## Uses of Interface
org.apache.ignite.IgniteCache

- Packages that use IgniteCache
  Package | Description
  --- | ---
  org.apache.ignite | Contains entry-point Ignite & HPC APIs.
  org.apache.ignite.ml.dataset | Base package for machine learning dataset classes.
  org.apache.ignite.ml.dataset.impl.cache | Base package for cache based implementation of machine learning dataset.
  org.apache.ignite.ml.inference.storage.descriptor | Root package for inference model descriptor storages.
  org.apache.ignite.ml.inference.storage.model | Root package for inference model storages.
  org.apache.ignite.ml.pipeline | Contains Pipeline API.
  org.apache.ignite.ml.preprocessing | Base package for machine learning preprocessing classes.
  org.apache.ignite.ml.selection.cv | Root package for cross-validation algorithms.
  org.apache.ignite.ml.selection.scoring.cursor | Util classes used for score calculation.
  org.apache.ignite.ml.selection.scoring.evaluator | Package for model evaluator classes.
  org.apache.ignite.ml.trainers | Contains model trainers.
  org.apache.ignite.ml.util.generators | Contains utility classes for data streams generation.
  org.apache.ignite.stream | Contains Ignite Streamer classes.

- - ### Uses of IgniteCache in org.apache.ignite

    Methods in org.apache.ignite that return IgniteCache
    Modifier and Type | Method and Description
    --- | ---
    `<K,V> IgniteCache<K,V>` | IgniteSpringBean.`cache(@Nullable String name)` Gets an instance of `IgniteCache` API for the given name if one is configured or `null` otherwise.
    `<K,V> IgniteCache<K,V>` | Ignite.`cache(String name)` Gets an instance of `IgniteCache` API for the given name if one is configured or `null` otherwise.
    `<K,V> IgniteCache<K,V>` | IgniteSpringBean.`createCache(CacheConfiguration<K,V> cacheCfg)` Dynamically starts new cache with the given cache configuration.
    `<K,V> IgniteCache<K,V>` | Ignite.`createCache(CacheConfiguration<K,V> cacheCfg)` Dynamically starts new cache with the given cache configuration.
    `<K,V> IgniteCache<K,V>` | IgniteSpringBean.`createCache(CacheConfiguration<K,V> cacheCfg, NearCacheConfiguration<K,V> nearCfg)` Dynamically starts new cache with the given cache configuration.
    `<K,V> IgniteCache<K,V>` | Ignite.`createCache(CacheConfiguration<K,V> cacheCfg, NearCacheConfiguration<K,V> nearCfg)` Dynamically starts new cache with the given cache configuration.
    `<K,V> IgniteCache<K,V>` | IgniteSpringBean.`createCache(String cacheName)` Dynamically starts new cache using template configuration.
    `<K,V> IgniteCache<K,V>` | Ignite.`createCache(String cacheName)` Dynamically starts new cache using template configuration.
    `<K,V> IgniteCache<K,V>` | IgniteSpringBean.`createNearCache(String cacheName, NearCacheConfiguration<K,V> nearCfg)` Starts a near cache on local node if cache was previously started with one of the `Ignite.createCache(CacheConfiguration)` or `Ignite.createCache(CacheConfiguration, NearCacheConfiguration)` methods.
    `<K,V> IgniteCache<K,V>` | Ignite.`createNearCache(String cacheName, NearCacheConfiguration<K,V> nearCfg)` Starts a near cache on local node if cache was previously started with one of the `Ignite.createCache(CacheConfiguration)` or `Ignite.createCache(CacheConfiguration, NearCacheConfiguration)` methods.
    `<K,V> IgniteCache<K,V>` | IgniteSpringBean.`getOrCreateCache(CacheConfiguration<K,V> cacheCfg)` Gets existing cache with the given name or creates new one with the given configuration.
    `<K,V> IgniteCache<K,V>` | Ignite.`getOrCreateCache(CacheConfiguration<K,V> cacheCfg)` Gets existing cache with the given name or creates new one with the given configuration.
    `<K,V> IgniteCache<K,V>` | IgniteSpringBean.`getOrCreateCache(CacheConfiguration<K,V> cacheCfg, NearCacheConfiguration<K,V> nearCfg)` Gets existing cache with the given cache configuration or creates one if it does not exist.
    `<K,V> IgniteCache<K,V>` | Ignite.`getOrCreateCache(CacheConfiguration<K,V> cacheCfg, NearCacheConfiguration<K,V> nearCfg)` Gets existing cache with the given cache configuration or creates one if it does not exist.
    `<K,V> IgniteCache<K,V>` | IgniteSpringBean.`getOrCreateCache(String cacheName)` Gets existing cache with the given name or creates new one using template configuration.
    `<K,V> IgniteCache<K,V>` | Ignite.`getOrCreateCache(String cacheName)` Gets existing cache with the given name or creates new one using template configuration.
    `<K,V> IgniteCache<K,V>` | IgniteSpringBean.`getOrCreateNearCache(@Nullable String cacheName, NearCacheConfiguration<K,V> nearCfg)` Gets existing near cache with the given name or creates a new one.
    `<K,V> IgniteCache<K,V>` | Ignite.`getOrCreateNearCache(String cacheName, NearCacheConfiguration<K,V> nearCfg)` Gets existing near cache with the given name or creates a new one.
    `<K1,V1> IgniteCache<K1,V1>` | IgniteCache.`withAllowAtomicOpsInTx()` By default atomic operations are allowed in transaction.
    `IgniteCache<K,V>` | IgniteCache.`withAsync()` Deprecated.
    `IgniteCache<K,V>` | IgniteCache.`withExpiryPolicy(javax.cache.expiry.ExpiryPolicy plc)` Returns cache with the specified expired policy set.
    `<K1,V1> IgniteCache<K1,V1>` | IgniteCache.`withKeepBinary()` Returns cache that will operate with binary objects.
    `IgniteCache<K,V>` | IgniteCache.`withNoRetries()`
    `IgniteCache<K,V>` | IgniteCache.`withPartitionRecover()` Gets an instance of `IgniteCache` that will be allowed to execute cache read operations regardless of partition loss policy.
    `IgniteCache<K,V>` | IgniteCache.`withReadRepair(ReadRepairStrategy strategy)` This is an experimental API.
    `IgniteCache<K,V>` | IgniteCache.`withSkipStore()`

