[Mongodb Java Driver Batch Insert
Betty Neyhart
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We will look into MongoDB bulk insert today. Multiple documents can be inserted at a time in MongoDB using bulk insert operation where an array of documents is passed to the insert method as parameter.
MongoDB bulk insert performs ordered insert by default. If an error occurs during the insertion at a certain point, the insertion does not happen for the remaining documents. Lets see an example of how to insert multiple documents using mongodb bulk insert through command line.
Read more about MongoDB find and MongoDB insert operations. While inserting it is not mandatory for user to provide all the fields in the query. Now lets see how the insert works when some of the fields are not specified.
In this example, for the second document, the id field is not specified by the user and for the third document only id, name and speed fields are supplied in the query. The query does a successful insertion even though some fields are missing in the second and third documents. The nInserted column says that three documents were inserted. Invoke find method and check the inserted documents.
This method performs an insert operation in bulk numbers. It is introduced from version 2.6 onwards. The syntax is Bulk.insert(). document: specifies the document to be inserted. Now we shall see the example for bulk insertion.
An unordered list named carbulk is created and insert query is specified with the fields, values to be inserted. Note that it is necessary to call the execute() method following the last insert statement to ensure that the data is actually inserted into the database.
Dear Pankaj, I am trying to compile your java class MongoDBBulkInsert in my IntelliJ IDEA, in which I have a SBT project, following import are showing red, it means I need to resolve dependency in build.sbt please help me what dependency I need. import com.mongodb.BulkWriteOperation; import com.mongodb.BulkWriteResult;
Inserting 1 million documents (See the sample document section) using bulk write, the performance starts to degrade when I use a batch size larger than 1000. The following is the execution times of the sample code using different batch sizes.
Also the 3.6.2 is a pretty old version with lots of revisions released since then with many performance improvements. I would not test performance on this version what so ever ( always use latest for testing 3.6.19)
Thanks for the explanation. It makes more sense to me now. I have verified the performance against newer versions of MongoDB. The execution results with batch size 1000 for 3.6.19 and 4.2.8 are as follows:
The performance on 4.2.8 seems a bit slower than 3.6.19 for some reason. Could it be due to a new feature in 4.2 ? Note that I am using MongoDB java driver 3.12.7 and the servers are plain docker containers created from the images in Docker.
Document can be either a Clojure map (in the majority of cases, it is)or an instance of com.mongodb.DBObject (referred to later asDBObject). In case your application obtains DBObjects from otherlibraries (for example), you can insert those:
If you insert a document without the :_id key, MongoDB Java driverthat Monger uses under the hood will generate one foryou. Unfortunately, it does so by mutating the document you passit. With Clojure's immutable data structures, that won't work the wayMongoDB Java driver authors expected.
Document ids in MongoDB do not have to be of the object id type, theyalso can be strings, integers and any value you can store that MongoDBknows how to compare order (sort). However, using ObjectIds isusually a good idea.
Sometimes you need to insert a batch of documents all at once and you need it to be done efficiently. MongoDB supports batchinserts feature. To do it with Monger, use monger.collection/insert-batch function:
In real world applications, things often go wrong. Insert operationsmay fail for one reason or another (from duplicate _id key tonetwork outages to hardware failures to everything in between). Mongerprovides monger.result namespace with several functions that checkMongoDB responses for success:
Monger does not handle data validation but it comes with a smallstandalone Clojure validation librarycalled Validateur. Validateur is inspired by Ruby's ActiveModel. Ithas two central concepts: validators and validation sets.
By default Monger will use WriteConcern/ACKNOWLEDGED as writeconcern. Historically, MongoDB Java driver (as well as other officialdrivers) have very unsafe defaults when no exceptions are raised,even for network issues. This does not sound like a good default formost applications: many applications use MongoDB because of theflexibility, not extreme write throughput requirements.
