partitioning

Obtaining nice cuts in Hmisc with cut2 (without the [ ) signs )

由 佐手、 提交于 2019-12-07 13:22:55
问题 I'm currently trying to neatly cut data with use of the Hmisc package, as in the example below: dummy <- data.frame(important_variable=seq(1:1000)) require(Hmisc) dummy$cuts <- cut2(dummy$important_variable, g = 4) The produced cuts are correct with respect to the values: important_variable cuts 1 1 [ 1, 251) 2 2 [ 1, 251) 3 3 [ 1, 251) 4 4 [ 1, 251) 5 5 [ 1, 251) 6 6 [ 1, 251) > table(dummy$cuts) [ 1, 251) [251, 501) [501, 751) [751,1000] 250 250 250 250 However, I would like for the data to

How to efficiently cluster voxel space into the fewest number of similar, contiguous blocks possible?

由 安稳与你 提交于 2019-12-07 08:44:42
问题 I am doing some research into how feasible it is to use voxels to represent largish (256x256x256 voxels) battlegrounds with destructible terrain for server-hosted multiplayer games. Only one battleground will exist for any game at a time. However, to be able to broadcast rooms and changes to their terrain, I am trying to find an algorithm that can group the voxels into the fewest rectangular blocks as possible. As a simplistic example, if the bottom half of the level was completely filled

#1016 - Can't open file: './database_name/#sql-38f_36aa.frm' (errno: 24)

由 孤街浪徒 提交于 2019-12-06 22:54:29
问题 I have table in mysql with MyISAM storage engine. I want to create partition on a particular table, for this I am executing the query - alter table Stops PARTITION BY KEY(`stop_id`) PARTITIONS 200 Where 'stop_id' is type of varchar. While executing the above query I am getting the error - #1016 - Can't open file: './database_name/#sql-38f_36aa.frm' (errno: 24) Can anybody please help me to resolve this problem? Thank You. 回答1: From here and here. errno: 24 means that too many files are open

Algorithm to partition a string into substrings including null partitions

由 Deadly 提交于 2019-12-06 16:08:46
问题 The problem: Let P be the set of all possible ways of partitioning string s into adjacent and possibly null substrings. I'm looking for an elegant algorithm to solve this problem. Background context: Given a tuple of strings (s, w), define P(s) and P(w) as above. There exists a particular partition R ∈ P(s) and T ∈ P(w) that yields the least number of substring Levenshtein (insertion, deletion and substitution) edits. An example: Partition string "foo" into 5 substrings, where ε is a null

How Partitions are split into Kafka Broker?

由 穿精又带淫゛_ 提交于 2019-12-06 16:03:07
I know that partitions are split across Kafka Broker. But the split is based on what ?. For instance, if I have 3 brokers and 6 partitions, how to ensure that each broker will have 2 partitions ? How this split is currently made in Kafka ? Assignment policy is an internal implementation detail and not documented as it can get changed at any point in time. Thus, you should not rely the this algorithms stay the same. Furthermore, there is nothing you can do to influent/configure this internal strategy. The basic policy is to ensure load balancing, i.e., it assigns partitions to brokers that have

Partitioning data set by time intervals in R

由 末鹿安然 提交于 2019-12-06 15:06:13
问题 I have some observed data by hour. I am trying to subset this data by the day or even week intervals. I am not sure how to proceed with this task in R . The sample of the data is below. date obs 2011-10-24 01:00:00 12 2011-10-24 02:00:00 4 2011-10-24 19:00:00 18 2011-10-24 20:00:00 7 2011-10-24 21:00:00 4 2011-10-24 22:00:00 2 2011-10-25 00:00:00 4 2011-10-25 01:00:00 2 2011-10-25 02:00:00 2 2011-10-25 15:00:00 12 2011-10-25 18:00:00 2 2011-10-25 19:00:00 3 2011-10-25 21:00:00 2 2011-10-25 23

Partition Implementation for Recursive Quicksort in Java is not working

由 被刻印的时光 ゝ 提交于 2019-12-06 13:57:42
问题 Wrote this Java implementation of a recursive quicksort algorithm, and something seems to go awry as the array I am trying to sort almost sorts perfectly except for two elements that should be switched (near the middle of the array). The array of integers I am trying to sort is: 4, 77, 98, 30, 20, 50, 77, 22, 49, 2 (10 elements). Here is my code: public static void quickSort(int[] array, int start, int end) { if (start < end) { int partition = partition(array, start, end); quickSort(array,

Spark Creates Less Partitions Then minPartitions Argument on WholeTextFiles

由 徘徊边缘 提交于 2019-12-06 13:46:59
I have a folder which has 14 files in it. I run the spark-submit with 10 executors on a cluster, which has resource manager as yarn. I create my first RDD as this: JavaPairRDD<String,String> files = sc.wholeTextFiles(folderPath.toString(), 10); However, files.getNumPartitions() gives me 7 or 8, randomly. Then I do not use coalesce/repartition anywhere and I finish my DAG with 7-8 partitions. As I know, we gave argument as the "minimum" number of partitions, so that why Spark divide my RDD to 7-8 partitions? I also run the same program with 20 partitions and it gave me 11 partitions. I have

Apache Spark: Join two RDDs with different partitioners

由 一曲冷凌霜 提交于 2019-12-06 12:48:01
问题 I have 2 rdds with different set of partitioners. case class Person(name: String, age: Int, school: String) case class School(name: String, address: String) rdd1 is the RDD of Person , which I have partitioned based on age of the person, and then converted the key to school . val rdd1: RDD[Person] = rdd1.keyBy(person => (person.age, person)) .partitionBy(new HashPartitioner(10)) .mapPartitions(persons => persons.map{case(age,person) => (person.school, person) }) rdd2 is the RDD of School

How does Round Robin partitioning in Spark work?

由 早过忘川 提交于 2019-12-06 12:18:52
问题 I've trouble to understand Round Robin Partitioning in Spark. Consider the following exampl. I split a Seq of size 3 into 3 partitions: val df = Seq(0,1,2).toDF().repartition(3) df.explain == Physical Plan == Exchange RoundRobinPartitioning(3) +- LocalTableScan [value#42] Now if I inspect the partitions, I get: df .rdd .mapPartitionsWithIndex{case (i,rows) => Iterator((i,rows.size))} .toDF("partition_index","number_of_records") .show +---------------+-----------------+ |partition_index|number
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