    Methods in org.apache.ignite that return types with arguments of type IgniteCache
    Modifier and Type | Method and Description
    --- | ---
    `Collection<IgniteCache>` | IgniteSpringBean.`createCaches(Collection<CacheConfiguration> cacheCfgs)` Dynamically starts new caches with the given cache configurations.
    `Collection<IgniteCache>` | Ignite.`createCaches(Collection<CacheConfiguration> cacheCfgs)` Dynamically starts new caches with the given cache configurations.
    `Collection<IgniteCache>` | IgniteSpringBean.`getOrCreateCaches(Collection<CacheConfiguration> cacheCfgs)` Gets existing caches with the given name or created one with the given configuration.
    `Collection<IgniteCache>` | Ignite.`getOrCreateCaches(Collection<CacheConfiguration> cacheCfgs)` Gets existing caches with the given name or created one with the given configuration.

  - ### Uses of IgniteCache in org.apache.ignite.ml.dataset

    Methods in org.apache.ignite.ml.dataset with parameters of type IgniteCache
    Modifier and Type | Method and Description
    --- | ---
    `static <K,V,C extends Serializable,D extends AutoCloseable> Dataset<C,D>` | DatasetFactory.`create(Ignite ignite, IgniteCache<K,V> upstreamCache, LearningEnvironmentBuilder envBuilder, PartitionContextBuilder<K,V,C> partCtxBuilder, PartitionDataBuilder<K,V,C,D> partDataBuilder, LearningEnvironment environment)` Creates a new instance of distributed dataset using the specified `partCtxBuilder` and `partDataBuilder`.
    `static <K,V,C extends Serializable,D extends AutoCloseable> Dataset<C,D>` | DatasetFactory.`create(Ignite ignite, IgniteCache<K,V> upstreamCache, PartitionContextBuilder<K,V,C> partCtxBuilder, PartitionDataBuilder<K,V,C,D> partDataBuilder)` Creates a new instance of distributed dataset using the specified `partCtxBuilder` and `partDataBuilder`.
    `static <K,V,C extends Serializable,CO extends Serializable> SimpleDataset<C>` | DatasetFactory.`createSimpleDataset(Ignite ignite, IgniteCache<K,V> upstreamCache, LearningEnvironmentBuilder envBuilder, PartitionContextBuilder<K,V,C> partCtxBuilder, Preprocessor<K,V> featureExtractor)` Creates a new instance of distributed `SimpleDataset` using the specified `partCtxBuilder` and `featureExtractor`.
    `static <K,V,CO extends Serializable> SimpleDataset<EmptyContext>` | DatasetFactory.`createSimpleDataset(Ignite ignite, IgniteCache<K,V> upstreamCache, LearningEnvironmentBuilder envBuilder, Preprocessor<K,V> featureExtractor)` Creates a new instance of distributed `SimpleDataset` using the specified `featureExtractor`.
    `static <K,V,CO extends Serializable> SimpleDataset<EmptyContext>` | DatasetFactory.`createSimpleDataset(Ignite ignite, IgniteCache<K,V> upstreamCache, Preprocessor<K,V> featureExtractor)` Creates a new instance of distributed `SimpleDataset` using the specified `featureExtractor`.
    `static <K,V,C extends Serializable,CO extends Serializable> SimpleLabeledDataset<C>` | DatasetFactory.`createSimpleLabeledDataset(Ignite ignite, IgniteCache<K,V> upstreamCache, LearningEnvironmentBuilder envBuilder, PartitionContextBuilder<K,V,C> partCtxBuilder, Preprocessor<K,V> vectorizer)` Creates a new instance of distributed `SimpleLabeledDataset` using the specified `partCtxBuilder`, `featureExtractor` and `lbExtractor`.
