I'm looking to implement the Spring Batch example which will read the data from Azure Databricks and write it into Postgres or any other systems.
How Spring Batch will connect to Azure Databricks and how data will be populated ?
I don't see Inbuilt ItemReader or ItemWriter is available yet? Does it plan ?
You need to connect to Azure Databricks via JDBC Connection and for one DB to another you can refer https://www.yawintutor.com/spring-boot-batch-read-from-database-and-write-to-database-example/.
Let me know , if this does help you
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I'm using Google BigQuery for OLAP, and plan to provision Google Cloud SQL (Postgres) for OLTP.
My plan is to direct stream data from Google BigQuery to Postgres.
I try googling the solution, but the option is only using batch file .
Is it possible for the streaming solution from Google BigQuery to PostgreSQL?
Currently there is no streaming read mechanism for accessing bigquery data as mentioned in this Stackoverflow post.
Hence, you'll have to go for reading data through batch process.
You can also setup manual ETL process to integrate BigQuery to PostgreSQL using Cloud Data Fusion as mentioned in this article.
I am trying to migrate a Datawarehouse to Delta lake. One thing that I am struggling to figure out is how to connect to Delta Lake (silver and gold) tables outside a spark session. I want to able to connect to these tables using BI tools like Tableau. I am not using databricks and I was wondering if storing these tables in the hive metastore could help. If not this then could someone help me with an alternative approach or if this is feasible or not.
You can have a Hive metastore and a Thrift server with Spark open source and delta.io open source then connect Tableau desktop for instance.
I'm currently working in a Mainframe Technology where we store the data in IBM DB2.
We got a new requirement to use scalable process to migrate the data to a new messaging platform including new database. For that we have identified Kafka is a suitable solution with either KSQLDB or MONGODB.
Can someone able to tell or direct me on how can we connect to IBM DB2 from Kafka to import the data and place it in either KSQLDB or MONGODB?
Any help is much appreciated.
To import the data from IBM DB2 into Kafka, You need to use any connector like the Debezium connector for DB2.
The information regarding the connector can be found in the following.
https://debezium.io/documentation/reference/connectors/db2.html
Connector Configuration
You can also use JDBC Source Connector for the same functionality. The following links are helpful for the configuration.
https://www.confluent.io/blog/kafka-connect-deep-dive-jdbc-source-connector/
A Simple diagram for events flows from RDMS to Kafka topic.
After placing the data into Kafka, we need to transfer that data MongoDb. We need to use Mongo Db Connector to transfer the data from Kafka to mongo Db.
https://www.mongodb.com/blog/post/getting-started-with-the-mongodb-connector-for-apache-kafka-and-mongodb-atlas
https://www.confluent.io/hub/mongodb/kafka-connect-mongodb
We are using Kafka connect S3 sink connector that connect to Kafka and load data to S3 buckets.Now I want to load data from S3 buckets to AWS Redshift using Copy command, for that I'm creating my own custom connector.Use case is I want to load data that created over S3 to Redshift in synchronous way, and then next time S3 connector should replace the existing file and again our custom connector load data to S3.
How can I do this using Confluent Kafka Connect,or my other better approach to do same task?
Thanks in advance !
If you want data to Redshift, you should probably just use the JDBC Sink Connector and download the Redshift JDBC Driver into the kafka-connect-jdbc directory.
Otherwise, rather than writing a Connector, you could use Lambda to trigger some type of S3 event notification to do some type of Redshift upload
Alternatively, if you are simply looking to query S3 data, you could use Athena instead without dealing with any databases
But basically, Sink Connectors don't communicate between one another. They are independent tasks that are designed to initially consume from a topic and write to a destination, not necessarily trigger external, downstream systems.
You want to achieve synchronous behaviour from Kafka to redshift then S3 sink connector is not right option.
If you are using S3 sink connector then first put the data into s3 and then externally run copy command to push to S3. ( Copy command is extra overhead )
No customize code or validation can happen before pushing to redshift.
Redshift sink connector has come up with native jdbc library which is equivalent fast to S3 copy command.
In my spring batch project i am reading data from db and write data to db, when i checked the dynatrace after job completed, i am not able to see the db select and insert queries in dynatrace.
Is any configuration need to do in spring batch to get these queries in dynatrace ?
Thanks!