berkeley-db

问题 I would like to ask a fundamental question about when is it useful to use a system call like fsync. I am beginner and i was always under the impression that write is enough to write to a file, and samples that use write actually write to the file at the end. So what is the purpose of a system call like fsync? Just to provide some background i am using Berkeley DB library version 5.1.19 and there is a lot of talk around the cost of fsync() vs just writing. That is the reason i am wondering.

问题 I would like to ask a fundamental question about when is it useful to use a system call like fsync. I am beginner and i was always under the impression that write is enough to write to a file, and samples that use write actually write to the file at the end. So what is the purpose of a system call like fsync? Just to provide some background i am using Berkeley DB library version 5.1.19 and there is a lot of talk around the cost of fsync() vs just writing. That is the reason i am wondering.

问题 Is it safe for multiple computers to concurrently access an svn repository stored on a shared filesystem? I'm building an application in which each Windows client machine has a local working set of files, and can periodically synchronize with the rest of the team. From a server standpoint, I'd like to rely on nothing except a Windows shared mount point. Does the svn file:// URL protocol support shared filesystems, or does it assume that the filesystem is local? The Subversion docs mention

问题 I just started playing with Berkeley DB a few days ago so I'm trying to see if there's something I've been missing when it comes to storing data as fast as possible. Here's some info about the data: - it comes in 512 byte chunks - chunks come in order - chunks will be deleted in FIFO order - if i lose some data off the end because of power failure that's ok as long as the whole db isn't broken After reading the a bunch of the documentation it seemed like a Queue db was exactly what I wanted.

问题 I just started playing with Berkeley DB a few days ago so I'm trying to see if there's something I've been missing when it comes to storing data as fast as possible. Here's some info about the data: - it comes in 512 byte chunks - chunks come in order - chunks will be deleted in FIFO order - if i lose some data off the end because of power failure that's ok as long as the whole db isn't broken After reading the a bunch of the documentation it seemed like a Queue db was exactly what I wanted.

问题 I just started playing with Berkeley DB a few days ago so I'm trying to see if there's something I've been missing when it comes to storing data as fast as possible. Here's some info about the data: - it comes in 512 byte chunks - chunks come in order - chunks will be deleted in FIFO order - if i lose some data off the end because of power failure that's ok as long as the whole db isn't broken After reading the a bunch of the documentation it seemed like a Queue db was exactly what I wanted.

问题 I just started playing with Berkeley DB a few days ago so I'm trying to see if there's something I've been missing when it comes to storing data as fast as possible. Here's some info about the data: - it comes in 512 byte chunks - chunks come in order - chunks will be deleted in FIFO order - if i lose some data off the end because of power failure that's ok as long as the whole db isn't broken After reading the a bunch of the documentation it seemed like a Queue db was exactly what I wanted.

问题 I just started playing with Berkeley DB a few days ago so I'm trying to see if there's something I've been missing when it comes to storing data as fast as possible. Here's some info about the data: - it comes in 512 byte chunks - chunks come in order - chunks will be deleted in FIFO order - if i lose some data off the end because of power failure that's ok as long as the whole db isn't broken After reading the a bunch of the documentation it seemed like a Queue db was exactly what I wanted.

问题 We are using BerkeleyDB Java edition, core api to read/write cdrfiles, we are having a problem with log files. When we are writing 9lack records to database then multiples log files are created with huge sizes, 1.08gb . We want to know why multiple logfiles are created while using transaction , is it due to every commit statement after writing data to database ? or is there any other reason ? 回答1: This is normal. The log files contains ongoing tranactions, as well as information you can use

问题 I'm building an application that requires Berkeley DB (http://www.resiprocate.org). I am building on OS X, and I had to install Berkeley DB since the machine did not already have it. However, the reSIProcate package I am trying to build cannot find the db_cxx library ( -ldb_cxx ). The installed Berkeley DB lib directory only has the following files: libdb-5.3.a libdb-5.3.dylib libdb-5.4.la libdb.a What exactly is db_cxx ...is -ldb_cxx outdated? Or is there some option I need to specify when