nodejs-bigquery
Apache Spark
nodejs-bigquery | Apache Spark | |
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43 | 101 | |
457 | 38,414 | |
0.9% | 0.7% | |
8.0 | 10.0 | |
2 days ago | 1 day ago | |
TypeScript | Scala | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
nodejs-bigquery
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Wrangling BigQuery at Reddit
If you've ever wondered what it's like to manage a BigQuery instance at Reddit scale, know that it's exactly like smaller systems just with much, much bigger numbers in the logs. Database management fundamentals are eerily similar regardless of scale or platform; BigQuery handles just about anything we throw at it, and we do indeed throw it the whole book. Our BigQuery platform is more than 100 petabytes of data that supports data science, machine learning, and analytics workloads that drive experiments, analytics, advertising, revenue, safety, and more. As Reddit grew, so did the workload velocity and complexity within BigQuery and thus the need for more elegant and fine-tuned workload management.
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Building a dev.to analytics dashboard using OpenSearch
Now I know I've got some data I could use, I now need to find a platform that I can use to analyse the data coming from the Forem API. I did consider some other pieces of software, such as Google BigQuery (with looker studio) and ElasticSearch (with Kibana), I ultimately went with OpenSearch which is essentially a forked version of ElasticSearch maintained by AWS. The main reasons are that I could host it locally for free (unlike BigQuery). I do have some prior experience with both elastic (back when it was called ELK) and OpenSearch, but my work with OpenSearch was far more recent, so I decided to go with that.
- Como evitar SQL Injection utilizando client do BigQuery
- Learning Excel. Is there a resource for fake data sets like retail and wholesale inventories and sales histories etc for testing and practice?
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How to Totally Fubar Your Cloud Infrastructure Costs
First, in one of our recent projects, we helped our client to run the cloud-based infrastructure of their entirely automated, real-time SEO platform. The solution rested in the safe familiarity of Google’s popular cloud-based data centres (i.e. Google Cloud Platform), whilst also making use of BigQuery — a serverless, multi-cloud data warehouse.
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Data Analytics at Potloc I: Making data integrity your priority with Elementary & Meltano
Bigquery as our data warehouse
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I've tried really hard but need some help please. Bigquery not returning data after 2019.
This post in github thinks it may be an error in bigquery's backend.
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Deploying a Data Warehouse with Pulumi and Amazon Redshift
A data warehouse is a specialized database that's purpose built for gathering and analyzing data. Unlike general-purpose databases like MySQL or PostgreSQL, which are designed to meet the real-time performance and transactional needs of applications, a data warehouse is designed to collect and process the data produced by those applications, collectively and over time, to help you gain insight from it. Examples of data-warehouse products include Snowflake, Google BigQuery, Azure Synapse Analytics, and Amazon Redshift — all of which, incidentally, are easily managed with Pulumi.
- [Question] Which GCP tool should I use to build a Business decisional dashboard?
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Designing a Video Streaming Platform 📹
Google BigQuery
Apache Spark
- "xAI will open source Grok"
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Groovy 🎷 Cheat Sheet - 01 Say "Hello" from Groovy
Recently I had to revisit the "JVM languages universe" again. Yes, language(s), plural! Java isn't the only language that uses the JVM. I previously used Scala, which is a JVM language, to use Apache Spark for Data Engineering workloads, but this is for another post 😉.
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🦿🛴Smarcity garbage reporting automation w/ ollama
Consume data into third party software (then let Open Search or Apache Spark or Apache Pinot) for analysis/datascience, GIS systems (so you can put reports on a map) or any ticket management system
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Go concurrency simplified. Part 4: Post office as a data pipeline
also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc.
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Five Apache projects you probably didn't know about
Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features.
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Apache Spark VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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Integrate Pyspark Structured Streaming with confluent-kafka
Apache Spark - https://spark.apache.org/
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Spark – A micro framework for creating web applications in Kotlin and Java
A JVM based framework named "Spark", when https://spark.apache.org exists?
- Rest in Peas: The Unrecognized Death of Speech Recognition (2010)
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PySpark SparkSession Builder with Kubernetes Master
I recently saw a pull request that was merged to the Apache/Spark repository that apparently adds initial Python bindings for PySpark on K8s. I posted a comment to the PR asking a question about how to use spark-on-k8s in a Python Jupyter notebook, and was told to ask my question here.
What are some alternatives?
airbyte - The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.
Trino - Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
dbt-core - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
dagster - An orchestration platform for the development, production, and observation of data assets.
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
rudderstack-docs - Documentation repository for RudderStack - the Customer Data Platform for Developers.
Scalding - A Scala API for Cascading
dbt - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications. [Moved to: https://github.com/dbt-labs/dbt-core]
mrjob - Run MapReduce jobs on Hadoop or Amazon Web Services
streamlit - Streamlit — A faster way to build and share data apps.
luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.