我正在尝试在Amazon AWS中使用名为Twilio/Wigle.net Street Vector Data Set的公共数据集。此数据集包含美国街道名称和地址范围的数据。它的大小约为10 GiB。当我们看一下linux时，它看起来如下：
ubuntu@ip-172-31-xxx-xxx:/data-us-street$ pwd
/data-us-street
ubuntu@ip-172-31-xxx-xxx:/data-us-street$ ll
total 20576
drwxr-xr-x 6 27 sudo 4096 May 19 2009 ./
drwxr-xr-x 23 root root 4096 Apr 20 18:10 ../
-rw-r--r-- 1 root root 8339 May 19 2009 README
drwx------ 2 27 sudo 4096 Mar 18 2009 addresses/
-rw-rw---- 1 27 sudo 5242880 Mar 18 2009 ib_logfile0
-rw-rw---- 1 27 sudo 5242880 Mar 8 2009 ib_logfile1
-rw-rw---- 1 27 sudo 10485760 Mar 18 2009 ibdata1
drwx------ 2 27 sudo 16384 Mar 8 2009 lost+found/
drwx------ 2 27 sudo 4096 Mar 8 2009 mysql/
-rw-rw---- 1 27 sudo 117 Mar 18 2009 mysql-bin.000001
-rw-rw---- 1 27 sudo 19 Mar 18 2009 mysql-bin.index
drwx------ 2 27 sudo 4096 Mar 8 2009 test/
为了使用它的数据，我想将它链接到同一主机中的MySQL数据库。有人能告诉我怎么做吗？
我尝试覆盖位于datadir的mysql存储目录/etc/mysql/my.cnf，但有以下更改：
#datadir = /var/lib/mysql
datadir = /data-us-street
我停止了服务器，更改为值然后重新启动MySQL服务器。但是，它不起作用。
自述
/*
Copyright (c) 2009 Twilio, Inc.
Permission is hereby granted, free of charge, to any person
obtaining a copy of this software and associated documentation
files (the "Software"), to deal in the Software without
restriction, including without limitation the rights to use,
copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the
Software is furnished to do so, subject to the following
conditions:
The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
OTHER DEALINGS IN THE SOFTWARE.
*/
1. The Twilio/Wigle.net public address dataset
This public dataset contains the street data for the U.S., based on
the geodata published by the U.S. Census Bureau's TIGER project.
We have reformated the data from GIS friendly shapefiles to a more
generally accessible MySQL database.
This dataset covers all the streets, roads, and highways in the U.S.
These streets are represented as "polylines" which are shapes made up
of individual line segments. Each polyline has its own unique ID,
and each segment that makes up the polyline has a sequence number.
The combination of this ID and sequence number is the primary key of
the address table. Each row in the database represents one of these
line segments.
2. Description of Columns
+-------------+------------+------+-----+------------+-------+
| Field | Type | Null | Key | Default | Extra |
+-------------+------------+------+-----+------------+-------+
| id | char(10) | NO | PRI | | |
| seq | char(3) | NO | PRI | | |
| name | char(30) | YES | MUL | NULL | |
| prefix | char(2) | YES | MUL | NULL | |
| type | char(4) | YES | | NULL | |
| startlat | float(12,8)| NO | | 0.00000000 | |
| startlong | float(12,8)| NO | | 0.00000000 | |
| endlat | float(12,8)| NO | | 0.00000000 | |
| endlong | float(12,8)| NO | | 0.00000000 | |
| leftzip | int(5) | YES | MUL | NULL | |
| rightzip | int(5) | YES | MUL | NULL | |
| leftaddr1 | char(11) | YES | | NULL | |
| leftaddr2 | char(11) | YES | | NULL | |
| rightaddr1 | char(11) | YES | | NULL | |
| rightaddr2 | char(11) | YES | | NULL | |
| name_dtmf | char(30) | YES | | NULL | |
| prefix_dtmf | char(2) | YES | | NULL | |
+-------------+------------+------+-----+------------+-------+
id - this is the unique ID of a street, road, or highway polyline,
according to US census blocks
seq - this is the sequence number of this segment in the polyline,
used to correlate 2 segments of the same street within a US
census block
name - the name of this street, road, or highway. example: Main
prefix - the prefix of the street name. examples: N,S,E,W
type - the suffix of the street name. examples: Blvd, St, Rd
startlat/startlong - the lat/long pair of this segments the starting
point
endlat/endlong - the lat/long pair of this segments the ending point
leftzip/rightzip - the zipcode of the addresses on the corresponding
side of the street
leftaddr1/leftaddr2/rightaddr1/rightaddr2 - the starting and ending
addresses
numbers for each side of the street
name_dtmf/prefix_dtmf/type_dtmf - the name, prefix and type columns,
represented
as DTMF encoded numbers. For example, (A,B,C) = 2, (D,E,F) = 3,
etc.
Useful for telephony applications.
3. Example Segment
--------------------------------------------------------
id: 111710515
seq: 0
name: Main
prefix:
type: St
startlat: 41.49493408
startlong: -87.70324707
endlat: 41.49483490
endlong: -87.70324707
leftzip: 60466
rightzip: 60443
leftaddr1: 21801
leftaddr2: 21805
rightaddr1: 21800
rightaddr2: 21804
name_dtmf: 6246
prefix_dtmf:
--------------------------------------------------------
Name: Main St.
