前言 因為業務要求api的一次請求響應時間在10ms以內,所以傳統的資料庫查詢操作直接被排除(網路io和磁碟io)。通過調研,最終使用了bieset,目前已經正常運行了很久 bitset介紹 看JDK中的解釋簡直一頭霧水,用我自己的理解概括一下 1. bitset的內部實現是long數組 2. se ...
前言
因為業務要求api的一次請求響應時間在10ms以內,所以傳統的資料庫查詢操作直接被排除(網路io和磁碟io)。通過調研,最終使用了bieset,目前已經正常運行了很久
***
bitset介紹
看JDK中的解釋簡直一頭霧水,用我自己的理解概括一下
- bitset的內部實現是long數組
- set中每一個位的預設值為false(0)
- bitset長度按需增長
bitset非線程安全
***bitset關鍵方法分析
/** * Sets the bit at the specified index to {@code true}. * * @param bitIndex a bit index * @throws IndexOutOfBoundsException if the specified index is negative * @since JDK1.0 */ public void set(int bitIndex) { if (bitIndex < 0) throw new IndexOutOfBoundsException("bitIndex < 0: " + bitIndex); int wordIndex = wordIndex(bitIndex); expandTo(wordIndex); words[wordIndex] |= (1L << bitIndex); // Restores invariants checkInvariants(); }
設置指定“位”為true,bitIndex參數為非負整數。假設我們執行以下代碼,觀察上面代碼中worIndex,words[wordIndex]值的變化
BitSet bs = new BitSet() bs.set(0); bs.set(1); bs.set(2); bs.set(3); bs.set(4);
bitIndex wordIndex words[wordIndex] words[wordIndex]二進位表示 0 0 1 0001 1 0 3 0011 2 0 7 0111 3 0 15 1111 4 0 31 0001 1111 通過上表,我們可以很清晰的根據bitIndex和words[wordIndex]二進位值的對應關係,得到一個結論,即:bitset中每一個long可以表示64個非負整數在bitSet中存在與否。例如:0001可以表示整數0在bitset中存在,1111可以表示整數3,2,1,0在bitset中存在。
***
進入正題,實現bitset毫秒級查詢
想象一個場景,我們有一張user表,name唯一。
CREATE TABLE `user` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`name` varchar(255) NOT NULL,
`address` varchar(255) NOT NULL comment '地址',
`gender` varchar(10) NOT NULL comment '性別',
`age` varchar(10) NOT NULL,
PRIMARY KEY (`id`),
UNIQUE KEY `name` (`name`)
) ENGINE=InnoDB AUTO_INCREMENT=0 DEFAULT CHARSET=utf8;
假設我們要查詢“北京市18歲的女生”,那麼對應的sql如下:
select * from `user` where address='北京' and age='18' and gender='girl';
如何使用bitset實現同樣的查詢呢?
