RedisSearch Crash In 8.2.1: Segfault In RaxGenericInsert

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RedisSearch Crash in 8.2.1: Segfault in raxGenericInsert

Hey everyone! Today, we're diving deep into a tricky bug that's been causing some headaches for Redis users: a crash occurring in Redis 8.2.1 when used with the RedisSearch module. Specifically, the crash manifests as a segmentation fault (segfault) within the raxGenericInsert function. This can be a real pain, especially in production environments, so let's break down what's happening and how to address it.

Understanding the Issue: Redis and RedisSearch

First, let's quickly recap what Redis and RedisSearch are. Redis, at its core, is an in-memory data structure store, often used as a database, cache, and message broker. Its speed and versatility make it a popular choice for many applications. RedisSearch, on the other hand, is a powerful module that adds full-text search capabilities to Redis. This allows you to index and search your data directly within Redis, opening up a whole new world of possibilities.

When these two technologies work together, they can provide blazing-fast search performance. However, like any complex system, there's always a chance of encountering bugs or compatibility issues. And that's precisely what we're seeing with this raxGenericInsert segfault.

Key Symptoms and Log Excerpts

So, what does this crash actually look like? Here are some key indicators you might see in your logs:

  • A SIGSEGV signal (segmentation fault) indicating a memory access violation.

  • The crash occurring within the raxGenericInsert function, which is part of Redis's radix tree implementation. Radix trees are used for efficient storage and retrieval of data, particularly strings.

  • The stack trace will point to redis-server and show the crash originating from within the raxGenericInsert function. You'll likely see references to RedisSearch modules in the stack as well.

  • Log excerpts similar to the following:

    1:M 26 Oct 2025 07:45:51.549 # Redis 8.2.1 crashed by signal: 11, si_code: 1
1:M 26 Oct 2025 07:45:51.549 # Accessing address: (nil)
1:M 26 Oct 2025 07:45:51.549 # Crashed running the instruction at: 0x55b3f56a8817
------ STACK TRACE ------
EIP:
redis-server *:6379(raxGenericInsert+0xb7)[0x55b3f56a8817]
...
24 gc-0214 *
/usr/lib/libc.so.6(+0x3c050)[0x7f348e33e050]
redis-server *:6379(raxGenericInsert+0xb7)[0x55b3f56a8817]
redis-server *:6379(RM_GetServerInfo+0x1ec)[0x55b3f5690aec]
/opt/bitnami/redis/lib/redis/modules/redisearch.so(+0x36f55d)[0x7f348c85e55d]
...

The stack trace clearly indicates that the crash originates from within the raxGenericInsert function, which is a core Redis function for managing radix trees. The involvement of redisearch.so in the stack trace suggests that the RedisSearch module is triggering this crash.

Diving Deeper: What's raxGenericInsert?

To really understand what's going on, let's zoom in on raxGenericInsert. This function is a fundamental part of Redis's internal data structures. It's responsible for inserting data into a radix tree, also known as a prefix tree. Think of a radix tree like a highly optimized dictionary where keys are strings, and the tree structure is built based on the prefixes of those strings. This allows for very efficient prefix-based searches and lookups.

In the context of RedisSearch, radix trees are likely used to store and manage the indexes created for full-text searching. When you index documents or data using RedisSearch, it needs to organize that data in a way that allows for fast searching. Radix trees are a great fit for this purpose.

So, when raxGenericInsert crashes, it means there's a problem in how data is being inserted into this crucial index structure. This could be due to a variety of reasons, including:

  • A bug in RedisSearch itself that's causing it to pass invalid data to raxGenericInsert.
  • A concurrency issue where multiple threads are trying to modify the radix tree at the same time, leading to a race condition.
  • A memory corruption issue where the radix tree's memory becomes corrupted, causing raxGenericInsert to misbehave.
  • An incompatibility between RedisSearch and the specific version of Redis (8.2.1 in this case).

