partitioning

We have large amount of data partitioned on year value using range partition in oracle. We have used range partition but each partition contains data only for one year. When we write a query targeting a specific year, oracle fetches the information from that partition but still checks if the year is what we have specified. Since this year column is not part of the index it fetches the year from table and compares it. We have seen that any time the query goes to fetch table data it is getting too slow. Can we somehow avoid oracle comparing the year values since we for sure know that the

I have an ordered 1-D array of numbers. Both the array length and the values of the numbers in the array are arbitrary. I want to partition the array into k partitions, according to the number values, e.g. let's say I want 4 partitions, distributed as 30% / 30% / 20% / 20%, i.e. the top 30% values first, the next 30% afterwards, etc. I get to choose k and the percentages of the distribution. In addition, if the same number appears more than once in the array, it should not be contained in two different partitions. This means that the distribution percentages above are not strict, but rather

Is the a way to physically separate between neo4j partitions? Meaning the following query will go to node1: Match (a:User:Facebook) While this query will go to another node (maybe hosted on docker) Match (b:User:Google) this is the case: i want to store data of several clients under neo4j, hopefully lots of them. now, i'm not sure about whats is the best design for that but it has to fulfill few conditions: no mixed data should be returned from a cypher query ( its really hard to make sure, that no developer will forget the ":Partition1" (for example) in a cypher query) performance of 1 client

I want to create a table like this. create table some_data ( id number(19,0), group_id number(19,0), value float, timestamp timestamp ); For this table i would like to have the data stored like group_id=1 jan-2015 feb-2015 ... group_id=2 jan-2015 feb-2015 ... and so on. So I assume i have to create a partition by range for the group_id and then a subpartition also by range with the timestamp column, right? So it should look like this: create table some_data ( id number(19,0), group_id number(19,0), value float, timestamp timestamp ) PARTITION BY RANGE (group_id) SUBPARTITION BY RANGE (

I'm trying to use PowerShell and WMI to remotely extend a C drive partition on Windows VMs running on VMware. These VM do not have WinRM enabled and that's not an option. What I'm trying to do is an equivalent of remotely managing an Active Directory computer object in an AD console to extend a partition, but in PowerShell. I'v already managed to pull partition informations through Win32 WMI objects but not yet the extension part. Does anyone know how to max out a C partition on a drive like that? Pre-requisites: PsExec from SysInternals Suite PowerShell 2.0 or greater for PowerShell modules

I want to find a combinatorial formula that given a certain number of integers, I can find the number of all possible groupings of these integers (such that all values belong to a single group) Say I have 3 integers, 1, 2, 3 There would be 5 groupings: 1 2 3 1|2|3| 1 2|3 1|2 3 2|1 3 I have calculated these computationally for N = 3 to 11, but I am trying to theoretically assertain. These values are: (I believe they are correct) num_integers num_groupings 3 5 4 15 5 52 6 203 7 877 8 4140 9 21147 10 115975 11 678570 The reason for doing this is to find the total number of partitionings of a

I am new to Hive and MapReduce and would really appreciate your answer and also provide a right approach. I have defined an external table logs in hive partitioned on date and origin server with an external location on hdfs /data/logs/ . I have a MapReduce job which fetches these logs file and splits them and stores under the folder mentioned above. Like "/data/logs/dt=2012-10-01/server01/" "/data/logs/dt=2012-10-01/server02/" ... ... From MapReduce job I would like add partitions to the table logs in Hive. I know the two approaches alter table command -- Too many alter table commands adding