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PostgreSQL使用PreparedStatement导致查询慢的分析
实验环境：
创新互联是由多位在大型网络公司、广告设计公司的优秀设计人员和策划人员组成的一个具有丰富经验的团队，其中包括网站策划、网页美工、网站程序员、网页设计师、平面广告设计师、网络营销人员及形象策划。承接：成都网站建设、成都做网站、网站改版、网页设计制作、网站建设与维护、网络推广、数据库开发,以高性价比制作企业网站、行业门户平台等全方位的服务。
DB is PostgreSQL version 8.2.15
JDK1.8
测试一
使用JDBC查询一个SQL：
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public static void test1(String url, Properties props){
String sql = "SELECT l.src_ip, l.location_id, "
+ "SUM(l.us_bytes) as up_usage, "
+ "SUM(l.ds_bytes) as down_usage, "
+ "(SUM(l.us_bytes) + SUM(l.ds_bytes) ) as total_usage "
+ "FROM unmapped_endpoint_location_hours l "
+ "where l.org_id = 195078 "
+ "AND date_time >= '2017-04-01 00:00:00.0' AND date_time < '2017-04-08 00:00:00.0' "
+ "AND l.location_id in (2638,2640,2654 ) "
+ "GROUP BY l.src_ip, l.location_id ";
Connection conn = null;
Statement sta = null; try {
System.out.println("Start query1:" ); long s_time = System.currentTimeMillis();
conn = DriverManager.getConnection(url, props);
sta = conn.createStatement();
sta.execute(sql);
System.out.println("Using Time: " + (System.currentTimeMillis() - s_time));
} catch (SQLException e) {
e.printStackTrace();
} finally { if (conn != null) { try {
conn.close();
} catch (SQLException e) {
e.printStackTrace();
}
} if (sta != null) { try {
sta.close();
} catch (SQLException e) {
e.printStackTrace();
}
}
}
}
结果：
Start query1:
Using Time: 11519 ms
测试二
使用JDBC PreparedStatement 查询相同的SQL：
public static void test2(String url, Properties props){
String sql2 = "SELECT l.src_ip, l.location_id, "
+ "SUM(l.us_bytes) as up_usage, "
+ "SUM(l.ds_bytes) as down_usage, "
+ "(SUM(l.us_bytes) + SUM(l.ds_bytes) ) as total_usage "
+ "FROM unmapped_endpoint_location_hours l "
+ "where l.org_id = ? "
+ "AND date_time >= ? AND date_time < ? "
+ "AND l.location_id in (2638,2640,2654 ) "
+ "GROUP BY l.src_ip, l.location_id";
Connection conn = null;
PreparedStatement preSta = null; try {
System.out.println("Start query2:"); long s_time = System.currentTimeMillis();
conn = DriverManager.getConnection(url, props);
preSta = conn.prepareStatement(sql2);
preSta.setString(1, "195078");
preSta.setString(2, "2017-04-01 00:00:00.0");
preSta.setString(3, "2017-04-09 00:00:00.0");
preSta.executeQuery();
System.out.println("Using Time: " + (System.currentTimeMillis() - s_time));
} catch (SQLException e) {
e.printStackTrace();
} finally { if (conn != null) { try {
conn.close();
} catch (SQLException e) {
e.printStackTrace();
}
} if (preSta != null) { try {
preSta.close();
} catch (SQLException e) {
e.printStackTrace();
}
}
}
}
结果：
Start query2:
Using Time: 143031 ms
相同的SQL，测试二和测试一结果为什么差别这么大？
测试一的SQL没有使用PreparedStatement 方式，直接给了原始的SQL。测试二的使用了PreparedStatement ，但是在set参数的时候用的都是String。
两者查询速度相差10倍，这是不是很奇怪？
现在来做另一个实验：
测试三
使用JDBC PreparedStatement 查询相同的SQL：
public static void test3(String url, Properties props){
String sql2 = "SELECT l.src_ip, l.location_id, "
+ "SUM(l.us_bytes) as up_usage, "
