Python：如何从 HDFS 导入目录中的文件列表

Question

I try to import list of files from HDFS in python.

How to do this from HDFS :

path =r'/my_path'
allFiles = glob.glob(path + "/*.csv")

df_list = []
for file_ in allFiles:
    df = pd.read_csv(file_,index_col=None, header=0,sep=';')    
    df_list.append(df)

I think subprocess.Popen do the trick but how to extract only the filename ?

import subprocess
p = subprocess.Popen("hdfs dfs -ls /my_path/ ",
    shell=True,
    stdout=subprocess.PIPE,
    stderr=subprocess.STDOUT)


for line in p.stdout.readlines():
    print(line)

The output is like this :

b'Found 32 items\n'
b'-rw-------   3 user hdfs   42202621 2019-01-21 10:05 /my_path/file1.csv\n'
b'-rw-------   3 user hdfs   99320020 2019-01-21 10:05 /my_path/file2.csv\n'

Answer 1

Declaimer : This will be a long and tedious. But given the circumstance, I'll try to make it as general and reproducible as possible.

---

Given the requirement of no external libraries (except for pandas ?), there isn't must of a choice to take. I suggest utilizing WebHDFS as much as possible.

AFAIK, installation of HDFS , by default, includes an installation of WebHDFS . Following solution heavily relies on WebHDFS .

First Step

To begin with, you must be aware of WebHDFS urls. WebHDFS is installed on HDFS Namenode(s) , and default port is 50070 .

Therefore, we start with http://[namenode_ip]:50070/webhdfs/v1/ , where /webhdfs/v1 / is a common url for all.

For the sake of example, let's assume it as http://192.168.10.1:50070/web/hdfs/v1 .

Second Step

Ordinarily, one can use curl to list contents of a HDFS directory. For detailed explanation, refer to WebHDFS REST API: List a Directory

If you were to use curl , following provides FileStatuses of all the files inside a given directory.

curl "http://192.168.10.1:50070/webhdfs/v1/<PATH>?op=LISTSTATUS"
             ^^^^^^^^^^^^ ^^^^^             ^^^^  ^^^^^^^^^^^^^
             Namenode IP  Port              Path  Operation

As mentioned, this returns FileStatuses in JSON object:

{
  "FileStatuses":
  {
    "FileStatus":
    [
      {
        "accessTime"      : 1320171722771,
        "blockSize"       : 33554432,
        "group"           : "supergroup",
        "length"          : 24930,
        "modificationTime": 1320171722771,
        "owner"           : "webuser",
        "pathSuffix"      : "a.patch",
        "permission"      : "644",
        "replication"     : 1,
        "type"            : "FILE"
      },
      {
        "accessTime"      : 0,
        "blockSize"       : 0,
        "group"           : "supergroup",
        "length"          : 0,
        "modificationTime": 1320895981256,
        "owner"           : "szetszwo",
        "pathSuffix"      : "bar",
        "permission"      : "711",
        "replication"     : 0,
        "type"            : "DIRECTORY"
      },
      ...
    ]
  }
}

Same result can be achieved using python's default libs:

import requests

my_path = '/my_path/'
curl = requests.get('http://192.168.10.1:50070/webhdfs/v1/%s?op=LISTSTATUS' % my_path)

And as shown above, the actual status of each file is two levels below of the result JSON. In other words, to get the FileStatus of each file:

curl.json()['FileStatuses']['FileStatus'] 

[
  {
    "accessTime"      : 1320171722771,
    "blockSize"       : 33554432,
    "group"           : "supergroup",
    "length"          : 24930,
    "modificationTime": 1320171722771,
    "owner"           : "webuser",
    "pathSuffix"      : "a.patch",
    "permission"      : "644",
    "replication"     : 1,
    "type"            : "FILE"
  },
  {
    "accessTime"      : 0,
    "blockSize"       : 0,
    "group"           : "supergroup",
    "length"          : 0,
    "modificationTime": 1320895981256,
    "owner"           : "szetszwo",
    "pathSuffix"      : "bar",
    "permission"      : "711",
    "replication"     : 0,
    "type"            : "DIRECTORY"
  },
  ...
]

Third Step

Since you now have all the information you want, all you need to do is parsing.

import os

file_paths = []
for file_status in curl.json()['FileStatuses']['FileStatus']:
    file_name = file_status['pathSuffix']
    # this is the file name in the queried directory
    if file_name.endswith('.csv'):
    # if statement is only required if the directory contains unwanted files (i.e. non-csvs).
        file_paths.append(os.path.join(path, file_name))
        # os.path.join asserts your result consists of absolute path

file_paths
['/my_path/file1.csv',
 '/my_path/file2.csv',
 ...]

Final Step

Now you know the paths of files and WebHDFS links, pandas.read_csv can handle rest of the works.

import pandas as pd

dfs = []
web_url = "http://192.168.10.1:50070/webhdfs/v1/%s?op=OPEN"
#                                                  ^^^^^^^
#                                    Operation is now OPEN
for file_path in file_paths:
    file_url = web_url % file_path
    # http://192.168.10.1:50070/webhdfs/v1/my_path/file1.csv?op=OPEN
    dfs.append(pd.read_csv(file_url))

And there you go with all the .csv s imported and assigned to dfs .

Warnings

If your HDFS is configured for HA (High Availability), there will be multiple namenodes and thus your namenode_ip must be set accordingly: It must be the IP of an active node.