dbt-databricks
Apache Flink
dbt-databricks | Apache Flink | |
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15 | 9 | |
180 | 23,190 | |
1.7% | 0.7% | |
9.5 | 9.9 | |
14 days ago | 2 days ago | |
Python | Java | |
Apache License 2.0 | Apache License 2.0 |
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dbt-databricks
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Curious if anyone has adopted a stack to do raw data ingestion in Databricks?
Our current data infra looks a little something like this: 1. Airbyte deployed on EKS for supported data connectors. I’m using the alpha Databricks connector to load directly into Unity Catalog. 1a. S3 bucket for raw landing zone storage if we cannot directly load into Databricks Managed Tables. 2. Orchestration, storage, and transformations are in Databricks. Calling out to the Airbyte api in the EKS cluster to keep all orchestrations inside Databricks. 2a. databricks-dbt for transformations & cleaning.
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dolly-v2-12b
dolly-v2-12bis a 12 billion parameter causal language model created by Databricks that is derived from EleutherAI’s Pythia-12b and fine-tuned on a ~15K record instruction corpus generated by Databricks employees and released under a permissive license (CC-BY-SA)
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Any suggestions for building DBT project on DataBricks?
Read this https://github.com/databricks/dbt-databricks
- dummy
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Clickstream data analysis with Databricks and Redpanda
Global organizations need a way to process the massive amounts of data they produce for real-time decision making. They often utilize event-streaming tools like Redpanda with stream-processing tools like Databricks for this purpose.
- Next step for my career..
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DeWitt Clause, or Can You Benchmark %DATABASE% and Get Away With It
Databricks, a data lakehouse company founded by the creators of Apache Spark, published a blog post claiming that it set a new data warehousing performance record in 100 TB TPC-DS benchmark. It was also mentioned that Databricks was 2.7x faster and 12x better in terms of price performance compared to Snowflake.
- Would you use dbt with databricks? If so, why?
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Welcome, DataEngHack online!
databricks
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A Quick Start to Databricks on AWS
Go to Databricks and click the Try Databricks button. Fill in the form and Select AWS as your desired platform afterward.
Apache Flink
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First 15 Open Source Advent projects
7. Apache Flink | Github | tutorial
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Pyflink : Flink DataStream (KafkaSource) API to consume from Kafka
Does anyone have fully running Pyflink code snippet to read from Kafka using the new Flink DataStream (KafkaSource) API and just print out the output to console or write it out to a file. Most of the examples and the official Flink GitHubare using the old API (FlinkKafkaConsumer).
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I keep getting build failure when I try to run mvn clean compile package
I'm trying to use https://github.com/mauricioaniche/ck to analyze the ck metrics of https://github.com/apache/flink. I have the latest version of java downloaded and I have the latest version of apache maven downloaded too. My environment variables are set correctly. I'm in the correct directory as well. However, when I run mvn clean compile package in powershell it always says build error. I've tried looking up the errors but there's so many. https://imgur.com/a/Zk8Snsa I'm very new to programming in general so any suggestions would be appreciated.
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How do I determine what the dependencies are when I make pom.xml file?
Looking at the project on github, it seems like they should have a pom in the root dir https://github.com/apache/flink/blob/master/pom.xml
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Akka is moving away from Open Source
Akka is used only as a possible RPC implementation, isn't it?
- We Are Changing the License for Akka
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DeWitt Clause, or Can You Benchmark %DATABASE% and Get Away With It
Apache Drill, Druid, Flink, Hive, Kafka, Spark
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Computation reuse via fusion in Amazon Athena
It took me some time to get a good grasp of the power of SQL; and it really kicked in when I learned about optimization rules. It's a program that you rewrite, just like an optimizing compiler would.
You state what you want; you have different ways to fetch and match and massage data; and you can search through this space to produce a physical plan. Hopefully you used knowledge to weight parts to be optimized (table statistics, like Java's JIT would detect hot spots).
I find it fascinating to peer through database code to see what is going on. Lately, there's been new advances towards streaming databases, which bring a whole new design space. For example, now you have latency of individual new rows to optimize for, as opposed to batch it whole to optimize the latency of a dataset. Batch scanning will be benefit from better use of your CPU caches.
And maybe you could have a hybrid system which reads history from a log and aggregates in a batched manner, and then switches to another execution plan when it reaches the end of the log.
If you want to have a peek at that here are Flink's set of rules [1], generic and stream-specific ones. The names can be cryptic, but usually give a good sense of what is going on. For example: PushFilterIntoTableSourceScanRule makes the WHERE clause apply the earliest possible, to save some CPU/network bandwidth further down. PushPartitionIntoTableSourceScanRule tries to make a fan-out/shuffle happen the earliest possible, so that parallelism can be made use of.
[1] https://github.com/apache/flink/blob/5f8fb304fb5d68cdb0b3e3c...
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Avro SpecificRecord File Sink using apache flink is not compiling due to error incompatible types: FileSink<?> cannot be converted to SinkFunction<?>
[1]: https://mvnrepository.com/artifact/org.apache.avro/avro-maven-plugin/1.8.2 [2]: https://github.com/apache/flink/blob/master/flink-connectors/flink-connector-files/src/main/java/org/apache/flink/connector/file/sink/FileSink.java [3]: https://ci.apache.org/projects/flink/flink-docs-master/docs/connectors/datastream/file_sink/ [4]: https://github.com/apache/flink/blob/c81b831d5fe08d328251d91f4f255b1508a9feb4/flink-end-to-end-tests/flink-file-sink-test/src/main/java/FileSinkProgram.java [5]: https://github.com/rajcspsg/streaming-file-sink-demo
What are some alternatives?
dbt-spark - dbt-spark contains all of the code enabling dbt to work with Apache Spark and Databricks
Trino - Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
Neo4j - Graphs for Everyone
Deeplearning4j - Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learning using automatic differentiation.
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
TimescaleDB - An open-source time-series SQL database optimized for fast ingest and complex queries. Packaged as a PostgreSQL extension.
H2O - Sparkling Water provides H2O functionality inside Spark cluster
sql_to_ibis - A Python package that parses sql and converts it to ibis expressions
Scio - A Scala API for Apache Beam and Google Cloud Dataflow.
nutter - Testing framework for Databricks notebooks
Apache Kafka - Mirror of Apache Kafka