Java通过mongo-java-driver-3.0+查询mongodb数据库

本文以mongo-java-driver-3.5.0.jar为例

1 基本查询关键字（对应的sql语句）：

MongoDB Aggregation Operators	SQL Terms, Functions, and Concepts
$match	WHERE/HAVING
$group	GROUP BY
$project	SELECT
$limit	LIMIT
$sort (降序:-1 升序:1)	ORDER BY (降序:DESC 升序:ASC默认)
$skip 跳过n个	持久化框架有接口
$sum	SUM()/COUNT()
$in	IN()
$nin	NOT IN()
$or	OR
$and	AND
$regex 模糊查询	LIKE
$gt	>
$gte	>=
$lt	<
$lte	<=
$ne	!=
	=

2 构造复杂查询条件的3种方法：

2.1 测试数据

{ "_id" : { "$oid" : "59c8cbea6157d6c78dab4ff0" }, "name" : "yy", "password" : "123", "nickname" : "ygirl2", "iid" : 2 }
{ "_id" : { "$oid" : "59c9c1393471f5330c65ccd2" }, "name" : "nie", "password" : "nie", "nickname" : "nn", "iid" : 8 }
{ "_id" : { "$oid" : "59c9ec75a4e55c541a000003" }, "name" : "yy", "password" : "123", "nickname" : "ygirl2", "iid" : 8.0, "isRead" : false, "createTime" : { "$date" : 1506405705952 }, "money" : 88.88 }
{ "_id" : { "$oid" : "59b34277beca1aaeaf1d1fbe" }, "name" : "yan", "password" : "ygirlyan", "nickname" : "ygirl2", "iid" : 3.0 }
{ "_id" : { "$oid" : "59b34282beca1aaeaf1d1fbf" }, "name" : "yan", "password" : "ygirlyan", "nickname" : "ygirl2", "iid" : 4.0 }

2.3 实现构造复杂查询条件的3种方法：

public static MongoCollection<Document> connect() {
@SuppressWarnings("resource")
MongoClient client = new MongoClient("127.0.0.1", 27017);
MongoDatabase db = client.getDatabase("test");
MongoCollection<Document> collection = db.getCollection("user");
return collection;
}

public static List<Document> findBy(Bson filter) {
List<Document> results = new ArrayList<Document>();
FindIterable<Document> iterables = connect().find(filter);
MongoCursor<Document> cursor = iterables.iterator();
while (cursor.hasNext()) {
results.add(cursor.next());
}

return results;
}
public static List<Document> findBy1(DBObject filter) {
List<Document> results = new ArrayList<Document>();
FindIterable<Document> iterables = connect().find((Bson) filter);
MongoCursor<Document> cursor = iterables.iterator();
while (cursor.hasNext()) {
results.add(cursor.next());
}

return results;
}

// 方法1：运用Filters.and添加复合条件；
@Test
public void testFindByLickQuery2(){
int iid = 2;
String name = "yy";
String nickname = "ygirl2";
Bson filter = null;
if (iid >= 0) {
if (name != "") {
if (nickname != "") {
filter = Filters.and(Filters.gte("iid", iid), Filters.eq("nickname", nickname), Filters.regex("name", name));
} else {
filter = Filters.and(Filters.gte("iid", iid), Filters.regex("name", name));
}
} else {
if (nickname != "") {
filter = Filters.and(Filters.gte("iid", iid), Filters.eq("nickname", nickname));
} else {
filter = Filters.and(Filters.gte("iid", iid));
}
}
} else {
if (name != "") {
if (nickname != "") {
filter = Filters.and(Filters.eq("nickname", nickname), Filters.regex("name", name));
} else {
filter = Filters.and(Filters.regex("name", name));
}
} else {
if (nickname != "") {
filter = Filters.and(Filters.eq("nickname", nickname));
} else {
filter = Filters.and();
}
}
}
List<Document> results = findBy(filter);
for(Document doc : results){
System.out.println(doc.toJson());
}
// { "_id" : { "$oid" : "59c8cbea6157d6c78dab4ff0" }, "name" : "yy", "password" : "123", "nickname" : "ygirl2", "iid" : 2 }
// { "_id" : { "$oid" : "59c9ec75a4e55c541a000003" }, "name" : "yy", "password" : "123", "nickname" : "ygirl2", "iid" : 8.0, "isRead" : false, "createTime" : { "$date" : 1506405705952 }, "money" : 88.88 }
}

// 方法2：运用Document filter.append添加复合条件；
@Test
public void testFindByLickQuery1(){
int iid = 3, iid2 = 4;
String name = "";
String nickname = "";
Document filter = new Document();
if (iid >= 0) {
filter.append("iid", new Document("$gte", iid));
}
// 得到iid<=4结果；
// iid>=3条件被覆盖，Document.append不适合在同一个结果添加多个条件
if (iid2 >= 0) {
filter.append("iid", new Document("$lte", iid2));

