key-value

Other than MongoDB and Memcached, what key-value stores run on Windows? Most of the ones I've seen seem to only run on Linux (Hypertable, Redis, Lightcloud). Related links: Is there a business proven cloud store / Key=>Value Database? (Open Source) http://www.metabrew.com/article/anti-rdbms-a-list-of-distributed-key-value-stores/ I would take a look at this article from highscalability.com . It describes a few options that you may want to consider, including Tokyo Cabinet/Tyrant , CouchDB and MongoDB . Berkeley DB is available . I'm surprised no-one has mentioned it yet. You can build it on

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I'm looking for suggestions regarding in-memory key-value store engines or libraries, that have C++ interfaces or that are written in C++. I'm looking for solutions that can scale without any problems to about 100mill key-value pairs and that are compatible/compilable on linux and win32/64 回答1: How about std::map ? http://cplusplus.com/reference/stl/map/ 回答2: If you really need to store such amount of pairs in memory consider this Sparse Hash . It has special implementation which is optimized for low memory consumption. 回答3: i think storing

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I have a DynamoDB attribute whose value is a map from a Number to a String. I am trying to put in a new key-value pair. From what I've read, this seems to be possible, but I don't know how. I assume the solution is similar to the one in the link below: How to update a Map or a List on AWS DynamoDB document API? But I do not believe the example is on putting in a new item to a map. Could someone show me how to put in an item to a map? Thanks. EDIT: I do not want to get the item, locally make the changes, and put it back. I am working with

I'm looking for a way to get all the information out of localStorage. The trouble I'm having is I don't know what the data will be as it is user generated. So here what happens, a user inputs some text, it uses javascript to manipulate it depending on what check boxes they have ticked on the input form. these boxes are for symbols for example if they tick the box for @ then the text + the @At (symbol then word) will be placed in local storage with the other half of the pair as a Boolean (1 or 0 in this case) representing whether its been checked. the exact pair would look like this: someString

I have question about the KeyEventArgs 's KeyCode and KeyData and KeyValue . KeyCode and Keydata are Keys type, but I don't know what the difference between them is. For KeyValue , I don't know what it is -- it has an int type, does it return the char value of the pressed key? I don't have much experience with Key events; any explanation of how they function and how to use them would be greatly appreciated. KeyCode contains data for the key that produced the KeyUp or KeyDown event. KeyData contains the combination of that key together with CTRL, SHIFT or ALT if any of those were pressed.

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: Normally, we write the mapper in the form : public static class Map extends Mapper Here the input key-value pair for the mapper is - as far as I know when the mapper gets the input data its goes through line by line - so the Key for the mapper signifies the line number - please correct me if I am wrong. My question is : If I give the input key-value pair for mapper as then it is giving the error java.lang.ClassCastException: org.apache.hadoop.io.LongWritable cannot be cast to org.apache.hadoop.io.Text Is it a mandatory to give the input key

var map = {}; map['key1'] = 1; map['key2@'] = 2; console.log(map['key1']);//结果是1. console.log(map['key2@']);//结果是2. //如果遍历map for(var prop in map){ if(map.hasOwnProperty(prop)){ console.log('key is ' + prop +' and value is' + map[prop]); } } 文章来源: JS中key-value存取

Spark算子大致上可分为三大类算子： 1、mapValues mapValues是针对[K,V]中对V的值进行map 2、combineByKey 使用用户设置好的聚合函数对每个Key中对Value进行组合(combine)，可以将输入类型为 RDD[(K,V)] 转成RDD[(K,C)] 3、reduceByKey 对元素为KV对的RDD中Key相同对元素对Value进行binary_function的reduce操作，因此Key相同的多个元素的值被reduce为一个值，然后与原RDD中的Key组成一个新的KV对 4、partitionBy 对RDD进行分区操作 5、cogroup cogroup指对两个RDD中对KV元素，每个RDD中相同Key中对元素中的元素分别聚合成一个集合 6、join 对两个需要连接对RDD进行cogroup函数操作 7、leftOutJoin 8、rightOutJoin 文章来源: Spark中RDD的Key-Value型Transformation算子操作（二）

Spark算子大致上可分为三大类算子： Value数据类型的Transformation算子，这种变换不触发提交作业，针对处理的数据项是Value型的数据。 Key-Value数据类型的Transformation算子，这种变换不触发提交作业，针对处理的数据项是Key-Value型的数据。 Action算子，这类算子会触发SparkContext提交作业。 1、mapValues mapValues是针对[K,V]中对V的值进行map 2、combineByKey 使用用户设置好的聚合函数对每个Key中对Value进行组合(combine)，可以将输入类型为 RDD[(K,V)] 转成RDD[(K,C)] 3、reduceByKey 对元素为KV对的RDD中Key相同对元素对Value进行binary_function的reduce操作，因此Key相同的多个元素的值被reduce为一个值，然后与原RDD中的Key组成一个新的KV对 4、partitionBy 对RDD进行分区操作 5、cogroup cogroup指对两个RDD中对KV元素，每个RDD中相同Key中对元素中的元素分别聚合成一个集合 6、join 对两个需要连接对RDD进行cogroup函数操作 7、leftOutJoin 8、rightOutJoin 转载请标明出处: Spark中RDD的Key