- 將user表數據載入進記憶體中
- 為user表建立address,age,gender維度的bitset索引
- 根據索引查詢數據
1.將user表數據載入進記憶體中
將user表從資料庫讀取出來存入List
User實體類:
public class User implements Cloneable {
private String name;
private String address;
private String gender;
private String age;
@Override
public String toString() {
return "User [name=" + name + ", address=" + address + ", gender=" + gender + ", age=" + age + "]";
}
@Override
public User clone() {
User user = null;
try {
user = (User) super.clone();
} catch (CloneNotSupportedException e) {
e.printStackTrace();
}
return user;
}
//省略get set 方法。。。
2.建立索引
創建bitset索引模型類
public class BitSetIndexModel {
private String type;//索引類型:address,age,gender
private ConcurrentHashMap<String, Integer> map;//索引類型和bitSet在bsList中下標的映射關係
private List<String> list;//索引類型的值集合,例如gender:girl,boy
private List<BitSet> bsList;//bitset集合
public BitSetIndex() {
}
public BitSetIndexModel(String type) {
this.type = type;
map = new ConcurrentHashMap<String, Integer>();
list = new ArrayList<String>();
bsList = new ArrayList<BitSet>();
}
public String getType() {
return type;
}
public void setType(String type) {
this.type = type;
}
public Map<String, Integer> getMap() {
return map;
}
public void setMap(ConcurrentHashMap<String, Integer> map) {
this.map = map;
}
public List<String> getList() {
return list;
}
public void setList(List<String> list) {
this.list = list;
}
public List<BitSet> getBsList() {
return bsList;
}
public void setBsList(List<BitSet> bsList) {
this.bsList = bsList;
}
/**
*
* @param str
* @param i
*/
public void createIndex(String str, int i) {
BitSet bitset = null;
//獲取‘str’對應的bitset在bsList中的下標
Integer index = this.getMap().get(str);
if (index != null) {
bitset = this.getBsList().get(index);
if (bitset == null) {
bitset = new BitSet();
this.getBsList().add(index, bitset);
}
bitset.set(i, true);// 將str對應的位置為true,true可省略
} else {
bitset = new BitSet();
List<String> list = this.getList();
list.add(str);
index = list.size() - 1;
bitset.set(i, true);
this.getBsList().add(bitset);
this.getMap().put(str, index);
}
}
/**
* 從entity里拿出符合條件的bitset
*
* @param str
* @return
*/
public BitSet get(String str) {
BitSet bitset = null;
str = str.toLowerCase();
Integer index = this.getMap().get(str);
if (index != null) {
bitset = this.getBsList().get(index);
} else {
bitset = new BitSet();
}
return bitset;
}
/**
* bitset的與運算
*
* @param str
* @param bitset
* @return
*/
public BitSet and(String str, BitSet bitset) {
if (str != null) {
str = str.toLowerCase();
if (bitset != null) {
bitset.and(get(str));
} else {
bitset = new BitSet();
bitset.or(get(str));
}
}
return bitset;
}
/**
* bitset的或運算
*
* @param str
* @param bitset
* @return
*/
public BitSet or(String str, BitSet bitset) {
if (str != null) {
str = str.toLowerCase();
if (bitset != null) {
bitset.or(get(str));
} else {
bitset = new BitSet();
bitset.or(get(str));
}
}
return bitset;
}
/**
* 獲取bitset值為true的 即 把 bitset翻譯為list的索引
*
* @param bitset
* @return
*/
public static List<Integer> getRealIndexs(BitSet bitset) {
List<Integer> indexs = new ArrayList<Integer>();
if (bitset != null) {
int i = bitset.nextSetBit(0);
if (i != -1) {
indexs.add(i);
for (i = bitset.nextSetBit(i + 1); i >= 0; i = bitset.nextSetBit(i + 1)) {
int endOfRun = bitset.nextClearBit(i);
do {
indexs.add(i);
} while (++i < endOfRun);
}
}
}
return indexs;
}
}
為每一個user對象創建address,gender,age維度索引
public class UserIndexStore {
private static final String ADDRESS = "address";
private static final String GENDER = "gender";
private static final String AGE = "age";
private BitSetIndexModel address;
private BitSetIndexModel gender;
private BitSetIndexModel age;
private ConcurrentHashMap<Integer, User> userMap;//存儲所有的user數據
