This opposed to the web client, which does not have all features the thick client has. Tip: use the thick client to set up the initial user folder – use the client to create users, change the system settings and basically to configure Data Crow to fit your needs. You can choose to have the server edition set up a new empty user folder, or, you can choose to use an existing user folder. ![]() Just as the normal client does need a user folder where it stores the data and settings, the server does so too. It does require Java version 17 or higher though. That’s it – it does not require any further installation. Unzip the zipped Data Crow Server distribution to the installation location.The server edition is headless, meaning it can run in environments where there is no graphical interface. The user management function allows you to set granular user permissions per user, right down to field level. The server allows multiple users, using either of these clients (thick / web) to connect to the server, at the same time. This means that users can connect to Data Crow using the thick-client (the Data Crow application) and / or the web client (the browser). The server edition is an advanced server, a combined web and application server. This allows for clients to connect to a single instance of Data Crow. Thus, the client can be left in a bad state until the application server is rebooted, for example.Since Data Crow 4.0 it is possible to run Data Crow as a server. This results in a server-side error (not master) which is not handled appropriately by the Java driver (this is still under investigation). Using the above client connection settings, if there is a failover and a delayed DNS record update for the cluster writer endpoint, the client would still try to issue writes to the old writer (now reader after failover). MongoClient mongoClient = MongoClients.create(settings) applyToClusterSettings(builder -> builder.hosts( ![]() So even if the client settings are initialized like below, all reads would still go to the primary instead of the secondary.įinal ServerAddress serverAddress0 = new ServerAddress("cluster-endpoint", 27317)) įinal MongoCredential credential = MongoCredential.createCredential("xxx",įinal MongoClientSettings settings = MongoClientSettings.builder() This causes the client to disregard the read preference and only connect to the server configured in hosts(). When the client specifies only one host in the hosts() method, the mode is set to ClusterConnectionMode.SINGLE instead of ClusterConnectionMode.MULTIPLE The MongoClient Cluster Settings can be defined using a few different methods, such as hosts(), requiredReplicaSetName(), and mode(). This issue, first discovered in Java Mongo Driver 3.7.x, occurs when a client establishes a connection to Amazon DocumentDB using MongoClientSettings and, specifically, when chaining the applyToClusterSettings method. The Region is in the endpoint.Īuthorizing Inbound Traffic for Your Linux InstancesĪuthorizing Inbound Traffic for Your Windows InstancesĬlient read preferences are not honored and some clients cannot write to Amazon DocumentDB after failover unless they reboot. To verify the Region of your Amazon DocumentDB cluster, run theįollowing command. (us-east-1) from US West (Oregon) Region (us-west-2)-the Instance in a Region other than the cluster's Region-forĮxample, trying to connect to a cluster in US East (N. If you try to connect to an Amazon DocumentDB cluster from an Amazon EC2 For more information, see Connecting to an Amazon DocumentDBĪdditionally, if your development environment is in a differentĪmazon VPC, you can also use VPC Peering and connect to your Amazon DocumentDBĬluster from another Amazon VPC in the same region or a different To connect to an Amazon DocumentDB cluster from outside an Amazon VPC, youĬan use an SSH tunnel. Thus, you can't connectĭirectly to your Amazon DocumentDB cluster from your laptop or localĭevelopment environment outside of your VPC. Amazon DocumentDB is virtual private cloud (VPC)-only and does notĬurrently support public endpoints. Trying to connect to an Amazon DocumentDB cluster directly from a publicĮndpoint, such as your laptop or local development machine, willįail. You are trying to connect to an Amazon DocumentDBĬluster directly from your laptop or local development
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