGNITE-10542) [ML] Distributive models with basic algebra
[ https://issues.apache.org/jira/browse/IGNITE-10542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov reassigned IGNITE-10542: Assignee: Alexey Platonov > [ML] Distributive models with basic algebra > --- > > Key: IGNITE-10542 > URL: https://issues.apache.org/jira/browse/IGNITE-10542 > Project: Ignite > Issue Type: New Feature > Components: ml >Reporter: Yury Babak >Assignee: Alexey Platonov >Priority: Major > > We need to implement basic algebra for distributions fixture (adding and > removing components) -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-10548) [ML] Classificator based on GMM
[ https://issues.apache.org/jira/browse/IGNITE-10548?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-10548: - Description: Implement supervised learning over GMM. > [ML] Classificator based on GMM > --- > > Key: IGNITE-10548 > URL: https://issues.apache.org/jira/browse/IGNITE-10548 > Project: Ignite > Issue Type: New Feature > Components: ml >Reporter: Yury Babak >Priority: Major > > Implement supervised learning over GMM. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-10547) [ML] Examples of GMM usage
[ https://issues.apache.org/jira/browse/IGNITE-10547?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-10547: - Description: Prepare several examples of GMM with/without fixed components number using test sample generators and Kulback-Leibler distance. > [ML] Examples of GMM usage > -- > > Key: IGNITE-10547 > URL: https://issues.apache.org/jira/browse/IGNITE-10547 > Project: Ignite > Issue Type: New Feature > Components: ml >Reporter: Yury Babak >Priority: Major > > Prepare several examples of GMM with/without fixed components number using > test sample generators and Kulback-Leibler distance. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-10548) [ML] Classificator based on GMM
[ https://issues.apache.org/jira/browse/IGNITE-10548?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-10548: - Description: Implement supervised classifier learning over GMM. (was: Implement supervised learning over GMM.) > [ML] Classificator based on GMM > --- > > Key: IGNITE-10548 > URL: https://issues.apache.org/jira/browse/IGNITE-10548 > Project: Ignite > Issue Type: New Feature > Components: ml >Reporter: Yury Babak >Priority: Major > > Implement supervised classifier learning over GMM. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-10542) [ML] Distributive models with basic algebra
[ https://issues.apache.org/jira/browse/IGNITE-10542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-10542: - Description: We need to implement basic algebra for distributions fixture (adding and removing components) > [ML] Distributive models with basic algebra > --- > > Key: IGNITE-10542 > URL: https://issues.apache.org/jira/browse/IGNITE-10542 > Project: Ignite > Issue Type: New Feature > Components: ml >Reporter: Yury Babak >Priority: Major > > We need to implement basic algebra for distributions fixture (adding and > removing components) -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-10546) [ML] GMM with adding and removal of components
[ https://issues.apache.org/jira/browse/IGNITE-10546?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-10546: - Description: Improve fixed GMM by adding changeable number of components ability. > [ML] GMM with adding and removal of components > -- > > Key: IGNITE-10546 > URL: https://issues.apache.org/jira/browse/IGNITE-10546 > Project: Ignite > Issue Type: New Feature > Components: ml >Reporter: Yury Babak >Priority: Major > > Improve fixed GMM by adding changeable number of components ability. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-10545) [ML] Kullback–Leibler divergence
[ https://issues.apache.org/jira/browse/IGNITE-10545?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-10545: - Description: For comparing several distributions we need to implement such metric. [wiki link|https://en.wikipedia.org/wiki/Kullback%E2%80%93Leibler_divergence] was:[wiki link|https://en.wikipedia.org/wiki/Kullback%E2%80%93Leibler_divergence] > [ML] Kullback–Leibler divergence > > > Key: IGNITE-10545 > URL: https://issues.apache.org/jira/browse/IGNITE-10545 > Project: Ignite > Issue Type: New Feature > Components: ml >Reporter: Yury Babak >Priority: Major > > For comparing several distributions we need to implement such metric. > > [wiki link|https://en.wikipedia.org/wiki/Kullback%E2%80%93Leibler_divergence] -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-10543) [ML] Test/train sample generator