}
if (name != "") {
filter.append("name",new Document("$regex", name));
}
if (nickname != "") {
filter.append("nickname",nickname);
}

List<Document> results = findBy(filter);
for(Document doc : results){
System.out.println(doc.toJson());
}
// { "_id" : { "$oid" : "59c8cbea6157d6c78dab4ff0" }, "name" : "yy", "password" : "123", "nickname" : "ygirl2", "iid" : 2 }
// { "_id" : { "$oid" : "59b34277beca1aaeaf1d1fbe" }, "name" : "yan", "password" : "ygirlyan", "nickname" : "ygirl2", "iid" : 3.0 }
// { "_id" : { "$oid" : "59b34282beca1aaeaf1d1fbf" }, "name" : "yan", "password" : "ygirlyan", "nickname" : "ygirl2", "iid" : 4.0 }
}

// 方法3：运用DBObject.put添加复合条件；
@Test
public void testFindByLickQuery1Copy(){
int iid = 3, iid2 = 4;
String name = "";
String nickname = "";
DBObject filter = new BasicDBObject();
if (iid >= 0) {
filter.put("iid", new BasicDBObject("$gte", iid));
}
// 得到iid<=4结果；
// iid>=3条件被覆盖，Document.append不适合在同一个结果添加多个条件
if (iid2 >= 0) {
if (iid >= 0) {
BasicDBObject[] queryObjectAnd =  new BasicDBObject[] { new BasicDBObject("iid", new BasicDBObject("$gte", iid)),
new BasicDBObject("iid", new BasicDBObject("$lte", iid2)) };
filter.put("$and", queryObjectAnd);
} else {
filter.put("iid",  new BasicDBObject("$lte", iid2));
}

}
if (name != "") {
filter.put("name",new BasicDBObject("$regex", name));
}
if (nickname != "") {
filter.put("nickname",nickname);
}

List<Document> results = findBy1(filter);
for(Document doc : results){
System.out.println(doc.toJson());
}
// { "_id" : { "$oid" : "59b34277beca1aaeaf1d1fbe" }, "name" : "yan", "password" : "ygirlyan", "nickname" : "ygirl2", "iid" : 3.0 }
// { "_id" : { "$oid" : "59b34282beca1aaeaf1d1fbf" }, "name" : "yan", "password" : "ygirlyan", "nickname" : "ygirl2", "iid" : 4.0 }
}

2.3 分析构造复杂查询条件的3种方法异同：

方法	实现	难易程度	能否给同一个字段加大于1个约束条件	适用于
方法1	Bson filter=Filters.and(Filters 1,…)	条件越多实现越困难，if-else越复杂	能	查询条件少且固定永远不变
方法2	Document f=append(key, v) Document f=append(key, newBasicDBObject(“$gte”,v))	条件越多实现不会太困难	不能，后面的append条件会覆盖前面的	查询条件多且每个属性查询条件<=1
方法3	DBObject filter=put(“iid”,new BasicDBObject(“$gte”,v));	条件越多实现不会太困难	能	适用于一切查询，特别适用于复杂条件查询应用

3 其他查询关键字应用：

3.1 String类型按条件聚合

@Test
public void testGroup() {
/* Group操作*/
//DBObject groupFields = new BasicDBObject("_id", new BasicDBObject("name", "$name").append("nickname", "$nickname"));
// 1 加入标志项_id，即聚合字段值;
DBObject groupFields = new BasicDBObject("_id", "$name");
// 2 加入统计数count，即聚合个数；
groupFields.put("count", new BasicDBObject("$sum", 1));
DBObject group = new BasicDBObject("$group", groupFields);

// 排序操作  ，按count降序
DBObject sortchBasicDBObjet = new BasicDBObject("$sort", new BasicDBObject("count",-1));

// 分页操作.skip(startRow)，首先取2个记录，再跳过1个记录取出第二个记录显示出来；
DBObject limitBasicDBObjet = new BasicDBObject("$limit",2);
DBObject limitBasicDBObjet2 = new BasicDBObject("$skip",2);

// project 操作  : 过滤查询显示字段个数,db.books.aggregate( [ { $project : { _id: 0, name : 1 , password : 1 }]);只显示name和password
// DBObject projectBasicDBObjet = new BasicDBObject("$project", new BasicDBObject("_id",0).append("times", "$_id.times").append("user_id", "$_id.user_id").append("user_account", "$_id.user_account").append("count", 1));
List<Bson> list = new ArrayList<Bson>();
list.add((Bson) group);
list.add((Bson) sortchBasicDBObjet);
// $limit和$skip   add到list顺序不一样，结果不一样
list.add((Bson) limitBasicDBObjet2);
list.add((Bson) limitBasicDBObjet);
// list.add((Bson) limitBasicDBObjet2);
List<Document> results = MongoDb.group(list);;
for(Document doc : results){
System.out.println(doc.toJson());
}
}

