are java streams thread safe?
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3 Answers. There is no such thing as general thread safety or atomicity. ... A stream operation in itself is a purely local operation, this holds even for parallel stream operations, as the threads participating in that operation are unrelated to any other threads.
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The main reason that nulls aren't allowed in ConcurrentMaps (ConcurrentHashMaps, ConcurrentSkipListMaps) is that ambiguities that may be just barely tolerable in non-concurrent maps can't be accommodated. ... contains(key) , but in a concurrent one, the map might have changed between calls.
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Yes, sockets are thread-safe, however you have to be careful. ... Having multiple threads receiving data from a socket is usually fine for UDP socket, but doesn't make much sense for TCP sockets most of the time.
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Kafka Stream is the Streams API to transform, aggregate, and process records from a stream and produces derivative streams. Kafka Connect is the connector API to create reusable producers and consumers (e.g., stream of changes from DynamoDB).
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Thread safety guarantees. Intrusive containers have thread safety guarantees similar to STL containers. Several threads having read or write access to different instances is safe as long as inserted objects are different. Concurrent read-only access to the same container is safe.
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In fact, all collection classes (except Vector and Hashtable) in the java. util package are not thread-safe. ... That's why the new collections (List, Set, Map, etc) provide no concurrency control at all to provide maximum performance in single-threaded applications.
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5 Answers. If the JDBC driver is spec-compliant, then technically yes, the object is thread-safe, but you should avoid sharing connections between threads, since the activity on the connection will mean that only one thread will be able to do anything at a time.
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Filter streams {Processing stream} For additional functionality – altering or managing data in the stream. node stream is not the name of a class member of ObjectOutputStream , but it's rather a Stream instance, with which the class works internally.
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DbContext is not thread-safe You must never access your DbContext -derived instance from multiple threads simultaneously. This might result on multiple queries being sent concurrently over the same database connection. ... Any instance members are not guaranteed to be thread safe.
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flush() writes the content of the buffer to the destination and makes the buffer empty for further data to store but it does not closes the stream permanently. That means you can still write some more data to the stream. But close() closes the stream permanently.
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In case the data is not modified when shared between threads, the story is simple. The data has only to be initialized in the thread safe way. It is not necessary to use an expensive lock for each access. There are three ways in C++ to initialize variables in a thread safe way.
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A std::shared_ptr consists of a control block and its resource. Yes, the control block is thread-safe; but no, the access to the resource is not thread-safe. That means, modifying the reference counter is an atomic operation and you have the guarantee that the resource will be deleted exactly once.
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Fail-Fast iterators immediately throw ConcurrentModificationException if a collection is modified while iterating over it. Where as Fail-Safe iterators don't throw any exceptions if a collection is modified while iterating over it. Because, they operate on the clone of the collection, not on the actual collection.
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Parallel streams divide the provided task into many and run them in different threads, utilizing multiple cores of the computer. On the other hand sequential streams work just like for-loop using a single core. ... Parallel execution of streams run multiple iterations simultaneously in different available cores.
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Java memory models consider each array element as a separate variable. You may have thread-unsafe actions on such a variable just like any other variables. The array itself is quite thread safe. You may get incorrect results, or even unsensible results, or exceptions.
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4 Answers. It is never OK to read something possibly modified in a different thread without synchronization. What level of synchronization is needed depends on what you are actually reading. For primitive types, you should have a look at atomic reads, e.g. in the form of std::atomic<bool> .
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HashMap is non synchronized. It is not-thread safe and can't be shared between many threads without proper synchronization code whereas Hashtable is synchronized. ... HashMap allows one null key and multiple null values whereas Hashtable doesn't allow any null key or value.