[ https://issues.apache.org/jira/browse/IGNITE-10543?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-10543: - Description: Need to design and implement sample generators for standard distributions and user defined functions/points. It is useful for test regressions and statistic package examples. > [ML] Test/train sample generator > > > Key: IGNITE-10543 > URL: https://issues.apache.org/jira/browse/IGNITE-10543 > Project: Ignite > Issue Type: New Feature > Components: ml >Reporter: Yury Babak >Priority: Major > > Need to design and implement sample generators for standard distributions and > user defined functions/points. It is useful for test regressions and > statistic package examples. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-10549) [ML] LogisticRegressionSGDTrainerTest fails with BLAS
Alexey Platonov created IGNITE-10549: Summary: [ML] LogisticRegressionSGDTrainerTest fails with BLAS Key: IGNITE-10549 URL: https://issues.apache.org/jira/browse/IGNITE-10549 Project: Ignite Issue Type: Bug Reporter: Alexey Platonov Assignee: Alexey Platonov LogisticRegressionSGDTrainerTest fails with BLAS on case with 3 partitions. Investigation is needed. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Commented] (IGNITE-10440) Analyse test suites for possible acceleration
[ https://issues.apache.org/jira/browse/IGNITE-10440?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16708638#comment-16708638 ] Alexey Platonov commented on IGNITE-10440: -- I guess that test above is not relevant for my commit and we can skip it > Analyse test suites for possible acceleration > - > > Key: IGNITE-10440 > URL: https://issues.apache.org/jira/browse/IGNITE-10440 > Project: Ignite > Issue Type: Improvement >Reporter: Alexey Platonov >Assignee: Alexey Platonov >Priority: Major > Labels: MakeTeamcityGreenAgain > -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-10517) [ML] Merge inference and learning architectures
[ https://issues.apache.org/jira/browse/IGNITE-10517?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-10517: - Issue Type: Improvement (was: Sub-task) Parent: (was: IGNITE-10479) > [ML] Merge inference and learning architectures > --- > > Key: IGNITE-10517 > URL: https://issues.apache.org/jira/browse/IGNITE-10517 > Project: Ignite > Issue Type: Improvement > Components: ml >Reporter: Alexey Platonov >Priority: Major > Fix For: 2.8 > > > We need to review of inference framework and try to merge it with core part > on ML library in terms of reusing imported models in all ML steps excluding > learning (model estimation, compositions etc.) -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-10517) [ML] Merge inference and learning architectures
Alexey Platonov created IGNITE-10517: Summary: [ML] Merge inference and learning architectures Key: IGNITE-10517 URL: https://issues.apache.org/jira/browse/IGNITE-10517 Project: Ignite Issue Type: Sub-task Components: ml Reporter: Alexey Platonov Fix For: 2.8 We need to review of inference framework and try to merge it with core part on ML library in terms of reusing imported models in all ML steps excluding learning (model estimation, compositions etc.) -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-10503) Meta information for vectors
Alexey Platonov created IGNITE-10503: Summary: Meta information for vectors Key: IGNITE-10503 URL: https://issues.apache.org/jira/browse/IGNITE-10503 Project: Ignite Issue Type: Improvement Components: ml Reporter: Alexey Platonov We need to design and implement vector meta-information like feature names, bagging information, etc -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Updated] (IGNITE-10503) [ML] Meta information for vectors
