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byte_array's profile picture. Founder @Onehousehq, Creator of @apachehudi, Built the World's first #DataLakehouse, Distributed/Data Systems, Linkedin, Uber, Confluent alum. (views are mine)

Vinoth Chandar

@byte_array

Founder @Onehousehq, Creator of @apachehudi, Built the World's first #DataLakehouse, Distributed/Data Systems, Linkedin, Uber, Confluent alum. (views are mine)

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Vinoth Chandar
@byte_array
May 20

🔥 Meet Quanton — the new query execution engine from Onehouse. 👍 Same Spark & SQL. 📉 At least half the cost. 📈 1.6x-3.6x better ETL price-performance 📊 2.2x-6.5x better Ingest price-performance 👉  Read the full blog here: onehouse.ai/blog/announcin… ⬇️  Download our free…

byte_array's tweet card. Meet Quanton! Our new query execution engine, that powers Spark and SQL jobs on top of the Onehouse Compute Runtime. Learn how it provides 2-3x better price-performance for your ETL data pipelines.
Announcing Apache Spark™ and SQL on the Onehouse Compute Runtime with Quanton
Source: onehouse.ai
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apachehudi's profile picture.
Apache Hudi
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14 h

🚀 Big news for Hudi Community! We're back with the Apache Hudi Meetup | ASIA (Chinese), and this time we're hosted by the incredible team at @JD_Corporate (京东) ! Get ready to explore the "Next-Generation Lakehouse: The Intelligent Future Engine". We have a packed agenda…

apachehudi's tweet image. 🚀 Big news for Hudi Community! We're back with the Apache Hudi Meetup | ASIA (Chinese), and this time we're hosted by the incredible team at @JD_Corporate (京东) ! Get ready to explore the "Next-Generation Lakehouse: The Intelligent Future Engine". We have a packed agenda…
apachehudi's tweet image. 🚀 Big news for Hudi Community! We're back with the Apache Hudi Meetup | ASIA (Chinese), and this time we're hosted by the incredible team at @JD_Corporate (京东) ! Get ready to explore the "Next-Generation Lakehouse: The Intelligent Future Engine". We have a packed agenda…
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Vinoth Chandar
@byte_array
Sep 29

💰🔥 Spark’s default autoscaler = higher latency scaling up, wasted $$ scaling down. Why? It’s based on task backlog, not actual resource usage. Costly flaw. Result: 🐢 Slow scale-ups (e.g. too few Kafka partitions during spikes) 🐢 Slow scale-downs (e.g. many tiny tasks →…

byte_array's tweet image. 💰🔥 Spark’s default autoscaler = higher latency scaling up, wasted $$ scaling down. Why? It’s based on task backlog, not actual resource usage. Costly flaw. Result: 🐢 Slow scale-ups (e.g. too few Kafka partitions during spikes) 🐢 Slow scale-downs (e.g. many tiny tasks →…
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Vinoth Chandar
@byte_array
Sep 26

📊 If you’re using Apache Spark on EMR (or anywhere really), you need better visibility into where your compute spend is going. At Onehouse, we kept seeing the same pattern across Hudi and non-Hudi users alike: 👉 Jobs were under-optimized 👉 Executors were sitting idle 👉…

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Vinoth Chandar
@byte_array
Sep 24

🗞️ OLD NEWS: but worth a shout-out. Keys are optional in Hudi ... One of Hudi’s core goals was to remove friction from building data lakes. That’s why — for a long time now — Hudi has quietly supported auto-generation of record keys. No need to think up a key field just to get…

byte_array's tweet image. 🗞️ OLD NEWS: but worth a shout-out. Keys are optional in Hudi ... One of Hudi’s core goals was to remove friction from building data lakes. That’s why — for a long time now — Hudi has quietly supported auto-generation of record keys. No need to think up a key field just to get…
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