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At an extreme level, this would include preventing the user from accessing a shell altogether, as well as access to AppleScript capabilities If the user must absolutely have shell access, an alternative approach would be to utilize OS X sandboxing to restrict access to certain CLI utilities: most notably /bin/ls, but also also interpreted runtimes such as Python, Perl, PHP, or Ruby Utilizing sandbox technology to protect an OS X environment is covered in detail in 6..



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You should not look toward partitions as a way to massively improve query performance in an OLTP system In fact, in a traditional OLTP system, you must apply partitioning with care so as to not negatively affect runtime performance In a traditional OLTP system, most queries are expected to return virtually instantaneously, and most of the retrievals from the database are expected to be via very small index range scans Therefore, the main performance benefits of partitioning listed previously would not come into play Partition elimination is useful where you have full scans of large objects, because it allows you to avoid full scanning large pieces of an object However, in an OLTP environment, you are not full scanning large objects (if you are, you have a serious design flaw).





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If you are reading this book we assume you have sensitive data to protect, and if so, you might want to consider routinely auditing your file system permissions Earlier in this chapter, we learned of the dangers that can be had when permissions are poorly applied An inadvertent write mode granted to a directory containing executables means that a malicious user can inject his own, executables, thereby granting him the ability to further exploit your system The suid bit, when granted to an insecure program, can lead to a user subverting the program and gaining complete control of your box If an executable must be suid to function, then there s not much you can do with POSIX or ACL permissions to prevent damage To protect against such a scenario, consider Sandboxing your program, as discussed later on in this book, 6.

Even if you partition your indexes, any increase in performance achieved by scanning a smaller index will be miniscule if you actually achieve an increase in speed at all If some of your queries use an index and they cannot eliminate all but one partition from consideration, you may find your queries actually run slower after partitioning since you now have 5, 10, or 20 small indexes to probe, instead of one larger index We will investigate this in much more detail later when we look at the types of partitioned indexes available to us Having said all this, there are opportunities to gain efficiency in an OLTP system with partitions For example, they may be used to increase concurrency by decreasing contention They can be used to spread the modifications of a single table out over many physical partitions.

Instead of having a single table segment with a single index segment, you might have 20 table partitions and 20 index partitions It could be like having 20 tables instead of 1, hence contention would be decreased for this shared resource during modifications As for parallel operations, as we ll investigate in more detail in the next chapter Parallel Execution, you do not want to do a parallel query in an OLTP system You would reserve your use of parallel operations for the DBA to perform rebuilds, create indexes, gather statistics, and so on The fact is that in an OLTP system, your queries should already be characterized by very fast index accesses, and partitioning will not speed that up very much, if at all This does not mean that you should avoid partitioning for OLTP; it means that you shouldn t expect partitioning to offer massive improvements in performance.

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