{"componentChunkName":"component---node-modules-carrotsearch-gatsby-theme-apidocs-templates-documentation-page-js","path":"/java-concurrency/","result":{"data":{"html":{"frontmatter":{"id":"java-concurrency","title":"Concurrency"},"html":"
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Concurrency

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\n If you intend to run Lingo3G clustering in parallel threads, make sure your\n code follows the concurrency guidelines outlined in this article.\n

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\n Thread-safety\n

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\n Lingo3G Java API follows the following contracts with respect to\n thread-safety:\n

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\n In other words, if your code needs to cluster data in parallel threads,\n each thread should \"own\" its own\n Lingo3GClusteringAlgorithm instance. All threads should reuse\n the sameLanguageComponent instance loaded beforehand.\n

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\n The following sections show two approaches to configuring Lingo3G\n algorithm instance once and then reusing it in subsequent, possibly\n concurrent, clustering calls.\n

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\n Ephemeral instances\n

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\n The simplest way to ensure thread-safety is to create and configure a\n Lingo3GClusteringAlgorithm\n instance on the fly and discard it after the clustering completes.\n

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\n The following example defines a function that transforms a stream of\n documents into a list of clusters:\n

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// Load one language components instance for sharing among all parallel threads.\nLanguageComponents english = LanguageComponents.loader().load().language(\"English\");\n\n// Document stream -> cluster list function.\nFunction<Stream<Document>, List<Cluster<Document>>> processor =\n    (documentStream) -> {\n      // Algorithm instances are created per-call (per-thread)\n      Lingo3GClusteringAlgorithm algorithm = new Lingo3GClusteringAlgorithm();\n\n      // ...configured in place\n      algorithm.documents.phraseDfThresholdScalingFactor.set(0.1);\n      algorithm.hierarchy.maxHierarchyDepth.set(1);\n\n      // and discarded once clustering call completes.\n      return algorithm.cluster(documentStream, english);\n    };\n\nrunConcurrentClustering(processor);
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\n Calling clustering in multiple threads using disposable clustering\n algorithm instances in Java API.\n

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\n Note that the code loads a LanguageComponents instance once\n and then shares it among all parallel threads for reuse.\n

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\n Cloning preconfigured instances\n

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\n If the configuration of your Lingo3GClusteringAlgorithm\n instance is complex or you would like to decouple it from the actual\n clustering, your code can do the following:\n

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    \n Create and configure a \"blueprint\"\n Lingo3GClusteringAlgorithm\n instance.\n

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    \n Use the Attrs.toMap method to convert the \"blueprint\"\n instance into a Map for sharing among concurrent threads.\n

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    \n In each thread, use the Attrs.fromMap method to create a\n clone of the \"blueprint\" instance.\n

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    4. \n
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The following example demonstrates this approach:

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// Apply any configuration tweaks once.\nLingo3GClusteringAlgorithm preconfigured = new Lingo3GClusteringAlgorithm();\npreconfigured.documents.phraseDfThresholdScalingFactor.set(0.1);\npreconfigured.hierarchy.maxHierarchyDepth.set(1);\n\n// Populate the map with algorithm and its attributes.\nMap<String, Object> attrs = Attrs.toMap(preconfigured);\n\n// Reuse the previously populated map to create a new cloned instance.\nFunction<Stream<Document>, List<Cluster<Document>>> processor =\n    (documentStream) -> {\n      Lingo3GClusteringAlgorithm cloned;\n      cloned = Attrs.fromMap(Lingo3GClusteringAlgorithm.class, attrs);\n      return cloned.cluster(documentStream, english);\n    };\n\nrunConcurrentClustering(processor);
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\n Calling clustering in multiple threads by cloning a preconfigured\n clustering algorithm instance in Java API.\n

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\n Note that the parallel threads do not use the \"blueprint\" instance\n directly as it is not thread-safe. Instead, they create a disposable clone\n for each clustering call.\n

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","tableOfContents":[{"heading":"Thread-safety","anchor":"thread-safety"},{"heading":"Ephemeral instances","anchor":"ephemeral-instances"},{"heading":"Cloning preconfigured instances","anchor":"cloning"}]}},"pageContext":{"slug":"/java-concurrency/"}},"staticQueryHashes":["1164750013"]}