Concurrency cookbook

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  • Over 60 simple but incredibly effective recipes for mastering multithreaded application development with Java 7 All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews. Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied.

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  • [ Team LiB ] Recipe 6.13 Implementing Pessimistic Concurrency Without Using Database Locks Problem You need the safety of pessimistic locking without the overhead of database locks. Solution Use extra columns and stored procedures as shown in the following examples.

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  • [ Team LiB ] Recipe 6.10 Checking for Concurrency Violations Problem You need to check for concurrency violations. Solution Use a timestamp column to manage data concurrency violations.

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  • We, NumPy users, live in exciting times. New NumPy-related developments seem to come to our attention every week or maybe even daily. When this book was being written, NumPy Foundation of Open Code for Usable Science was created. The Numba project—NumPy-aware, dynamic Python compiler using LLVM—was announced. Also, Google added support to their Cloud product Google App Engine. In the future, we can expect improved concurrency support for clusters of GPUs and CPUs. OLAP-like queries will be possible with NumPy arrays.

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