[ https://issues.apache.org/jira/browse/IGNITE-10503?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov updated IGNITE-10503: - Summary: [ML] Meta information for vectors (was: Meta information for vectors) > [ML] Meta information for vectors > - > > Key: IGNITE-10503 > URL: https://issues.apache.org/jira/browse/IGNITE-10503 > Project: Ignite > Issue Type: Improvement > Components: ml >Reporter: Alexey Platonov >Priority: Major > > We need to design and implement vector meta-information like feature names, > bagging information, etc -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Commented] (IGNITE-9902) ScanQuery doesn't take lost partitions into account
[ https://issues.apache.org/jira/browse/IGNITE-9902?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16702858#comment-16702858 ] Alexey Platonov commented on IGNITE-9902: - [~ibessonov] thank you for review, I pushed logger to assertion and I think we can merge this code. > ScanQuery doesn't take lost partitions into account > --- > > Key: IGNITE-9902 > URL: https://issues.apache.org/jira/browse/IGNITE-9902 > Project: Ignite > Issue Type: Bug >Reporter: Stanislav Lukyanov >Assignee: Alexey Platonov >Priority: Major > Time Spent: 8h > Remaining Estimate: 0h > > Same as IGNITE-9841, but about scan queries. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (IGNITE-10440) Analyse test suites for possible acceleration
Alexey Platonov created IGNITE-10440: Summary: Analyse test suites for possible acceleration Key: IGNITE-10440 URL: https://issues.apache.org/jira/browse/IGNITE-10440 Project: Ignite Issue Type: Improvement Reporter: Alexey Platonov Assignee: Alexey Platonov -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Commented] (IGNITE-9902) ScanQuery doesn't take lost partitions into account
[ https://issues.apache.org/jira/browse/IGNITE-9902?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16700536#comment-16700536 ] Alexey Platonov commented on IGNITE-9902: - [~ibessonov], thank you for advice, I didn't know about GridTestUtils#assertThrows with error message checking. I've reformatted code in according to your comment. > ScanQuery doesn't take lost partitions into account > --- > > Key: IGNITE-9902 > URL: https://issues.apache.org/jira/browse/IGNITE-9902 > Project: Ignite > Issue Type: Bug >Reporter: Stanislav Lukyanov >Assignee: Alexey Platonov >Priority: Major > Time Spent: 8h > Remaining Estimate: 0h > > Same as IGNITE-9841, but about scan queries. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Resolved] (IGNITE-9959) Set consistent id in tests
[ https://issues.apache.org/jira/browse/IGNITE-9959?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov resolved IGNITE-9959. - Resolution: Won't Fix > Set consistent id in tests > -- > > Key: IGNITE-9959 > URL: https://issues.apache.org/jira/browse/IGNITE-9959 > Project: Ignite > Issue Type: Improvement >Reporter: Alexey Platonov >Assignee: Alexey Platonov >Priority: Major > Labels: MakeTeamcityGreenAgain > Fix For: 2.8 > > > We need to set consistent id for starting nodes in tests -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Commented] (IGNITE-10193) IgniteBaselineAffinityTopologyActivationTest#testBaselineTopologyHistoryIsDeletedOnBaselineDelete fails asserting bltHist.history().size()
[
https://issues.apache.org/jira/browse/IGNITE-10193?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16696470#comment-16696470
]
Alexey Platonov commented on IGNITE-10193:
--
[~Jokser], yes I will. But it's very strange behavior because I just delete one
test)
> IgniteBaselineAffinityTopologyActivationTest#testBaselineTopologyHistoryIsDeletedOnBaselineDelete
> fails asserting bltHist.history().size()
> --
>
> Key: IGNITE-10193
> URL: https://issues.apache.org/jira/browse/IGNITE-10193
> Project: Ignite
> Issue Type: Bug
>Affects Versions: 2.6
>Reporter: Oleg Ignatenko
>Assignee: Alexey Platonov
>Priority: Major
> Labels: MakeTeamcityGreenAgain
>
> IgniteBaselineAffinityTopologyActivationTest#testBaselineTopologyHistoryIsDeletedOnBaselineDelete
> (in current codebase muted by renaming to
> {{_testBaselineTopologyHistoryIsDeletedOnBaselineDelete}}) fails. Test
> javadoc says: "Restore this test when requirements for BaselineTopology
> deletion are clarified and this feature is covered with more tests."
