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Java 8 parallel streams
- 1. Java 8 ParallelStreams MASUD HASAN
- 2. What is stream A stream is not a collection , sequence , or a stream of objects A stream is an abstraction that holds zero or more values Not (necessarily) a collection : values might not be stored anywhere Not (necessarily) a sequence : order might not matter Values ,not objects : avoids mutation and side effects
- 3. Pipelines A streamsource Zero of more intermediate operations A terminal operation Collection.strteam() .filter(…) .map(…) .collect(…);
- 4. Parallel Streams Sourcesstart with stream(),parallelStream() or other stream factory Can be switched using parallel and sequential stream Parallel vs sequential is a property of the entire pipeline Can’t switch between parallel and sequential in the middle Last one wins Parallel makes it auto-magically go faster? NO collection().stream() .filter(...) .parallel() .map(...) .sequential() .collect(...) entire stream runs sequentially
- 5. Parallel stream considerations Parallel and sequential stream should give same result Parallelism leads to non determinism which is bad Encounter order vs processing order Stateful vs stateless : side effects Accumulation vs Reduction Reduction : Identity and associativity Explicit nondeterminism can speed things up Parallel has a overload , might also slow up things
- 6. Parallel vs sequential Sourceop1 op2 terminal op op1 op2 Source op1 op2 op1 op2 terminal op op1 op2
- 7. Encounter order vsprocessing order The ordering of the source determines the ordering in the result Processing order is non deterministic
- 8. Accumulation vs Reduction longsum = 0L; for (long i = 0; i <= 1_000_000L; i++) { sum += i; }
- 9. A better way: reduction 1+2+3+4+5+6+7+8 {1+2}+ {3+4} + {5+6} + {7+8} {3 + 7} + {11 + 15} {10 + 26} 36
- 10. Identity Value Thestarting value of each partition in parallel stream Becomes the result if the stream is empty The values must be correct must really a VALUE(immutable)
- 11. Associativity Reduction operationmust be associative in parallel stream
- 12. Where are threads Stream workload split and dispatched to the common-fork-join pool Control over concurrency is explicitly opaque in the api Common pool controlled by system properties
- 13. When go parallel Parallel stream has startup overload Typically 1000 misroseconds If you computation is shorter , do not even bother Consider parallel if N * Q >= 10,000 N = number of elements Q = cost per element Assumptions Element processing is idependent and source is spliatble
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