    `static <K,V,CO extends Serializable> SimpleLabeledDataset<EmptyContext>` | DatasetFactory.`createSimpleLabeledDataset(Ignite ignite, LearningEnvironmentBuilder envBuilder, IgniteCache<K,V> upstreamCache, Preprocessor<K,V> vectorizer)` Creates a new instance of distributed `SimpleLabeledDataset` using the specified `featureExtractor` and `lbExtractor`.

  - ### Uses of IgniteCache in org.apache.ignite.ml.dataset.impl.cache

    Methods in org.apache.ignite.ml.dataset.impl.cache that return IgniteCache
    Modifier and Type | Method and Description
    --- | ---
    `IgniteCache<Integer,C>` | CacheBasedDataset.`getDatasetCache()`
    `IgniteCache<K,V>` | CacheBasedDataset.`getUpstreamCache()`
    `IgniteCache<K,V>` | CacheBasedDatasetBuilder.`getUpstreamCache()` Returns upstream cache.

    Constructors in org.apache.ignite.ml.dataset.impl.cache with parameters of type IgniteCache
    Constructor and Description
    `CacheBasedDataset(Ignite ignite, IgniteCache<K,V> upstreamCache, IgniteBiPredicate<K,V> filter, UpstreamTransformerBuilder upstreamTransformerBuilder, IgniteCache<Integer,C> datasetCache, LearningEnvironmentBuilder envBuilder, PartitionDataBuilder<K,V,C,D> partDataBuilder, UUID datasetId, boolean upstreamKeepBinary, LearningEnvironment localLearningEnv, int retriesCnt)` Constructs a new instance of dataset based on Ignite Cache, which is used as `upstream` and as reliable storage for partition `context` as well.
    `CacheBasedDataset(Ignite ignite, IgniteCache<K,V> upstreamCache, IgniteBiPredicate<K,V> filter, UpstreamTransformerBuilder upstreamTransformerBuilder, IgniteCache<Integer,C> datasetCache, LearningEnvironmentBuilder envBuilder, PartitionDataBuilder<K,V,C,D> partDataBuilder, UUID datasetId, boolean upstreamKeepBinary, LearningEnvironment localLearningEnv, int retriesCnt)` Constructs a new instance of dataset based on Ignite Cache, which is used as `upstream` and as reliable storage for partition `context` as well.
    `CacheBasedDatasetBuilder(Ignite ignite, IgniteCache<K,V> upstreamCache)` Constructs a new instance of cache based dataset builder that makes `CacheBasedDataset` with default predicate that passes all upstream entries to dataset.
    `CacheBasedDatasetBuilder(Ignite ignite, IgniteCache<K,V> upstreamCache, IgniteBiPredicate<K,V> filter)` Constructs a new instance of cache based dataset builder that makes `CacheBasedDataset`.
    `CacheBasedDatasetBuilder(Ignite ignite, IgniteCache<K,V> upstreamCache, IgniteBiPredicate<K,V> filter, UpstreamTransformerBuilder transformerBuilder)` Constructs a new instance of cache based dataset builder that makes `CacheBasedDataset`.
    `CacheBasedDatasetBuilder(Ignite ignite, IgniteCache<K,V> upstreamCache, IgniteBiPredicate<K,V> filter, UpstreamTransformerBuilder transformerBuilder, Boolean isKeepBinary, int retries)` Constructs a new instance of cache based dataset builder that makes `CacheBasedDataset`.