/*
*
* isRead  "0"表示未读，"1"表示已读
*/
public List<Object> findIfreadAlarmLog(String isRead, String CommunityName, String EQAddress) {
MongoCollection<Document> collection = getMongodbCollection();
// 添加统计统计
//DBObject matchBasicDBObjet = new BasicDBObject("$match",new BasicDBObject("IsRead", "0"));
DBObject queryCondition = new BasicDBObject();
queryCondition.put("IsRead", isRead);
if (CommunityName != null && !"".equals(CommunityName)) {
// 模糊匹配
queryCondition.put("CommunityName", new BasicDBObject("$regex", CommunityName));
}
if (EQAddress != null && !"".equals(EQAddress)) {
// 模糊匹配
queryCondition.put("EQAddress", new BasicDBObject("$regex", EQAddress));
}
DBObject matchBasicDBObjet = new BasicDBObject("$match", queryCondition);

// 添加统计条件
DBObject groupFields = new BasicDBObject("_id", new BasicDBObject("CommunityID", "$CommunityID").append("CommunityName", "$CommunityName").append("EQName", "$EQName")
.append("EQAccount", "$EQAccount").append("EQAddress", "$EQAddress").append("Coordinate", "$Coordinate").append("SingleCoordinate", "$SingleCoordinate"));
// 加入统计数count，即聚合个数；
groupFields.put("count", new BasicDBObject("$sum", 1));
DBObject group = new BasicDBObject("$group", groupFields);

// 添加显示条件
DBObject projectBasicDBObjet = new BasicDBObject("$project", new BasicDBObject("_id",0).append("CommunityID", "$_id.CommunityID").append("CommunityName", "$_id.CommunityName").append("EQName", "$_id.EQName")
.append("EQAccount", "$_id.EQAccount").append("EQAddress", "$_id.EQAddress").append("Coordinate", "$_id.Coordinate").append("SingleCoordinate", "$_id.SingleCoordinate").append("count", 1));
List<Bson> list = new ArrayList<Bson>();
list.add((Bson) matchBasicDBObjet);
list.add((Bson) group);
list.add((Bson) projectBasicDBObjet);
AggregateIterable<Document> iterables = collection.aggregate(list);
List<Object> results = new ArrayList<Object>();
MongoCursor<Document> cursor = iterables.iterator();
while (cursor.hasNext()) {
results.add(cursor.next());
}
return results;
}

3.2 json格式的查询

/*
* 先转换为Object再查询
*/
public List<String> getHouseHouseAccounts(List<Object> singleCoords , String isRead) {
MongoCollection<Document> collection = getMongodbCollection();
DBObject queryCondition = new BasicDBObject();
List<String> resultArray = new ArrayList<String>();
// 报错：org.bson.codecs.configuration.CodecConfigurationException: Can't find a codec for class cn.com.vo.Point.,Point包含lng，lat属性
// queryCondition.put("SingleCoordinate", JsonUtils.jsonToPojo(singleCoord, Point.class));

// 返回空
//queryCondition.put("SingleCoordinate", singleCoord);

// 成功返回，(DBObject) JSON.parse(singleCoord)=JSON.parse(singleCoord)={ "lng" : 102.731653 , "lat" : 25.052474}，88:H20170926000002     88:H20170926000003,H20170926000004
//queryCondition.put("SingleCoordinate", JSON.parse(singleCoord));

// 成功返回，JsonUtils.jsonToPojo(singleCoord, Object.class)={lng=102.731653, lat=25.052474}，88:H20170926000002     88:H20170926000003,H20170926000004
for (Object object : singleCoords) {
//queryCondition.put("SingleCoordinate", JsonUtils.jsonToPojo(singleCoord, Object.class));
queryCondition.put("SingleCoordinate", object);
queryCondition.put("IsRead", isRead);
List<Object> list = new ArrayList<Object>();
FindIterable<Document> findIterable =collection.find((Bson) queryCondition);
MongoCursor<Document> mongoCursor = findIterable.iterator();
while(mongoCursor.hasNext()){
Document document=mongoCursor.next();
list.add(document);
}
List<AlarmLog> alarmLogLists = JsonUtils.jsonToList(JsonUtils.objectToJson(list), AlarmLog.class);
for (AlarmLog alarmLog : alarmLogLists) {
resultArray.add("'" + alarmLog.getHouseAccount() + "'");
}
}