> (javadoc appears to be giving proper reason)
> Failure message: {noformat}
> junit.framework.AssertionFailedError:
> Expected :0
> Actual :2
> at junit.framework.Assert.fail(Assert.java:57)
> at junit.framework.Assert.failNotEquals(Assert.java:329)
> at junit.framework.Assert.assertEquals(Assert.java:78)
> at junit.framework.Assert.assertEquals(Assert.java:234)
> at junit.framework.Assert.assertEquals(Assert.java:241)
> at junit.framework.TestCase.assertEquals(TestCase.java:409)
> at
> org.apache.ignite.internal.processors.cache.persistence.IgniteBaselineAffinityTopologyActivationTest$17.verify(IgniteBaselineAffinityTopologyActivationTest.java:1041)
> at
> org.apache.ignite.internal.processors.cache.persistence.IgniteBaselineAffinityTopologyActivationTest.verifyBaselineTopologyHistoryOnNodes(IgniteBaselineAffinityTopologyActivationTest.java:693)
> at
> org.apache.ignite.internal.processors.cache.persistence.IgniteBaselineAffinityTopologyActivationTest.testBaselineTopologyHistoryIsDeletedOnBaselineDelete(IgniteBaselineAffinityTopologyActivationTest.java:1082)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:497)
> at junit.framework.TestCase.runTest(TestCase.java:176)
> at
> org.apache.ignite.testframework.junits.GridAbstractTest.runTestInternal(GridAbstractTest.java:2208)
> at
> org.apache.ignite.testframework.junits.GridAbstractTest.access$000(GridAbstractTest.java:144)
> at
> org.apache.ignite.testframework.junits.GridAbstractTest$5.run(GridAbstractTest.java:2124)
> at java.lang.Thread.run(Thread.java:745)
> {noformat}
> Snippet of code referred to from above message: {code}assertEquals(0,
> bltHist.history().size());{code}
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[jira] [Commented] (IGNITE-9959) Set consistent id in tests
[ https://issues.apache.org/jira/browse/IGNITE-9959?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16694426#comment-16694426 ] Alexey Platonov commented on IGNITE-9959: - new failed tests: [https://ci.ignite.apache.org/viewType.html?buildTypeId=IgniteTests24Java8_ComputeAffinityRun=%3Cdefault%3E=buildTypeStatusDiv] [https://ci.ignite.apache.org/project.html?projectId=IgniteTests24Java8=-8078436609482188163=%3Cdefault%3E=testDetails] [https://ci.ignite.apache.org/project.html?projectId=IgniteTests24Java8=-2339377680760862233=%3Cdefault%3E=testDetails] [https://ci.ignite.apache.org/project.html?projectId=IgniteTests24Java8=250837897303695090=%3Cdefault%3E=testDetails] for example: [https://ci.ignite.apache.org/viewLog.html?buildId=2363967=buildResultsDiv=IgniteTests24Java8_ComputeAffinityRun#testNameId5626617702600705182|https://ci.ignite.apache.org/viewLog.html?buildId=2364686=buildResultsDiv=IgniteTests24Java8_PdsCompatibility#testNameId-8078436609482188163] [https://ci.ignite.apache.org/viewLog.html?buildId=2367155=buildResultsDiv=IgniteTests24Java8_ComputeAffinityRun#testNameId-6470292966797814509] too many tests have similar problems - or some tests failed on destroyCache by ignite-node-id or some tests failed on after-test check for ignite nodes stopping it seems that consistentID setting shows some problems in test framework code on beforeTest-afterTest loop > Set consistent id in tests > -- > > Key: IGNITE-9959 > URL: https://issues.apache.org/jira/browse/IGNITE-9959 > Project: Ignite > Issue Type: Improvement >Reporter: Alexey Platonov >Assignee: Alexey Platonov >Priority: Major > Labels: MakeTeamcityGreenAgain > Fix For: 2.8 > > > We need to set consistent id for starting nodes in tests -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Assigned] (IGNITE-9902) ScanQuery doesn't take lost partitions into account
[ https://issues.apache.org/jira/browse/IGNITE-9902?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov reassigned IGNITE-9902: --- Assignee: Alexey Platonov > ScanQuery doesn't take lost partitions into account > --- > > Key: IGNITE-9902 > URL: https://issues.apache.org/jira/browse/IGNITE-9902 > Project: Ignite > Issue Type: Bug >Reporter: Stanislav Lukyanov >Assignee: Alexey Platonov >Priority: Major > > Same as IGNITE-9841, but about scan queries. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Reopened] (IGNITE-9959) Set consistent id in tests