  - ### Uses of IgniteCache in org.apache.ignite.ml.inference.storage.descriptor

    Constructors in org.apache.ignite.ml.inference.storage.descriptor with parameters of type IgniteCache
    Constructor and Description
    `IgniteModelDescriptorStorage(IgniteCache<String,ModelDescriptor> models)` Constructs a new instance of Ignite model descriptor storage.

  - ### Uses of IgniteCache in org.apache.ignite.ml.inference.storage.model

    Constructors in org.apache.ignite.ml.inference.storage.model with parameters of type IgniteCache
    Constructor and Description
    `IgniteModelStorageProvider(IgniteCache<String,FileOrDirectory> cache)` Constructs a new instance of Ignite model storage provider.

  - ### Uses of IgniteCache in org.apache.ignite.ml.pipeline

    Methods in org.apache.ignite.ml.pipeline with parameters of type IgniteCache
    Modifier and Type | Method and Description
    --- | ---
    `PipelineMdl<K,V>` | Pipeline.`fit(Ignite ignite, IgniteCache<K,V> cache)` Fits the pipeline to the input cache.

  - ### Uses of IgniteCache in org.apache.ignite.ml.preprocessing

    Methods in org.apache.ignite.ml.preprocessing with parameters of type IgniteCache
    Modifier and Type | Method and Description
    --- | ---
    `default Preprocessor<K,V>` | PreprocessingTrainer.`fit(Ignite ignite, IgniteCache<K,V> cache, Preprocessor<K,V> basePreprocessor)` Fits preprocessor.
    `default Preprocessor<K,V>` | PreprocessingTrainer.`fit(LearningEnvironmentBuilder envBuilder, Ignite ignite, IgniteCache<K,V> cache, Preprocessor<K,V> basePreprocessor)` Fits preprocessor.

  - ### Uses of IgniteCache in org.apache.ignite.ml.selection.cv

    Methods in org.apache.ignite.ml.selection.cv with parameters of type IgniteCache
    Modifier and Type | Method and Description
    --- | ---
    `CrossValidation<M,K,V>` | CrossValidation.`withUpstreamCache(IgniteCache<K,V> upstreamCache)`

  - ### Uses of IgniteCache in org.apache.ignite.ml.selection.scoring.cursor

    Constructors in org.apache.ignite.ml.selection.scoring.cursor with parameters of type IgniteCache
    Constructor and Description
    `CacheBasedLabelPairCursor(IgniteCache<K,V> upstreamCache, IgniteBiPredicate<K,V> filter, Preprocessor<K,V> preprocessor, IgniteModel<Vector,L> mdl)` Constructs a new instance of cache based truth with prediction cursor.
    `CacheBasedLabelPairCursor(IgniteCache<K,V> upstreamCache, Preprocessor<K,V> preprocessor, IgniteModel<Vector,L> mdl)` Constructs a new instance of cache based truth with prediction cursor.

  - ### Uses of IgniteCache in org.apache.ignite.ml.selection.scoring.evaluator

    Methods in org.apache.ignite.ml.selection.scoring.evaluator with parameters of type IgniteCache
    Modifier and Type | Method and Description
    --- | ---
    `static <K,V> double` | Evaluator.`evaluate(IgniteCache<K,V> dataCache, IgniteBiPredicate<K,V> filter, IgniteModel<Vector,Double> mdl, Preprocessor<K,V> preprocessor, Metric metric)` Computes the given metric on the given cache.
    `static <K,V> double` | Evaluator.`evaluate(IgniteCache<K,V> dataCache, IgniteBiPredicate<K,V> filter, IgniteModel<Vector,Double> mdl, Preprocessor<K,V> preprocessor, MetricName metric)` Computes the given metric on the given cache.
    `static <K,V> double` | Evaluator.`evaluate(IgniteCache<K,V> dataCache, IgniteModel<Vector,Double> mdl, Preprocessor<K,V> preprocessor, Metric metric)` Computes the given metric on the given cache.
    `static <K,V> double` | Evaluator.`evaluate(IgniteCache<K,V> dataCache, IgniteModel<Vector,Double> mdl, Preprocessor<K,V> preprocessor, MetricName metric)` Computes the given metric on the given cache.
    `static <K,V> EvaluationResult` | Evaluator.`evaluateBinaryClassification(IgniteCache<K,V> dataCache, IgniteBiPredicate<K,V> filter, IgniteModel<Vector,Double> mdl, Preprocessor<K,V> preprocessor)` Evaluate binary classifier by default metrics (see package classification).
    `static <K,V> EvaluationResult` | Evaluator.`evaluateBinaryClassification(IgniteCache<K,V> dataCache, IgniteModel<Vector,Double> mdl, Preprocessor<K,V> preprocessor)` Evaluate binary classifier by default metrics (see package classification).
    `static <K,V> EvaluationResult` | Evaluator.`evaluateRegression(IgniteCache<K,V> dataCache, IgniteBiPredicate<K,V> filter, IgniteModel<Vector,Double> mdl, Preprocessor<K,V> preprocessor)` Evaluate regression by default metrics (see package regression).
    `static <K,V> EvaluationResult` | Evaluator.`evaluateRegression(IgniteCache<K,V> dataCache, IgniteModel<Vector,Double> mdl, Preprocessor<K,V> preprocessor)` Evaluate regression by default metrics (see package regression).

