使用Python创建faker实例生成csv大数据测试文件并导入Hive数仓-Toy模板网

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一、Python生成数据

1.1 代码说明

这段Python代码用于生成模拟的个人信息数据，并将数据保存为CSV文件。

导入必要的模块：
- csv：用于处理CSV文件的模块。
- random：用于生成随机数。
- faker：用于生成模拟数据的库。
定义生成数据所需的基本信息：
- file_base_path：生成的CSV文件的基本路径。
- rows_per_file：每个CSV文件中包含的行数。
- num_rows：要生成的总行数。
- fake：创建faker.Faker()实例，用于生成模拟数据。
定义模拟数据的字典：
- nationalities：包含国籍编码和对应的国家。
- regions：包含区域编码和对应的区域名称。
- source_codes：包含一组源代码。
使用计数器 row_counter 来跟踪生成的行数。
使用循环生成多个CSV文件，每个文件包含 rows_per_file 行数据。
在每个文件中，生成随机的个人信息数据，并将其写入CSV文件。
数据生成的过程中，每10000行数据打印一次进度。
所有数据生成后，打印生成的总行数。

这段代码使用Faker库生成模拟的个人信息数据，每个CSV文件包含一定数量的行数据，数据字段包括 Rowkey, Name, Age, Email, Address, IDNumber, PhoneNumber, Nationality, Region, SourceCode。

1.2 代码参考

import csv
import random
import faker

# 文件基本路径
file_base_path = './output/personal_info_extended'
# 每个文件的行数
rows_per_file = 10000
# 总行数
num_rows = 10000000

# 创建Faker实例
fake = faker.Faker()

# 定义数据字典
nationalities = {
    1: 'US',
    2: 'CA',
    3: 'UK',
    4: 'AU',
    5: 'FR',
    6: 'DE',
    7: 'JP',
}

regions = {
    1: 'North',
    2: 'South',
    3: 'East',
    4: 'West',
    5: 'Central',
}

source_codes = ['A123', 'B456', 'C789', 'D101', 'E202']

# 计数器用于跟踪生成的行数
row_counter = 0

# 循环生成数据文件
for file_number in range(1, num_rows // rows_per_file + 1):
    file_path = f"{file_base_path}_{file_number}.csv"

    # 打开CSV文件以写入数据
    with open(file_path, 'w', newline='') as csvfile:
        csv_writer = csv.writer(csvfile)

        # 写入CSV文件的标题行
        if row_counter == 0:
            csv_writer.writerow(['Rowkey', 'Name', 'Age', 'Email', 'Address', 'IDNumber', 'PhoneNumber', 'Nationality', 'Region', 'SourceCode'])

        # 生成并写入指定行数的扩展的个人信息模拟数据
        for _ in range(rows_per_file):
            name = fake.name()
            age = random.randint(18, 99)
            email = fake.email()
            address = fake.address().replace('\n', ' ') // 替换掉地址中的换行，保持数据生成为一行
            id_number = fake.ssn()
            phone_number = fake.phone_number()
            nationality_code = random.randint(1, len(nationalities))
            nationality = nationalities[nationality_code]
            region_code = random.randint(1, len(regions))
            region = regions[region_code]
            source_code = random.choice(source_codes)

            data_row = [row_counter + 1, name, age, email, address, id_number, phone_number, nationality, region, source_code]
            csv_writer.writerow(data_row)

            row_counter += 1

    print(f'已生成 {row_counter} 行数据')

print(f'{num_rows} 行扩展的个人信息模拟数据已生成')

在这里插入图片描述

二、数据迁移

2.1 从本机上传至服务器

[root@hadoop10 personInfo]# pwd
/opt/data/personInfo
[root@hadoop10 personInfo]# ls -l| wc -l
215
[root@hadoop10 personInfo]# wc -l *
...
    10000 personal_info_extended_98.csv
    10000 personal_info_extended_99.csv
    10000 personal_info_extended_9.csv
  2131609 总用量

