Remove introducing-support-lateral-column-alias
article thumbnail

Introducing the Support of Lateral Column Alias

databricks

We are thrilled to introduce the support of a new SQL feature in Apache Spark and Databricks: Lateral Column Alias (LCA). This feature.

SQL 109
article thumbnail

Updates, Inserts, Deletes: Comparing Elasticsearch and Rockset for Real-Time Data Ingest

Rockset

In this blog, we’ll compare and contrast how Elasticsearch and Rockset handle data ingestion as well as provide practical techniques for using these systems for real-time analytics. If dynamic typing is used as the index type, then Elasticsearch does support some schema changes such as adding fields, removing fields and changing types.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Demystifying event streams: Transforming events into tables with dbt

dbt Developer Hub

In this blog post we’ll dive into how we tackled one source of quality issues: directly relying on upstream database schemas. Modern ETL tools like Fivetran and Stitch can flexibly handle schema changes - for example, if a new column is created they can propagate that creation to Snowflake. Each column is a variant type in Snowflake.

Kafka 52
article thumbnail

Using MongoDB Change Streams for Indexing with Elasticsearch vs Rockset

Rockset

Rockset Patch API Rockset recently introduced a Patch API method, which enables users to stream complex CDC changes to Rockset with low-latency inserts and updates that trigger incremental indexing, rather than a complete reindexing of the document. In this blog, I’ll discuss the benefits of Patch API and how Rockset makes it easy to use.

MongoDB 40
article thumbnail

Using Metrics Layer to Standardize and Scale Experimentation at DoorDash

DoorDash Engineering

Building a metrics layer that works for experimentation is not simple, as it should support different types of metrics of varying scale that are used across the diverse range of A/B tests that are being run across different products. It exposes a set of columns as measures or dimensions.

SQL 82