[ https://issues.apache.org/jira/browse/IGNITE-9959?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexey Platonov reopened IGNITE-9959: - New failed tests (flaky) that not caught by visa bot > Set consistent id in tests > -- > > Key: IGNITE-9959 > URL: https://issues.apache.org/jira/browse/IGNITE-9959 > Project: Ignite > Issue Type: Improvement >Reporter: Alexey Platonov >Assignee: Alexey Platonov >Priority: Major > Labels: MakeTeamcityGreenAgain > Fix For: 2.8 > > > We need to set consistent id for starting nodes in tests -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Assigned] (IGNITE-10250) Ignite Queue hangs after several read/write operations
[
https://issues.apache.org/jira/browse/IGNITE-10250?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Alexey Platonov reassigned IGNITE-10250:
Assignee: (was: Alexey Platonov)
> Ignite Queue hangs after several read/write operations
> --
>
> Key: IGNITE-10250
> URL: https://issues.apache.org/jira/browse/IGNITE-10250
> Project: Ignite
> Issue Type: Bug
> Components: data structures
>Affects Versions: 2.7
>Reporter: Anton Dmitriev
>Priority: Major
>
> Ignite Queue hangs after several read/write operations. Code to reproduce:
> {code:java}
> try (Ignite ignite = Ignition.start()) {
> IgniteQueue queue = ignite.queue("TEST_QUEUE", 1, new
> CollectionConfiguration());
> new Thread(() -> {
> for (int i = 0;; i++) {
> queue.put(i);
> System.out.println("Put: " + i);
> }
> }).start();
> new Thread(() -> {
> for (int i = 0;; i++) {
> queue.take();
> System.out.println("Take: " + i);
> }
> }).start();
> Thread.currentThread().join();
> }
> {code}
>
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[jira] [Assigned] (IGNITE-10250) Ignite Queue hangs after several read/write operations
[
https://issues.apache.org/jira/browse/IGNITE-10250?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Alexey Platonov reassigned IGNITE-10250:
Assignee: Alexey Platonov
> Ignite Queue hangs after several read/write operations
> --
>
> Key: IGNITE-10250
> URL: https://issues.apache.org/jira/browse/IGNITE-10250
> Project: Ignite
> Issue Type: Bug
> Components: data structures
>Affects Versions: 2.7
>Reporter: Anton Dmitriev
>Assignee: Alexey Platonov
>Priority: Major
>
> Ignite Queue hangs after several read/write operations. Code to reproduce:
> {code:java}
> try (Ignite ignite = Ignition.start()) {
> IgniteQueue queue = ignite.queue("TEST_QUEUE", 1, new
> CollectionConfiguration());
> new Thread(() -> {
> for (int i = 0;; i++) {
> queue.put(i);
> System.out.println("Put: " + i);
> }
> }).start();
> new Thread(() -> {
> for (int i = 0;; i++) {
> queue.take();
> System.out.println("Take: " + i);
> }
> }).start();
> Thread.currentThread().join();
> }
> {code}
>
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[jira] [Assigned] (IGNITE-10193) IgniteBaselineAffinityTopologyActivationTest#testBaselineTopologyHistoryIsDeletedOnBaselineDelete fails asserting bltHist.history().size()
[
https://issues.apache.org/jira/browse/IGNITE-10193?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Alexey Platonov reassigned IGNITE-10193:
Assignee: Alexey Platonov
> IgniteBaselineAffinityTopologyActivationTest#testBaselineTopologyHistoryIsDeletedOnBaselineDelete
> fails asserting bltHist.history().size()
> --
>
> Key: IGNITE-10193
> URL: https://issues.apache.org/jira/browse/IGNITE-10193
> Project: Ignite
> Issue Type: Bug
>Affects Versions: 2.6
>Reporter: Oleg Ignatenko
>Assignee: Alexey Platonov
>Priority: Major
> Labels: MakeTeamcityGreenAgain
>
> IgniteBaselineAffinityTopologyActivationTest#testBaselineTopologyHistoryIsDeletedOnBaselineDelete
> (in current codebase muted by renaming to
> {{_testBaselineTopologyHistoryIsDeletedOnBaselineDelete}}) fails. Test
> javadoc says: "Restore this test when requirements for BaselineTopology
> deletion are clarified and this feature is covered with more tests."