通过命令显示我们使用了生成的215个csv文件，现在已经上传到了/opt/data/personInfo目录下。

2.2 检查源数据格式

[root@hadoop10 personInfo]# head personal_info_extended_1.csv
Rowkey,Name,Age,Email,Address,IDNumber,PhoneNumber,Nationality,Region,SourceCode
1,Hayley Jimenez,58,garrisonalicia@harris.com,"92845 Davis Circles Apt. 198 East Jerryshire, NV 35424",657-35-2900,(141)053-9917,DE,North,C789
2,Amy Johnson,23,samuelrivera@hall.com,"119 Manning Rapids Suite 557 New Randyburgh, MN 58113",477-76-9570,+1-250-531-6115,UK,North,D101
3,Sara Harper,31,gsandoval@hotmail.com,"98447 Robinson Dale Garzatown, ME 35917",254-77-4980,7958192189,AU,East,A123
4,Alicia Wang,53,kellyreed@evans.com,"531 Lucas Vista New Laura, MO 62148",606-19-1971,001-295-093-9174x819,DE,West,C789
5,Lauren Rodriguez,71,rebeccasaunders@yahoo.com,"060 Gomez Ports Suite 355 Lake Aarontown, CO 38284",186-61-7463,8458236624,DE,East,E202
6,Juan Harris,98,davidsonjohn@hines.com,"50325 Alvarez Forge Apt. 800 New Ericchester, AL 16131",529-53-1492,+1-302-675-5810,CA,East,B456
7,Stephanie Price,90,sroberts@becker.com,"9668 Erik Inlet Port Joshua, MO 62524",303-11-9577,628.011.4670,UK,East,C789
8,Nicole Parker,61,tmcneil@rose-rodriguez.com,"485 Elliott Branch Scottshire, NJ 03885",473-55-5636,001-625-925-3712x952,FR,West,A123
9,Joel Young,54,john03@hotmail.com,"9413 Houston Flats Apt. 095 West Peggy, MD 56240",547-31-2815,920.606.0727x27740,JP,Central,E202

使用head命令查看文件的头，发现了首行字段，我们可以通过首行字段编写建表语句。

2.3 检查大小并上传至HDFS

[root@hadoop10 data]# du -h
282M    ./personInfo
282M    .

[root@hadoop10 data]# hdfs dfs -put /opt/data/personInfo /testdir/

[root@hadoop10 data]# hdfs dfs -du -h /testdir/
281.4 M  281.4 M  /testdir/personInfo

linux本地文件占用282M，上传至HDFS集群/testdir/目录后占用281.4M.

三、beeline建表

3.1 创建测试表并导入测试数据

CREATE TABLE personal_info (
    Rowkey STRING,
    Name STRING,
    Age STRING,
    Email STRING,
    Address STRING,
    IDNumber STRING,
    PhoneNumber STRING,
    Nationality STRING,
    Region STRING,
    SourceCode STRING
)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
STORED AS TEXTFILE;

LOAD DATA INPATH '/testdir/personInfo/*.csv' INTO TABLE personal_info;

如果csv文件的每一行都有同样的列名，需要在建表语句最后添加以下代码：TBLPROPERTIES ("skip.header.line.count"="1")，将首行跳过。

本案例由于使用python生成文件，只有第一个csv文件有列名，其余csv没有列名，我们稍后单独处理这一个首行。

3.2 建表显示内容

0: jdbc:hive2://hadoop10:10000> CREATE TABLE personal_info (
. . . . . . . . . . . . . . . >     Rowkey STRING,
. . . . . . . . . . . . . . . >     Name STRING,
. . . . . . . . . . . . . . . >     Age STRING,
. . . . . . . . . . . . . . . >     Email STRING,
. . . . . . . . . . . . . . . >     Address STRING,
. . . . . . . . . . . . . . . >     IDNumber STRING,
. . . . . . . . . . . . . . . >     PhoneNumber STRING,
. . . . . . . . . . . . . . . >     Nationality STRING,
. . . . . . . . . . . . . . . >     Region STRING,
. . . . . . . . . . . . . . . >     SourceCode STRING
. . . . . . . . . . . . . . . > )
. . . . . . . . . . . . . . . > ROW FORMAT DELIMITED
. . . . . . . . . . . . . . . > FIELDS TERMINATED BY ','
. . . . . . . . . . . . . . . > STORED AS TEXTFILE;
No rows affected (0.147 seconds)

0: jdbc:hive2://hadoop10:10000> LOAD DATA INPATH '/testdir/personInfo/*.csv' INTO TABLE personal_info;
No rows affected (2.053 seconds)

0: jdbc:hive2://hadoop10:10000> select * from personal_info limit 5;
+-----------------------+---------------------+--------------------+----------------------------+------------------------------------------------+-------------------------+----------------------------+----------------------------+-----------------------+---------------------------+
| personal_info.rowkey  | personal_info.name  | personal_info.age  |    personal_info.email     |             personal_info.address              | personal_info.idnumber  | personal_info.phonenumber  | personal_info.nationality  | personal_info.region  | personal_info.sourcecode  |
+-----------------------+---------------------+--------------------+----------------------------+------------------------------------------------+-------------------------+----------------------------+----------------------------+-----------------------+---------------------------+
| Rowkey                | Name                | Age                | Email                      | Address                                        | IDNumber                | PhoneNumber                | Nationality                | Region                | SourceCode                |
| 1                     | Hayley Jimenez      | 58                 | garrisonalicia@harris.com  | "92845 Davis Circles Apt. 198 East Jerryshire  |  NV 35424"              | 657-35-2900                | (141)053-9917              | DE                    | North                     |
| 2                     | Amy Johnson         | 23                 | samuelrivera@hall.com      | "119 Manning Rapids Suite 557 New Randyburgh   |  MN 58113"              | 477-76-9570                | +1-250-531-6115            | UK                    | North                     |
| 3                     | Sara Harper         | 31                 | gsandoval@hotmail.com      | "98447 Robinson Dale Garzatown                 |  ME 35917"              | 254-77-4980                | 7958192189                 | AU                    | East                      |
| 4                     | Alicia Wang         | 53                 | kellyreed@evans.com        | "531 Lucas Vista New Laura                     |  MO 62148"              | 606-19-1971                | 001-295-093-9174x819       | DE                    | West                      |
+-----------------------+---------------------+--------------------+----------------------------+------------------------------------------------+-------------------------+----------------------------+----------------------------+-----------------------+---------------------------+
5 rows selected (0.52 seconds)