//return StringUtils.collectionToDelimitedString(resultArray, ",");
return resultArray;
}

3.3 $or和$and关键字查询

/**
* Document  OR  AND 查询:db.user.find({"likes": {$gt:50}, $or: [{"by": "菜鸟教程"},{"title": "MongoDB 教程"}]}).pretty()；
* 适合少条件且条件不变的查询，适合单字段多条件查询
*/
@Test
public void testFindByOrAnd(){
// (查询iid等于2或者iid等于8的数据)  失败   只能查到8
Document filter = new Document();
filter.append("iid", 2);
filter.append("iid", 8);
List<Document> results = MongoDb.findBy(filter);

// $or (查询iid等于2或者iid等于8的数据)
BasicDBObject queryObjectOr = new BasicDBObject().append(
"$or",
new BasicDBObject[] { new BasicDBObject("iid", 2),
new BasicDBObject("iid", 8) });

// (查询iid等于2并且name等于nie的数据)   成功查出相应数据
Document filter2 = new Document();
filter2.append("iid", 2);
filter2.append("name", "yy");
List<Document> results2 = MongoDb.findBy(filter2);

// $and(查询iid等于2并且name等于nie的数据)
BasicDBObject queryObjectAnd = new BasicDBObject().append("$and",
new BasicDBObject[] { new BasicDBObject("iid", 2),
new BasicDBObject("name", "yy") });
List<Document> results3 = MongoDb.findBy(queryObjectOr);
List<Document> results4 = MongoDb.findBy(queryObjectAnd);
for(Document doc : results){
System.out.println(doc.toJson());
}
System.out.println("==========");
for(Document doc : results3){
System.out.println(doc.toJson());
}
System.out.println("==========");
for(Document doc : results4){
System.out.println(doc.toJson());
}
System.out.println("==========");
for(Document doc : results2){
System.out.println(doc.toJson());
}
// { "_id" : { "$oid" : "59c9c1393471f5330c65ccd2" }, "name" : "nie", "password" : "nie", "nickname" : "nn", "iid" : 8 }
// { "_id" : { "$oid" : "59c9ec75a4e55c541a000003" }, "name" : "yy", "password" : "123", "nickname" : "ygirl2", "iid" : 8.0, "isRead" : false, "createTime" : { "$date" : 1506405705952 }, "money" : 88.88 }
// ==========
// { "_id" : { "$oid" : "59c8cbea6157d6c78dab4ff0" }, "name" : "yy", "password" : "123", "nickname" : "ygirl2", "iid" : 2 }
// { "_id" : { "$oid" : "59c9c1393471f5330c65ccd2" }, "name" : "nie", "password" : "nie", "nickname" : "nn", "iid" : 8 }
// { "_id" : { "$oid" : "59c9ec75a4e55c541a000003" }, "name" : "yy", "password" : "123", "nickname" : "ygirl2", "iid" : 8.0, "isRead" : false, "createTime" : { "$date" : 1506405705952 }, "money" : 88.88 }
// ==========
// { "_id" : { "$oid" : "59c8cbea6157d6c78dab4ff0" }, "name" : "yy", "password" : "123", "nickname" : "ygirl2", "iid" : 2 }
// ==========
// { "_id" : { "$oid" : "59c8cbea6157d6c78dab4ff0" }, "name" : "yy", "password" : "123", "nickname" : "ygirl2", "iid" : 2 }

}

3.4$in和$nin关键字查询

/**
* Document  in  nin 查询
*/
@Test
public void testFindByInNin(){

// $in  （查询iid为1和2的数据）
BasicDBObject queryObjectIn = new BasicDBObject().append("iid", new BasicDBObject(
"$in", new int[] { 2, 8 }));
// $nin  （查询iid不为1,2,3,4,5,6,7,8,9的数据）
BasicDBObject queryObjectNin = new BasicDBObject().append("iid", new BasicDBObject(
"$nin", new int[] { 2, 9 }));
List<Document> results3 = MongoDb.findBy(queryObjectIn);
List<Document> results4 = MongoDb.findBy(queryObjectNin);
for(Document doc : results3){
System.out.println(doc.toJson());
}
// { "_id" : { "$oid" : "59c8cbea6157d6c78dab4ff0" }, "name" : "yy", "password" : "123", "nickname" : "ygirl2", "iid" : 2 }
// { "_id" : { "$oid" : "59c9c1393471f5330c65ccd2" }, "name" : "nie", "password" : "nie", "nickname" : "nn", "iid" : 8 }
// { "_id" : { "$oid" : "59c9ec75a4e55c541a000003" }, "name" : "yy", "password" : "123", "nickname" : "ygirl2", "iid" : 8.0, "isRead" : false, "createTime" : { "$date" : 1506405705952 }, "money" : 88.88 }
}