在运行istio0.8时，我在尝试使用cvallance的sidecar部署有状态的mongodb副本集时遇到了问题，如果我将istio排除在外，一切正常，但是当启用istio时，mongo-sidecars找不到彼此和副本集未配置。下面是我的mongo部署和服务。apiVersion:v1kind:Servicemetadata:labels:service:mongo-testenvironment:testname:mongo-testnamespace:testspec:ports:-name:mongoport:27017clusterIP:Noneselector:serv
在这个json中，我需要一个查找查询，它可以找到“status”:“Y”的所有字段，如果父字段有“status”:“N”，则忽略子字段，否则找到子字段其中"status":"Y"及其父字段注意:子字段在数组中[{"type":"Type1","status":"Y","code":"1","category":[{"type":"Cat1","status":"Y","code":"1000","subcategories":[{"type":"Sub1","status":"N","code":"1001"},{"type":"Sub2","status":"N","code":"1
在MongoDB中，如何返回所有符合以下条件的文档:共享特定字段的值。有一个字段等于一个值。在满足1和2的所有文档之间，它们还共同匹配输入的1到n值数组的所有字段。即，必须考虑每个值。例如，鉴于以下集合，我想匹配所有符合以下条件的文档:有同样的channelIddayOfWeek等于星期一在满足1&2的所有文档之间，它们还应该共同匹配产品ID[1,2]。即，如果我有一个channelId匹配dayOfWeek，它还必须有一个包含productId的文档1和另一个文档productId2.{channelId:"ID-A",dayOfWeek:"MONDAY",productId:"1"
如果这个键值同时存在，我们必须找到数据。1。orgId=PQR2。tagId=123这是对象数组。[{"_id":"c6114ee0",orders:[{"orgId":"ABC","tagId":"123"},{"orgId":"PQR","tagId":"456"},{"orgId":"XYZ"}]},{"_id":"c6114ee1",orders:[{"orgId":"SDE","tagId":"446"},{"orgId":"PQR","tagId":"123"},{"orgId":"UJI"}]}]输出{"_id":"c6114ee1",orders:[{"orgId":"
我使用游标在NodeJS中使用mongodb遍历>30k文档，并在此迭代期间在processFn中写入其他文档。示例代码:constcursor=collection.find({},{timeout:false}).addCursorFlag('noCursorTimeout',true);while(awaitcursor.hasNext()){constdoc=awaitcursor.next();awaitprocessFn({id:doc._id.toHexString(),...doc});}awaitcursor.close();由于未知原因，我收到随机CursorNot
我有三个集合包含如下数据，客户收藏{"_id":ObjectId("5a058e316803fafd127b23c9"),"client_name":"clientA","client_status":"A"}{"_id":ObjectId("5a058e316803fafd127b23cb"),"client_name":"clientB","client_status":"A"}池集合{"_id":ObjectId("5a0e76f66803fa530a7b23d4"),"pool_name":"poolA","pool_status":"A","client_id":Object
我正在尝试将spark(pyspark)连接到mongodb，如下所示:conf=SparkConf()conf.set('spark.mongodb.input.uri',default_mongo_uri)conf.set('spark.mongodb.output.uri',default_mongo_uri)sc=SparkContext(conf=conf)sqlContext=SQLContext(sc)spark=SparkSession\.builder\.appName("my-app")\.config("spark.mongodb.input.uri",defau
我有这个文件集:[{"name":"name1","data":[{"numbers":["1","2","3"]}]},{"name":"name2","data":[{"numbers":["2","5","3"]}]},{"name":"name3","data":[{"numbers":["1","5","2"]}]},{"name":"name4","data":[{"numbers":["1","4","3"]}]},{"name":"name5","data":[{"numbers":["1","2"]}]}]当作为参数传递的数组是data.numbers的子集时，我想获
如何获取MongoDB聚合查询执行时间？我试过这个:db.collection.explain("executionStats").aggregate([{'$match':{'$and':[{'meta.client_id':{'$eq':1}},{'meta.is_deleted':{'$ne':1}}]}},{'$group':{_id:'$Plant',value:{'$sum':1}}},{'$sort':{_id:1}}])但这是返回阶段queryPlanner、winningPlan和rejectedPlans而不是executionStats.我想获得以毫秒为单位的查询
我有一堆文件，格式如下:{_id:"5b38c85f213751038ff4d0bb",classes:[{_id:"5b38c85f21375103ytg65ju7",standard:"12",numberOfStudents:45},{_id:"5b38c85f2137510370987hgd",standard:"11",numberOfStudents:51},]}我想:按_id和特定类的_id搜索文档集合。更新该类(class)的numberOfStudents。只返回类对象。因此对于_id:"5b38c85f213751038ff4d0bb"&classes._id:"5