+ "SUM(l.ds_bytes) as down_usage, "
+ "(SUM(l.us_bytes) + SUM(l.ds_bytes) ) as total_usage "
+ "FROM unmapped_endpoint_location_hours l "
+ "where l.org_id = ? "
+ "AND date_time >= ? AND date_time < ? "
+ "AND l.location_id in (2638,2640,2654 ) "
+ "GROUP BY l.src_ip, l.location_id";
Connection conn = null;
PreparedStatement preSta = null; try {
System.out.println("Start query3:"); long s_time = System.currentTimeMillis();
conn = DriverManager.getConnection(url, props);
preSta = conn.prepareStatement(sql2);
int org_id = 195078;
SimpleDateFormat df = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
TimeZone.setDefault(TimeZone.getTimeZone("UTC"));
Date d1 = null;
Date d2 = null; try {
d1 = df.parse("2017-04-01 00:00:00");
d2 = df.parse("2017-04-09 00:00:00");
} catch (ParseException e1) {
e1.printStackTrace();
}
preSta.setInt(1, org_id);
preSta.setTimestamp(2, new java.sql.Timestamp(d1.getTime()));
preSta.setTimestamp(3, new java.sql.Timestamp(d2.getTime()));
preSta.executeQuery();
System.out.println("Using Time: " + (System.currentTimeMillis() - s_time));
} catch (SQLException e) {
e.printStackTrace();
} finally { if (conn != null) { try {
conn.close();
} catch (SQLException e) {
e.printStackTrace();
}
} if (preSta != null) { try {
preSta.close();
} catch (SQLException e) {
e.printStackTrace();
}
}
}
}
结果：
Start query3:
Using Time: 16245 ms
测试结果和测试一的结果差不多，为什么？
这次测试同样使用了PreparedStatement，但是在设置参数的时候指定了参数的类型。
explan analyze
查看explan
dev=# explain analyze SELECT count(loc.name) AS totalNum dev-# FROM (SELECT t.src_ip, t.location_id, t.up_usage, t.down_usage, t.total_usage dev(# FROM (SELECT l.src_ip, l.location_id, dev(# SUM(l.us_bytes) as up_usage, dev(# SUM(l.ds_bytes) as down_usage, dev(# (SUM(l.us_bytes) + SUM(l.ds_bytes) ) as total_usage dev(# FROM unmapped_endpoint_location_hours l dev(# where l.org_id = 195078dev(# AND date_time >= '2017-04-11 00:00:00.0' AND date_time < '2017-04-20 00:00:00.0'dev(# AND l.location_id in (2638,2640) dev(# GROUP BY l.src_ip, l.location_id ) t dev(# WHERE t.total_usage > 0.0 ) m dev-# LEFT OUTER JOIN locations loc on m.location_id = loc.id WHERE loc.org_id = 195078;
Time: 15202.518 ms
Prepare Expalin: PREPARE test(int,text,text,int) as SELECT count(loc.name) AS totalNum FROM (SELECT t.src_ip, t.location_id, t.up_usage, t.down_usage, t.total_usage FROM (SELECT l.src_ip, l.location_id, SUM(l.us_bytes) as up_usage, SUM(l.ds_bytes) as down_usage, (SUM(l.us_bytes) + SUM(l.ds_bytes) ) as total_usage FROM unmapped_endpoint_location_hours l where l.org_id = $1 AND date_time >= $2 AND date_time < $3 AND l.location_id in (2638,2640) GROUP BY l.src_ip, l.location_id ) t WHERE t.total_usage > 0.0 ) m LEFT OUTER JOIN locations loc on m.location_id = loc.id WHERE loc.org_id = $4; Explain analyze EXECUTE test(195078,'2017-04-11 00:00:00.0','2017-04-20 00:00:00.0',195078); dev=# EXECUTE test(195078,'2017-04-11 00:00:00.0','2017-04-20 00:00:00.0',195078);
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