In many applications, most operations are not performance-sensitivebut a few are. Some kinds of data can be lost but some is absolutelycruicial to system/company operation. For those cases, MongoDB andMonger allow developers to trade some write throughput for safety (orvice versa) by specifying a different write concern value forindividual operations:
This section provides some basic introduction to Spring and Document databases. The rest of the document refers only to Spring Data MongoDB features and assumes the user is familiar with MongoDB and Spring concepts.
While you need not know the Spring APIs, understanding the concepts behind them is important. At a minimum, the idea behind Inversion of Control (IoC) should be familiar, and you should be familiar with whatever IoC container you choose to use.
The core functionality of the MongoDB support can be used directly, with no need to invoke the IoC services of the Spring Container. This is much like JdbcTemplate, which can be used "'standalone'" without any other services of the Spring container. To leverage all the features of Spring Data MongoDB, such as the repository support, you need to configure some parts of the library to use Spring.
To learn more about Spring, you can refer to the comprehensive documentation that explains the Spring Framework in detail. There are a lot of articles, blog entries, and books on the subject. See the Spring framework home page for more information.
NoSQL stores have taken the storage world by storm. It is a vast domain with a plethora of solutions, terms, and patterns (to make things worse, even the term itself has multiple meanings). While some of the principles are common, you must be familiar with MongoDB to some degree. The best way to get acquainted is to read the documentation and follow the examples. It usually does not take more then 5-10 minutes to go through them and, especially if you are coming from an RDMBS-only background, these exercises can be an eye opener.
The following compatibility matrix summarizes Spring Data versions to MongoDB driver/database versions.Database versions show the highest supported server version that pass the Spring Data test suite.You can use newer server versions unless your application uses functionality that is affected by changes in the MongoDB server.
Learning a new framework is not always straightforward.In this section, we try to provide what we think is an easy-to-follow guide for starting with the Spring Data MongoDB module.However, if you encounter issues or you need advice, feel free to use one of the following links:
For information on the Spring Data Mongo source code repository, nightly builds, and snapshot artifacts, see the Spring Data Mongo homepage. You can help make Spring Data best serve the needs of the Spring community by interacting with developers through the Community on Stack Overflow. To follow developer activity, look for the mailing list information on the Spring Data Mongo homepage. If you encounter a bug or want to suggest an improvement, please create a ticket on the Spring Data issue tracker. To stay up to date with the latest news and announcements in the Spring eco system, subscribe to the Spring Community Portal. You can also follow the Spring blog or the project team on Twitter (SpringData).
Spring Data MongoDB 3.x requires the MongoDB Java Driver 4.x.
The 4.0 MongoDB Java Driver does no longer support certain features that have already been deprecated in one of the last minor versions.Some of the changes affect the initial setup configuration as well as compile/runtime features.We summarized the most typical changes one might encounter.
Depending on the application one of the mongodb-driver-sync, mongodb-driver-reactivestreams artifacts is is required next to the mandatory mongodb-driver-core.It is possible to combine the sync and reactive drivers in one application if needed.
Annotation based index creation is now turned OFF by default and needs to be enabled eg. when relying on @GeoSpatialIndexed.Please refer to Index Creation on how to create indexes programmatically.
For most tasks, you should use MongoTemplate or the Repository support, which both leverage the rich mapping functionality. MongoTemplate is the place to look for accessing functionality such as incrementing counters or ad-hoc CRUD operations. MongoTemplate also provides callback methods so that it is easy for you to get the low-level API artifacts, such as com.mongodb.client.MongoDatabase, to communicate directly with MongoDB. The goal with naming conventions on various API artifacts is to copy those in the base MongoDB Java driver so you can easily map your existing knowledge onto the Spring APIs.
First, you need to set up a running MongoDB server. Refer to the MongoDB Quick Start guide for an explanation on how to startup a MongoDB instance. Once installed, starting MongoDB is typically a matter of running the following command: $MONGO_HOME/bin/mongod
One of the first tasks when using MongoDB and Spring is to create a com.mongodb.client.MongoClient object using the IoC container. There are two main ways to do this, either by using Java-based bean metadata or by using XML-based bean metadata. Both are discussed in the following sections.
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