private ConcurrentHashMap<String, Integer> nameIndexMap;//name和index映射
public static final UserIndexStore INSTANCE = getInstance();
private UserIndexStore() {
init();
}
public static UserIndexStore getInstance() {
return UserIndexStoreHolder.instance;
}
private static class UserIndexStoreHolder {
private static UserIndexStore instance = new UserIndexStore();
}
private void init() {
this.address = new BitSetIndexModel(ADDRESS);
this.gender = new BitSetIndexModel(GENDER);
this.age = new BitSetIndexModel(AGE);
userMap = new ConcurrentHashMap<Integer, User>();
nameIndexMap = new ConcurrentHashMap<String, Integer>();
}
/**
* 構建索引
* @param users
*/
public void createIndex(List<User> users) {
if (users != null && users.size() > 0) {
for (int index = 0; index < users.size(); index++) {
User user = users.get(index);
createIndex(user, index);
}
}
}
private void createIndex(User user, int index) {
getAddress().update(user.getAddress(), index);
getGender().update(user.getGender(), index);
getAge().update(user.getAge(), index);
this.userMap.put(index, user);
this.nameIndexMap.put(user.getName(), index);
}
public BitSet query(String address, String gender, String age) {
BitSet bitset = null;
bitset = getAddress().and(address, bitset);
bitset = getGender().and(gender, bitset);
bitset = getAge().and(age, bitset);
return bitset;
}
public User findUser(Integer index) {
User user = this.userMap.get(index);
if (user != null) {
return user.clone();//可能會對user做修改操作,要保證記憶體原始數據不變
}
return null;
}
public BitSetIndexModel getAddress() {
return address;
}
public void setAddress(BitSetIndexModel address) {
this.address = address;
}
public BitSetIndexModel getGender() {
return gender;
}
public void setGender(BitSetIndexModel gender) {
this.gender = gender;
}
public BitSetIndexModel getAge() {
return age;
}
public void setAge(BitSetIndexModel age) {
this.age = age;
}
}
3.測試bitset
public class BitSetTest {
public static void main(String[] args) {
List<User> users = buildData();
UserIndexStore.getInstance().createIndex(users);
ExecutorService executorService = Executors.newFixedThreadPool(20);
int num = 2000;
long begin1 = System.currentTimeMillis();
for (int i = 0; i < num; i++) {
Runnable syncRunnable = new Runnable() {
@Override
public void run() {
List<Integer> indexs = BitSetIndexModel.getRealIndexs(UserIndexStore.getInstance().query("北京", "girl", "18"));
for (Integer index : indexs) {
UserIndexStore.getInstance().findUser(index);
}
}
};
executorService.execute(syncRunnable);
}
executorService.shutdown();
while (true) {
try {
if (executorService.awaitTermination(1, TimeUnit.SECONDS)) {
System.out.println("單次查詢時間為:" + (System.currentTimeMillis() - begin1) / num + "ms");
break;
}
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}
private static List<User> buildData() {
String[] addresss = { "北京", "上海", "深圳" };
String[] ages = { "16", "17", "18" };
List<User> users = new ArrayList<>();
for (int i = 0; i < 200000; i++) {
User user = new User();
user.setName("name" + i);
int rand = ThreadLocalRandom.current().nextInt(3);
user.setAddress(addresss[ThreadLocalRandom.current().nextInt(3)]);
user.setGender((rand & 1) == 0 ? "girl" : "boy");
user.setAge(ages[ThreadLocalRandom.current().nextInt(3)]);
users.add(user);
}
return users;
}
}
測試結果(查詢2w次):
數據量(users.size()) | 併發數 | 平均查詢時間
---|---|---
20w | 10 | 1ms
50w | 20 | 3ms
100w| 50 | 9ms
測試機為thinkpad x240 i5 8g記憶體
4.總結
==優點==:
通過測試發現隨著數據量的增大和併發數的提高,平均耗時並沒有明顯升高,並且響應時間都在10ms以內
==缺點==:
- 不適合數據量太大的情況,因為需要把數據全部載入進記憶體
- 不適合複雜查詢
不適合對name,id等唯一值做查詢
後記
因為我們的查詢業務比較簡單,唯一的要求是速度,並且數據量也不大,每張表的數據量都不超過100w,所以使用這種方式比較合適。
在本篇文章中只談到瞭如何創建索引,以及最基本的查詢,在下一篇中我會繼續說明如何更新索引,以及一些複雜查詢,比如<,>,between and。
轉載請註明出處