Skip to main content

Automating HBase Major Compactions with Cron and Kerberos

Major compactions in HBase can be scheduled during low-traffic hours to reduce load on RegionServers. This guide shows how to trigger a compaction from the HBase shell using a simple Ruby script and how to wrap it in a Kerberos-aware cron job. It reflects common operational practice in legacy Hadoop clusters where maintenance windows still matter.

Why Schedule Major Compactions?

Major compactions rewrite all store files of an HBase table, improving read performance but putting additional pressure on the cluster. Many administrators run them during off-peak windows. HBase itself does not provide built-in scheduling, so automation is typically handled with cron or at.

Ruby Script for HBase Shell

HBase shell executes commands through JRuby, so a simple script triggers the compaction:

# m_compact.rb
major_compact 't1'
exit

Cron-Compatible Shell Wrapper

Below is an example daily_compact script that refreshes a Kerberos ticket and runs the compaction via the HBase shell. Adapt table names, realms and keytabs to your environment.

#!/bin/bash

USER=hbase
PWD=$(echo ~$USER)
TABLE=t1

# Kerberos settings
KEYTAB=/etc/hbase/conf/hbase.keytab
HOST=$(hostname)
REALM=ALO.ALT

LOG=/var/log/daily_compact

# Acquire Kerberos ticket
sudo -u $USER kinit -k -t $KEYTAB $USER/$HOST@$REALM

# Trigger major compaction
sudo -u $USER hbase shell $PWD/m_compact.rb 2>&1 | tee -a $LOG

Log Output

All messages are appended to /var/log/daily_compact. Example output may look like:

WARN conf.Configuration: hadoop.native.lib is deprecated
12 row(s) in 0.7800 seconds

Operational Notes (Modern Context)

  • Major compactions increase disk and network load; avoid running on overloaded RegionServers.
  • Consider minor compactions and compaction policies before scheduling forced majors.
  • In cloud migrations or HBase-on-EMR clusters, perform compactions during autoscaling-stable hours.
  • Always verify ticket renewal for Kerberos environments as shared keytabs often expire silently.

If you need help with distributed systems, backend engineering, or data platforms, check my Services.

Most read articles

Why Is Customer Obsession Disappearing?

Many companies trade real customer-obsession for automated, low-empathy support. Through examples from Coinbase, PayPal, GO Telecommunications and AT&T, this article shows how reliance on AI chatbots, outsourced call centers, and KPI-driven workflows erodes trust, NPS and customer retention. It argues that human-centric support—treating support as strategic investment instead of cost—is still a core growth engine in competitive markets. It's wild that even with all the cool tech we've got these days, like AI solving complex equations and doing business across time zones in a flash, so many companies are still struggling with the basics: taking care of their customers. The drama around Coinbase's customer support is a prime example of even tech giants messing up. And it's not just Coinbase — it's a big-picture issue for the whole industry. At some point, the idea of "customer obsession" got replaced with "customer automation," and no...

What the Heck is Superposition and Entanglement?

This post is about superposition and interference in simple, intuitive terms. It describes how quantum states combine, how probability amplitudes add, and why interference patterns appear in systems such as electrons, photons and waves. The goal is to give a clear, non mathematical understanding of how quantum behavior emerges from the rules of wave functions and measurement. If you’ve ever heard the words superposition or entanglement thrown around in conversations about quantum physics, you may have nodded politely while your brain quietly filed them away in the "too confusing to deal with" folder.  These aren't just theoretical quirks; they're the foundation of mind-bending tech like Google's latest quantum chip, the Willow with its 105 qubits. Superposition challenges our understanding of reality, suggesting that particles don't have definite states until observed. This principle is crucial in quantum technologies, enabling phenomena like quantum comp...

SynthLink Compared to Google’s Natural Questions: A Practical Evaluation

SynthLink evaluates reasoning, synthesis and internal consistency across diverse question types. Google’s Natural Questions evaluates extractive QA: finding short text spans inside structured documents. Because real workloads require interpretation, abstraction and multi-step logic, SynthLink exposes capabilities and failure modes that NQ cannot measure. The two benchmarks are complementary, but SynthLink is more aligned with production tasks. Benchmarks such as Google’s Natural Questions (NQ) dominate model evaluation. They provide a reliable, academically stable test for extractive question answering: short queries, grounded answers, and constrained context ranges. But real workloads rarely look like NQ. Production systems must handle ambiguous inputs, multi-step reasoning, poorly structured prompts, and cases where no canonical answer exists. SynthLink was designed for this broader landscape. It focuses on evaluating reasoning, synthesis and internal consistency rather than snippe...