  - ### Uses of IgniteCache in org.apache.ignite.ml.trainers

    Methods in org.apache.ignite.ml.trainers with parameters of type IgniteCache
    Modifier and Type | Method and Description
    --- | ---
    `<K,V> M` | DatasetTrainer.`fit(Ignite ignite, IgniteCache<K,V> cache, IgniteBiPredicate<K,V> filter, Preprocessor<K,V> preprocessor)` Trains model based on the specified data.
    `<K,V> M` | DatasetTrainer.`fit(Ignite ignite, IgniteCache<K,V> cache, Preprocessor<K,V> preprocessor)` Trains model based on the specified data.
    `<K,V> M` | DatasetTrainer.`update(M mdl, Ignite ignite, IgniteCache<K,V> cache, IgniteBiPredicate<K,V> filter, Preprocessor<K,V> preprocessor)` Gets state of model in arguments, update in according to new data and return new model.
    `<K,V> M` | DatasetTrainer.`update(M mdl, Ignite ignite, IgniteCache<K,V> cache, Preprocessor<K,V> preprocessor)` Gets state of model in arguments, update in according to new data and return new model.

  - ### Uses of IgniteCache in org.apache.ignite.ml.util.generators

    Methods in org.apache.ignite.ml.util.generators with parameters of type IgniteCache
    Modifier and Type | Method and Description
    --- | ---
    `default <K> void` | DataStreamGenerator.`fillCacheWithCustomKey(int datasetSize, IgniteCache<K,LabeledVector<Double>> cache, Function<LabeledVector<Double>,K> keyMapper)` Fills given cache with labeled vectors from this generator and user defined mapper from vectors to keys.
    `default void` | DataStreamGenerator.`fillCacheWithVecHashAsKey(int datasetSize, IgniteCache<Integer,LabeledVector<Double>> cache)` Fills given cache with labeled vectors from this generator as values and their hashcodes as keys.
    `default void` | DataStreamGenerator.`fillCacheWithVecUUIDAsKey(int datasetSize, IgniteCache<UUID,LabeledVector<Double>> cache)` Fills given cache with labeled vectors from this generator as values and random UUIDs as keys

  - ### Uses of IgniteCache in org.apache.ignite.stream

    Methods in org.apache.ignite.stream with parameters of type IgniteCache
    Modifier and Type | Method and Description
    --- | ---
    `void` | StreamTransformer.`receive(IgniteCache<K,V> cache, Collection<Map.Entry<K,V>> entries)` Updates cache with batch of entries.
    `void` | StreamReceiver.`receive(IgniteCache<K,V> cache, Collection<Map.Entry<K,V>> entries)` Updates cache with batch of entries.
    `void` | StreamVisitor.`receive(IgniteCache<K,V> cache, Collection<Map.Entry<K,V>> entries)` Updates cache with batch of entries.

    Method parameters in org.apache.ignite.stream with type arguments of type IgniteCache
    Modifier and Type | Method and Description
    --- | ---
    `static <K,V> StreamVisitor<K,V>` | StreamVisitor.`from(IgniteBiInClosure<IgniteCache<K,V>,Map.Entry<K,V>> c)` Creates a new visitor based on instance of `IgniteBiInClosure`.

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Ignite Database and Caching Platform | : ver. 2.13.0
Release Date | : April 20 2022