四、csv文件首行列名的处理

4.1 创建新的表

解决思路是通过将整表的数据查询出，插入到另一个新表中，而后删除旧的表，该方法如果在生产环境中使用应考虑机器性能和存储情况。

CREATE TABLE pinfo (
    Rowkey STRING,
    Name STRING,
    Age STRING,
    Email STRING,
    Address STRING,
    IDNumber STRING,
    PhoneNumber STRING,
    Nationality STRING,
    Region STRING,
    SourceCode STRING
)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
STORED AS TEXTFILE;

查询旧表中的行数。

0: jdbc:hive2://hadoop10:10000> select count(*) from personal_info;
+----------+
|   _c0    |
+----------+
| 2131609  |
+----------+
1 row selected (45.762 seconds)

4.2 将旧表过滤首行插入新表

INSERT OVERWRITE TABLE pinfo
SELECT
    t.Rowkey,
    t.Name,
    t.Age,
    t.Email,
    t.Address,
    t.IDNumber,
    t.PhoneNumber,
    t.Nationality,
    t.Region,
    t.SourceCode
FROM (
    SELECT
        Rowkey,
        Name,
        Age,
        Email,
        Address,
        IDNumber,
        PhoneNumber,
        Nationality,
        Region,
        SourceCode
    FROM personal_info
) t
WHERE t.Name != 'Name';


0: jdbc:hive2://hadoop10:10000> select * from pinfo limit 5;
+---------------+-------------------+------------+----------------------------+------------------------------------------------+-----------------+--------------------+-----------------------+---------------+-------------------+
| pinfo.rowkey  |    pinfo.name     | pinfo.age  |        pinfo.email         |                 pinfo.address                  | pinfo.idnumber  | pinfo.phonenumber  |   pinfo.nationality   | pinfo.region  | pinfo.sourcecode  |
+---------------+-------------------+------------+----------------------------+------------------------------------------------+-----------------+--------------------+-----------------------+---------------+-------------------+
| 1             | Hayley Jimenez    | 58         | garrisonalicia@harris.com  | "92845 Davis Circles Apt. 198 East Jerryshire  |  NV 35424"      | 657-35-2900        | (141)053-9917         | DE            | North             |
| 2             | Amy Johnson       | 23         | samuelrivera@hall.com      | "119 Manning Rapids Suite 557 New Randyburgh   |  MN 58113"      | 477-76-9570        | +1-250-531-6115       | UK            | North             |
| 3             | Sara Harper       | 31         | gsandoval@hotmail.com      | "98447 Robinson Dale Garzatown                 |  ME 35917"      | 254-77-4980        | 7958192189            | AU            | East              |
| 4             | Alicia Wang       | 53         | kellyreed@evans.com        | "531 Lucas Vista New Laura                     |  MO 62148"      | 606-19-1971        | 001-295-093-9174x819  | DE            | West              |
| 5             | Lauren Rodriguez  | 71         | rebeccasaunders@yahoo.com  | "060 Gomez Ports Suite 355 Lake Aarontown      |  CO 38284"      | 186-61-7463        | 8458236624            | DE            | East              |
+---------------+-------------------+------------+----------------------------+------------------------------------------------+-----------------+--------------------+-----------------------+---------------+-------------------+
5 rows selected (0.365 seconds)
0: jdbc:hive2://hadoop10:10000>

使用Python创建faker实例生成csv大数据测试文件并导入Hive数仓,Hadoop生态,python,hive,大数据,数据仓库
在yarn中查看新表插入的进度。

最后新表的查询结果显示比旧表少1行即为插入处理完成。文章来源地址https://www.toymoban.com/news/detail-725212.html

0: jdbc:hive2://hadoop10:10000> select count(*) from pinfo;
+----------+
|   _c0    |
+----------+
| 2131608  |
+----------+
1 row selected (0.291 seconds)

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