Observations and Environment Details

Let's analyze the observations and environment details to narrow down the cause:

  • The crash occurs in Redis core radix tree (rax) logic, called from RedisSearch module code: This strongly suggests an issue within RedisSearch's interaction with the core Redis data structures.
  • Repeated ForkGC - got timeout while reading from pipe (Success) messages prior to crash—appears related to RedisSearch index GC: These messages indicate potential issues with the RedisSearch's garbage collection process, which might be related to resource contention or deadlocks.
  • Heavy usage of FT.SEARCH and JSON commands (high call counts, high p99 latency): This suggests that the system is under heavy load and that the crash might be triggered by specific workloads involving complex searches and JSON operations. The high latency indicates potential performance bottlenecks that could exacerbate concurrency issues.
  • IO threads enabled (io-threads 4), both RedisSearch and ReJSON loaded: IO threads can improve performance but also introduce additional complexity, especially when modules like RedisSearch and ReJSON are involved. These modules might have interactions that are not fully optimized for the IO thread model, leading to unexpected behavior.
  • No OOM or maxmemory reached; RSS and fragmentation normal: This eliminates memory exhaustion as a likely cause, suggesting that the issue is more related to logical errors or concurrency issues rather than physical memory limitations.

Environment

The environment details provide crucial context for understanding the crash:

  • Redis: 8.2.1 (Bitnami container)
  • RedisSearch: 8.2.1 (as per module info)
  • ReJSON: 8.2.0
  • Vectorset: 1
  • OS: Linux 5.14.0-427.85.1.el9_4.x86_64 x86_64
  • Memory: ~3GB used, 31GB total
  • Workload: High concurrency, heavy FT.SEARCH and JSON.GET/SET, pubsub activity

The combination of Redis 8.2.1, RedisSearch 8.2.1, and ReJSON 8.2.0, along with the high-concurrency workload and use of IO threads, might be a key factor in triggering this issue. The Bitnami container setup is also worth noting, as it provides a specific environment that could interact with the bug in unique ways.

Steps to Reproduce

Having clear steps to reproduce the issue is invaluable for debugging. The provided steps are:

  1. Run Redis 8.2.1 with RedisSearch 8.2.1 & ReJSON 8.2.0 modules loaded (Bitnami container)
  2. Enable IO threads (io-threads 4)
  3. Heavy usage of FT.SEARCH and JSON commands
  4. Observe repeated ForkGC timeouts, then eventual segfault

These steps outline a scenario where the system is under heavy load with specific RedisSearch and JSON operations. The observation of ForkGC timeouts before the segfault is a critical clue, suggesting that garbage collection processes in RedisSearch might be involved in the crash.

Potential Causes and Solutions

Okay, so we've got a good handle on the symptoms and the environment. Now, let's brainstorm some potential causes and, more importantly, how to fix them!

1. Bug in RedisSearch or Incompatibility

This is a strong possibility, especially given that the crash originates within RedisSearch's interaction with raxGenericInsert. There might be a bug in how RedisSearch is handling memory or data structures, or there could be an incompatibility between RedisSearch 8.2.1 and Redis 8.2.1.

Solution:

  • Check for known issues: The first step is to scour the RedisSearch issue tracker and forums for similar reports. There's a good chance someone else has encountered this and there might be a known fix or workaround.
  • Try a different version: If possible, try downgrading or upgrading RedisSearch to a different version. Sometimes, a bug is specific to a particular version, and switching versions can resolve the issue. Check the compatibility matrix for Redis and RedisSearch versions.
  • Contact RedisSearch maintainers: If you can't find a solution, reach out to the RedisSearch maintainers directly. They might be able to provide insights or suggest debugging steps.

2. Concurrency Issues

Given the high-concurrency workload and the use of IO threads, concurrency issues are definitely a suspect. It's possible that multiple threads are trying to modify the radix tree simultaneously, leading to a race condition and the segfault.