Left Zip: 60466
21801 21805
X------------------------------------>
21800 21804
Right Zip: 60443
4. Common Queries
a. Find the street segment record for 30 Rockefeller Plaza, NY, NY,
10020
SELECT * FROM address WHERE leftzip=10020 AND name LIKE 'Rockefeller'
AND 30 BETWEEN leftaddr1 AND leftaddr2
UNION
SELECT * FROM address WHERE rightzip=10020 AND name LIKE
'Rockefeller' AND 30 BETWEEN rightaddr1 AND rightaddr2
--------------------------------------------------------
id: 59657155
seq: 0
name: Rockefeller
prefix:
type: Plz
startlat: 40.7585
startlong: -73.979
endlat: 40.7592
endlong: -73.9786
leftzip: 10020
rightzip: 10020
leftaddr1: 22
leftaddr2: 38
rightaddr1: 21
rightaddr2: 39
name_dtmf: 7625335537
prefix_dtmf:
--------------------------------------------------------
b. Find all the street names within a zipcode.
SELECT DISTINCT prefix, name, type FROM address WHERE leftzip=10009
OR rightzip = 10009
+--------+----------+------+
| prefix | name | type |
+--------+----------+------+
| | 1st | Ave |
| | Avenue A | |
| E | 13th | St |
| E | 14th | St |
| E | 12th | St |
| E | 11th | St |
| E | 10th | St |
| E | 2nd | St |
| E | 3rd | St |
| E | 4th | St |
| E | 6th | St |
| E | 7th | St |
| | St Marks | Pl |
| E | 9th | St |
| | Avenue B | |
| E | 5th | St |
| | Avenue C | |
| E | 20th | St |
| E | 15th | St |
| E | 16th | St |
| E | 8th | St |
| | Avenue D | |
| | Szold | Pl |
+--------+----------+------+
c. Streets starting with F in a zipcode
SELECT DISTINCT prefix, name, type from address WHERE leftzip = 94117
AND name LIKE 'F%'
UNION
SELECT DISTINCT prefix, name, type from address WHERE rightzip =
94117 AND name LIKE 'F%'
+--------+------------+------+
| prefix | name | type |
+--------+------------+------+
| | Fulton | St |
| | Fell | St |
| | Frederick | St |
| | Farnsworth | Ln |
| | Fillmore | St |
| | Friendship | Ct |
+--------+------------+------+
d. Streets starting with "FRE" as DTMF digits in a zipcode:
SELECT DISTINCT prefix, name, type from address WHERE leftzip = 94117
AND name_dtmf LIKE '373%'
UNION
SELECT DISTINCT prefix, name, type from address WHERE rightzip =
94117 AND name_dtmf LIKE '373%'
+--------+------------+------+
| prefix | name | type |
+--------+------------+------+
| | Fulton | St |
| | Fell | St |
| | Frederick | St |
| | Farnsworth | Ln |
| | Fillmore | St |
| | Friendship | Ct |
+--------+------------+------+
答案 0 :(得分：0)
根文件夹public class JSONParser {
String charset = "UTF-8";
HttpURLConnection conn;
DataOutputStream wr;
StringBuilder result;
URL urlObj;
JSONObject jObj = null;
StringBuilder sbParams;
String paramsString;
public JSONObject makeHttpRequest(String url, String method,
HashMap<String, String> params) {
sbParams = new StringBuilder();
int i = 0;
for (String key : params.keySet()) {
try {
if (i != 0){
sbParams.append("&");
}
sbParams.append(key).append("=")
.append(URLEncoder.encode(params.get(key), charset));
} catch (UnsupportedEncodingException e) {
e.printStackTrace();
}
i++;
}
if (method.equals("POST")) {
// request method is POST
try {
urlObj = new URL(url);
conn = (HttpURLConnection) urlObj.openConnection();
conn.setDoOutput(true);
conn.setRequestMethod("POST");
conn.setRequestProperty("Accept-Charset", charset);
conn.setReadTimeout(10000);
conn.setConnectTimeout(15000);
conn.connect();
paramsString = sbParams.toString();
wr = new DataOutputStream(conn.getOutputStream());
wr.writeBytes(paramsString);
wr.flush();
wr.close();
} catch (IOException e) {
e.printStackTrace();
}
}
else if(method.equals("GET")){
// request method is GET
if (sbParams.length() != 0) {
url += "?" + sbParams.toString();
}
try {
urlObj = new URL(url);
conn = (HttpURLConnection) urlObj.openConnection();
conn.setDoOutput(false);
conn.setRequestMethod("GET");
conn.setRequestProperty("Accept-Charset", charset);
conn.setConnectTimeout(15000);
conn.connect();
} catch (IOException e) {
e.printStackTrace();
}
}
try {
//Receive the response from the server
InputStream in = new BufferedInputStream(conn.getInputStream());
BufferedReader reader = new BufferedReader(new InputStreamReader(in));
result = new StringBuilder();
String line;
while ((line = reader.readLine()) != null) {
result.append(line);
}
Log.d("JSON Parser", "result: " + result.toString());
} catch (IOException e) {
e.printStackTrace();
}
conn.disconnect();
// try parse the string to a JSON object
try {
jObj = new JSONObject(result.toString());
} catch (JSONException e) {
Log.e("JSON Parser", "Error parsing data " + e.toString());
}
// return JSON Object
return jObj;
}
}
下的每个子文件夹都代表一个数据库。因此，如果我想使用数据库/data-us-street，我需要使用文件夹addresses：
将目标数据库文件夹复制到当前MySQL数据库服务器实例的数据目录中，例如的/ var / lib中/ MySQL的
./addresses递归更改文件夹所有者
$ cp -r /data-us-street/addresses /var/lib/mysql/addresses
使用数据库$ chown mysql:mysql /var/lib/mysql/addresses/*
并享受！