bigdata

Zookeeper cluster set up

由 依然范特西╮ 提交于 2020-04-30 07:49:57
问题 I am able to set up zookeeper cluster on 1 machine with 3 different ports, but when I do the same with different IP to have zookeeper instance on different machines, it throws following error: 2014-11-20 12:16:24,819 [myid:1] - INFO [main:QuorumPeerMain@127] - Starting quorum peer 2014-11-20 12:16:24,827 [myid:1] - INFO [main:NIOServerCnxnFactory@94] - binding to port 0.0.0.0/0.0.0.0:2181 2014-11-20 12:16:24,842 [myid:1] - INFO [main:QuorumPeer@959] - tickTime set to 2000 2014-11-20 12:16:24

大数据数据名词：PV、IPV、UV等

由 匆匆过客 提交于 2020-04-17 22:34:29
大数据数据名词： 数据名词 定义 计算公式 相关名词 浏览量(PV) 店铺页面被访问的总次数 店铺内页面被点击一次，即被记为一次浏览（PV），一个用户多次点击或刷新同一个页面，会被记为多次浏览（PV），累加不去重。 人均店内停留时间、访客数(UV) 详情页浏览量(IPV) 店铺详情页面被访问的总次数 店铺的详情页面被点击一次，即被记为一次浏览（IPV），一个用户多次点击或刷新同一个页面，会被记为多次浏览（IPV），累加不去重。 详情页访客数、详情页平均停留时间 访客数(UV) 访问店铺的总人数 一个用户一天内多次访问店铺被记为一个访客 浏览量(PV)、人均店内停留时间 详情页访客数 到达店铺详情页面的访客数 详情页浏览量(IPV)、详情页平均停留时间 人均店内停留时间 平均每个用户连续访问店铺的时间（即平均每次访问店铺的时间） 浏览量(PV)、访客数(UV) 详情页平均停留时间 平均每个用户在连续访问店铺时，在每个详情页上停留的时间 详情页浏览量(IPV)、详情页访客数 访问深度 指用户一次连续访问的店铺页面数（即每次浏览店铺的页面数） 平均访问深度即用户平均每次连续访问浏览的店铺页面数 浏览量(PV)、访客数(UV) 成交转化率 本店成交人数占总访客数的比率 成交转化率=成交人数/访客数 访客数(UV)、成交人数 详情页成交转化率 详情页成交人数占详情页访客数的比率

How can I merge these many csv files (around 130,000) using PySpark into one large dataset efficiently?

由 时间秒杀一切 提交于 2020-04-14 21:01:49
问题 I posted this question earlier and got some advice to use PySpark instead. How can I merge this large dataset into one large dataframe efficiently? The following zip file (https://fred.stlouisfed.org/categories/32263/downloaddata/INTRNTL_csv_2.zip) contains a folder called data with around 130,000 of csv files. I want to merge all of them into one single dataframe. I have 16gb of RAM and I keep running out of RAM when I hit the first few hundred files. The files' total size is only about 300

Elasticsearch query to return all records

由 ☆樱花仙子☆ 提交于 2020-03-29 04:46:10
问题 I have a small database in Elasticsearch and for testing purposes would like to pull all records back. I am attempting to use a URL of the form... http://localhost:9200/foo/_search?pretty=true&q={'matchAll':{''}} Can someone give me the URL you would use to accomplish this, please? 回答1: I think lucene syntax is supported so: http://localhost:9200/foo/_search?pretty=true&q=*:* size defaults to 10, so you may also need &size=BIGNUMBER to get more than 10 items. (where BIGNUMBER equals a number

Elasticsearch query to return all records

由 穿精又带淫゛_ 提交于 2020-03-29 04:42:07
问题 I have a small database in Elasticsearch and for testing purposes would like to pull all records back. I am attempting to use a URL of the form... http://localhost:9200/foo/_search?pretty=true&q={'matchAll':{''}} Can someone give me the URL you would use to accomplish this, please? 回答1: I think lucene syntax is supported so: http://localhost:9200/foo/_search?pretty=true&q=*:* size defaults to 10, so you may also need &size=BIGNUMBER to get more than 10 items. (where BIGNUMBER equals a number

How large matrix can be fit into Eigen library? [closed]

由 拈花ヽ惹草 提交于 2020-03-21 05:59:17
问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 6 years ago . I am working on large scale data like 300000 x 300000 matrix currently may interest. It is really hard to process in matlab due to "Out of memory" error so I decide to use EIGEN. Is there any restriciton for eigen in the matrix size? 回答1: The dense matrices in EIGEN are stored in a contiguous block of memory,

Optimizing parsing of massive python dictionary, multi-threading

由 淺唱寂寞╮ 提交于 2020-03-18 09:59:31
问题 Let's take a small example python dictionary, where the values are lists of integers. example_dict1 = {'key1':[367, 30, 847, 482, 887, 654, 347, 504, 413, 821], 'key2':[754, 915, 622, 149, 279, 192, 312, 203, 742, 846], 'key3':[586, 521, 470, 476, 693, 426, 746, 733, 528, 565]} Let's say I need to parse the values of the lists, which I've implemented into the following function: def manipulate_values(input_list): return_values = [] for i in input_list: new_value = i ** 2 - 13 return_values

Error while importing gobblin gradle project into IDE

由 我是研究僧i 提交于 2020-03-02 19:58:19
问题 I am getting this error while I try to import the gobblin distribution into my IDE , I have tried both inteliJ and eclipse , not able to find any luck. Below are the errors which I get when I try to import. In Eclipse the error is: *org.gradle.tooling.BuildException: Could not run build action using Gradle distribution 'https://services.gradle.org/distributions/gradle-3.3-bin.zip'. * For InteliJ *Cause: startup failed: build file 'C:\Users\sayyad.ghazi\Desktop\gob\gobblin-master\gobblin

Why is this simple Spark program not utlizing multiple cores?

由 ぃ、小莉子 提交于 2020-01-31 18:09:05
问题 So, I'm running this simple program on a 16 core multicore system. I run it by issuing the following. spark-submit --master local[*] pi.py And the code of that program is the following. #"""pi.py""" from pyspark import SparkContext import random N = 12500000 def sample(p): x, y = random.random(), random.random() return 1 if x*x + y*y < 1 else 0 sc = SparkContext("local", "Test App") count = sc.parallelize(xrange(0, N)).map(sample).reduce(lambda a, b: a + b) print "Pi is roughly %f" % (4.0 *

Why is this simple Spark program not utlizing multiple cores?

由 戏子无情 提交于 2020-01-31 18:06:29
问题 So, I'm running this simple program on a 16 core multicore system. I run it by issuing the following. spark-submit --master local[*] pi.py And the code of that program is the following. #"""pi.py""" from pyspark import SparkContext import random N = 12500000 def sample(p): x, y = random.random(), random.random() return 1 if x*x + y*y < 1 else 0 sc = SparkContext("local", "Test App") count = sc.parallelize(xrange(0, N)).map(sample).reduce(lambda a, b: a + b) print "Pi is roughly %f" % (4.0 *
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