Solution:

  • Review RedisSearch concurrency handling: Investigate how RedisSearch handles concurrency internally. Are there any known limitations or best practices for using it in a multi-threaded environment?
  • Experiment with IO threads: Try disabling IO threads (io-threads 0) to see if it resolves the issue. While this might impact performance, it can help rule out concurrency as the root cause. You could also try reducing the number of IO threads to see if that mitigates the problem.
  • Implement locking or synchronization: If you suspect a race condition, you might need to implement additional locking or synchronization mechanisms within your application or within RedisSearch itself (if you're able to modify the module). However, this is a complex solution that should be approached with caution.

3. Memory Corruption

Although the fast memory test passed, memory corruption can still be a sneaky culprit. It's possible that memory is being corrupted in a way that the memory test doesn't detect, or that the corruption is happening in a specific region of memory used by the radix tree.

Solution:

  • Enable core dumps: Core dumps are snapshots of the process's memory at the time of the crash. They can be invaluable for debugging memory corruption issues. Configure your system to generate core dumps when Redis crashes.
  • Use a memory debugger: Tools like Valgrind can help detect memory errors such as invalid reads/writes, memory leaks, and use of uninitialized memory. Running Redis under Valgrind can be resource-intensive but can provide valuable insights.
  • Review RedisSearch memory management: Examine how RedisSearch allocates and deallocates memory. Are there any potential memory leaks or double-frees that could be corrupting memory?

4. RedisSearch Garbage Collection

The repeated ForkGC timeouts are a significant clue. Garbage collection (GC) is the process of reclaiming memory that is no longer being used. If the GC process in RedisSearch is timing out, it could indicate a problem with how it's managing memory or that it's getting stuck in some way.

Solution:

  • Investigate GC settings: Check the RedisSearch documentation for any configuration options related to garbage collection. There might be settings that you can adjust to improve GC performance or prevent timeouts.
  • Monitor GC activity: Use Redis monitoring tools to track GC activity. Look for patterns or spikes in GC activity that might correlate with the crashes.
  • Consider a different GC strategy: If RedisSearch offers different GC strategies, try experimenting with them to see if one performs better in your environment.

Steps to Take Now

Okay, guys, so what should you do right now if you're facing this issue? Here's a practical checklist:

  1. Check the RedisSearch issue tracker: Seriously, this is the first place to look. There's a good chance someone else has already reported the issue, and there might be a known workaround or fix.
  2. Try downgrading or upgrading: If possible, try switching to a different version of RedisSearch. This can often resolve compatibility issues.
  3. Disable IO threads: As a temporary measure, try disabling IO threads to see if it stabilizes the system. Remember to monitor performance if you do this.
  4. Enable core dumps: Configure your system to generate core dumps so you can analyze the crash in more detail if it happens again.
  5. Contact RedisSearch maintainers: If you're still stuck, reach out to the RedisSearch maintainers. They're the experts and can provide valuable guidance.

Additional Diagnostics

If you're reporting this issue, here's some extra information that will be super helpful:

  • Full crash log: Include the entire crash log, from START to END. This provides the full context of the crash.
  • Redis configuration: Share your Redis configuration file (redis.conf).
  • RedisSearch module configuration: If you have any specific configurations for RedisSearch, include those as well.
  • Workload details: Describe your workload in detail. What commands are you running? What's the data volume? What's the concurrency level?
  • Core dump: If you have a core dump, make it available (but be mindful of security and privacy!).

Recommendation and Next Steps

Based on the analysis, this issue appears to be a bug in the RedisSearch module or a module/core compatibility issue. I recommend the following steps:

  1. Check for known issues in the RedisSearch issue tracker and forums.
  2. Attempt a safe upgrade or downgrade path for RedisSearch, if possible, while checking version compatibility.
  3. Provide a core dump if requested by the RedisSearch maintainers for further debugging.

Let's keep digging, guys! This is a tricky one, but by working together and sharing information, we can hopefully get to the bottom of it and prevent these crashes from happening in the future. If you've experienced this issue or have any insights, please share them in the comments below. Let's help each other out!

Remember, debugging is a process of elimination. By systematically investigating potential causes and trying different solutions, we can narrow down the problem and find a fix.

Stay tuned for more updates as we learn more about this issue!