> (javadoc appears to be giving proper reason)
> Failure message: {noformat}
> junit.framework.AssertionFailedError:
> Expected :0
> Actual :2
> at junit.framework.Assert.fail(Assert.java:57)
> at junit.framework.Assert.failNotEquals(Assert.java:329)
> at junit.framework.Assert.assertEquals(Assert.java:78)
> at junit.framework.Assert.assertEquals(Assert.java:234)
> at junit.framework.Assert.assertEquals(Assert.java:241)
> at junit.framework.TestCase.assertEquals(TestCase.java:409)
> at
> org.apache.ignite.internal.processors.cache.persistence.IgniteBaselineAffinityTopologyActivationTest$17.verify(IgniteBaselineAffinityTopologyActivationTest.java:1041)
> at
> org.apache.ignite.internal.processors.cache.persistence.IgniteBaselineAffinityTopologyActivationTest.verifyBaselineTopologyHistoryOnNodes(IgniteBaselineAffinityTopologyActivationTest.java:693)
> at
> org.apache.ignite.internal.processors.cache.persistence.IgniteBaselineAffinityTopologyActivationTest.testBaselineTopologyHistoryIsDeletedOnBaselineDelete(IgniteBaselineAffinityTopologyActivationTest.java:1082)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:497)
> at junit.framework.TestCase.runTest(TestCase.java:176)
> at
> org.apache.ignite.testframework.junits.GridAbstractTest.runTestInternal(GridAbstractTest.java:2208)
> at
> org.apache.ignite.testframework.junits.GridAbstractTest.access$000(GridAbstractTest.java:144)
> at
> org.apache.ignite.testframework.junits.GridAbstractTest$5.run(GridAbstractTest.java:2124)
> at java.lang.Thread.run(Thread.java:745)
> {noformat}
> Snippet of code referred to from above message: {code}assertEquals(0,
> bltHist.history().size());{code}
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[jira] [Assigned] (IGNITE-10199) unexpected result from QueryCursor.getAll() in IgniteSqlSplitterSelfTest#testMergeJoin
[
https://issues.apache.org/jira/browse/IGNITE-10199?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Alexey Platonov reassigned IGNITE-10199:
Assignee: (was: Alexey Platonov)
> unexpected result from QueryCursor.getAll() in
> IgniteSqlSplitterSelfTest#testMergeJoin
> --
>
> Key: IGNITE-10199
> URL: https://issues.apache.org/jira/browse/IGNITE-10199
> Project: Ignite
> Issue Type: Bug
> Components: sql
>Affects Versions: 2.6
>Reporter: Oleg Ignatenko
>Priority: Major
> Time Spent: 8h
> Remaining Estimate: 16h
>
> IgniteSqlSplitterSelfTest#testMergeJoin (in current codebase muted by
> renaming to {{_testMergeJoin}}) fails with message:
> {noformat}
> junit.framework.AssertionFailedError
> at junit.framework.Assert.fail(Assert.java:55)
> at junit.framework.Assert.assertTrue(Assert.java:22)
> at junit.framework.Assert.assertTrue(Assert.java:31)
> at junit.framework.TestCase.assertTrue(TestCase.java:201)
> at
> org.apache.ignite.internal.processors.query.IgniteSqlSplitterSelfTest.testMergeJoin(IgniteSqlSplitterSelfTest.java:182)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:497)
> at junit.framework.TestCase.runTest(TestCase.java:176)
> at
> org.apache.ignite.testframework.junits.GridAbstractTest.runTestInternal(GridAbstractTest.java:2208)
> at
> org.apache.ignite.testframework.junits.GridAbstractTest.access$000(GridAbstractTest.java:144)
> at
> org.apache.ignite.testframework.junits.GridAbstractTest$5.run(GridAbstractTest.java:2124)
> at java.lang.Thread.run(Thread.java:745)
> {noformat}
> Test code referred by above message is last assert in below snippet: {code}
> String qry = "select o1.* from Org o1, " +
> "(select max(o.name) as name, o.id from Org o group by o.id)
> o2 " +
> "where o1.id = o2.id";
> List> plan = c.query(new SqlFieldsQuery("explain " + qry)
> .setEnforceJoinOrder(true)).getAll();
> X.println("Plan: " + plan);
> String map0 = (String)plan.get(0).get(0);
> String map1 = (String)plan.get(1).get(0);
> String rdc = (String)plan.get(2).get(0);
> assertTrue(map0.contains("ORDER BY"));
> assertTrue(map1.contains("ORDER BY"));
> {code}
> Note git history appears to refer mute in [commit
> 58e57fd|https://github.com/apache/ignite/commit/70eed75422ea50a7bb9dbe539e2b9a62458e57fd].
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[jira] [Updated] (IGNITE-10199) unexpected result from QueryCursor.getAll() in IgniteSqlSplitterSelfTest#testMergeJoin
[
https://issues.apache.org/jira/browse/IGNITE-10199?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Alexey Platonov updated IGNITE-10199:
-
Component/s: sql
> unexpected result from QueryCursor.getAll() in
> IgniteSqlSplitterSelfTest#testMergeJoin
> --
>
> Key: IGNITE-10199
> URL: https://issues.apache.org/jira/browse/IGNITE-10199
> Project: Ignite
> Issue Type: Bug
> Components: sql
>Affects Versions: 2.6
>Reporter: Oleg Ignatenko
>Assignee: Alexey Platonov
>Priority: Major
> Time Spent: 8h
> Remaining Estimate: 16h
>
> IgniteSqlSplitterSelfTest#testMergeJoin (in current codebase muted by
> renaming to {{_testMergeJoin}}) fails with message:
> {noformat}
> junit.framework.AssertionFailedError
> at junit.framework.Assert.fail(Assert.java:55)
> at junit.framework.Assert.assertTrue(Assert.java:22)
> at junit.framework.Assert.assertTrue(Assert.java:31)
> at junit.framework.TestCase.assertTrue(TestCase.java:201)
> at
> org.apache.ignite.internal.processors.query.IgniteSqlSplitterSelfTest.testMergeJoin(IgniteSqlSplitterSelfTest.java:182)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:497)
> at junit.framework.TestCase.runTest(TestCase.java:176)
> at
> org.apache.ignite.testframework.junits.GridAbstractTest.runTestInternal(GridAbstractTest.java:2208)
> at
> org.apache.ignite.testframework.junits.GridAbstractTest.access$000(GridAbstractTest.java:144)
> at
> org.apache.ignite.testframework.junits.GridAbstractTest$5.run(GridAbstractTest.java:2124)
> at java.lang.Thread.run(Thread.java:745)
> {noformat}
> Test code referred by above message is last assert in below snippet: {code}
> String qry = "select o1.* from Org o1, " +
> "(select max(o.name) as name, o.id from Org o group by o.id)
> o2 " +
> "where o1.id = o2.id";
> List> plan = c.query(new SqlFieldsQuery("explain " + qry)
> .setEnforceJoinOrder(true)).getAll();
> X.println("Plan: " + plan);
> String map0 = (String)plan.get(0).get(0);
> String map1 = (String)plan.get(1).get(0);
> String rdc = (String)plan.get(2).get(0);
> assertTrue(map0.contains("ORDER BY"));
> assertTrue(map1.contains("ORDER BY"));
> {code}
> Note git history appears to refer mute in [commit
> 58e57fd|https://github.com/apache/ignite/commit/70eed75422ea50a7bb9dbe539e2b9a62458e57fd].
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