Apache Kudu Troubleshooting

Startup Errors

Errors During Hole Punching Test

Kudu requires hole punching capabilities in order to be efficient. Hole punching support depends upon your operation system kernel version and local filesystem implementation.

  • RHEL or CentOS 6.4 or later, patched to kernel version of 2.6.32-358 or later. Unpatched RHEL or CentOS 6.4 does not include a kernel with support for hole punching.

  • Ubuntu 14.04 includes version 3.13 of the Linux kernel, which supports hole punching.

  • Newer versions of the EXT4 or XFS file systems support hole punching, but EXT3 does not. Older versions of XFS that do not support hole punching return a EOPNOTSUPP (operation not supported) error. Older versions of either EXT4 or XFS that do not support hole punching cause Kudu to emit an error message such as the following and to fail to start:

    Error during hole punch test. The log block manager requires a
    filesystem with hole punching support such as ext4 or xfs. On el6,
    kernel version 2.6.32-358 or newer is required. To run without hole
    punching (at the cost of some efficiency and scalability), reconfigure
    Kudu with --block_manager=file. Refer to the Kudu documentation for more
    details. Raw error message follows.

Without hole punching support, the log block manager is unsafe to use. It won’t ever delete blocks, and will consume ever more space on disk.

If you can’t use hole punching in your environment, you can still try Kudu. Enable the file block manager instead of the log block manager by adding the --block_manager=file flag to the commands you use to start the master and tablet servers. The file block manager does not scale as well as the log block manager.

The file block manager is known to scale and perform poorly, and should only be used for small-scale evaluation and development.

NTP Clock Synchronization

For the master and tablet server daemons, the server’s clock must be synchronized using NTP. In addition, the maximum clock error (not to be mistaken with the estimated error) be below a configurable threshold. The default value is 10 seconds, but it can be set with the flag --max_clock_sync_error_usec.

If NTP is not installed, or if the clock is reported as unsynchronized, Kudu will not start, and will emit a message such as:

F0924 20:24:36.336809 14550 hybrid_clock.cc:191 Couldn't get the current time: Clock unsynchronized. Status: Service unavailable: Error reading clock. Clock considered unsynchronized.

If NTP is installed and synchronized, but the maximum clock error is too high, the user will see a message such as:

Sep 17, 8:13:09.873 PM FATAL hybrid_clock.cc:196 Couldn't get the current time: Clock synchronized, but error: 11130000, is past the maximum allowable error: 10000000


Sep 17, 8:32:31.135 PM FATAL tablet_server_main.cc:38 Check failed: _s.ok() Bad status: Service unavailable: Cannot initialize clock: Cannot initialize HybridClock. Clock synchronized but error was too high (11711000 us).
If NTP is installed the user can monitor the synchronization status by running ntptime. The relevant value is what is reported for maximum error.

To install NTP, use the appropriate command for your operating system:

OS Command


sudo apt-get install ntp


sudo yum install ntp

If NTP is installed but not running, start it using one of these commands:

OS Command


sudo service ntp restart


sudo /etc/init.d/ntpd restart

NTP requires a network connection and may take a few minutes to synchronize the clock. In some cases a spotty network connection may make NTP report the clock as unsynchronized. A common, though temporary, workaround for this is to restart NTP with one of the commands above.

If the clock is being reported as synchronized by NTP, but the maximum error is too high, the user can increase the threshold to a higher value by setting the above mentioned flag. For example to increase the possible maximum error to 20 seconds the flag should be set like: --max_clock_sync_error_usec=20000000

Reporting Kudu Crashes

Kudu uses the Google Breakpad library to generate a minidump whenever Kudu experiences a crash. These minidumps are typically only a few MB in size and are generated even if core dump generation is disabled. At this time, generating minidumps is only possible in Kudu on Linux builds.

A minidump file contains important debugging information about the process that crashed, including shared libraries loaded and their versions, a list of threads running at the time of the crash, the state of the processor registers and a copy of the stack memory for each thread, and CPU and operating system version information.

It is also possible to force Kudu to create a minidump without killing the process by sending a USR1 signal to the kudu-tserver or kudu-master process. For example:

sudo pkill -USR1 kudu-tserver

By default, Kudu stores its minidumps in a subdirectory of its configured glog directory called minidumps. This location can be customized by setting the --minidump_path flag. Kudu will retain only a certain number of minidumps before deleting the oldest ones, in an effort to avoid filling up the disk with minidump files. The maximum number of minidumps that will be retained can be controlled by setting the --max_minidumps gflag.

Minidumps contain information specific to the binary that created them and so are not usable without access to the exact binary that crashed, or a very similar binary.

A minidump can be emailed to a Kudu developer or attached to a JIRA in order to help a Kudu developer debug a crash. In order for it to be useful, the developer will need to know the exact version of Kudu and the operating system where the crash was observed. Note that while a minidump does not contain a heap memory dump, it does contain stack memory and therefore it is possible for application data to appear in a minidump. If confidential or personal information is stored on the cluster, do not share minidump files.

Performance Troubleshooting

Kudu Tracing

The kudu-master and kudu-tserver daemons include built-in tracing support based on the open source Chromium Tracing framework. You can use tracing to help diagnose latency issues or other problems on Kudu servers.

Accessing the tracing interface

The tracing interface is accessed via a web browser as part of the embedded web server in each of the Kudu daemons.

Table 1. Tracing Interface URLs
Daemon URL

Tablet Server




The tracing interface is known to work in recent versions of Google Chrome. Other browsers may not work as expected.

Collecting a trace

After navigating to the tracing interface, click the Record button on the top left corner of the screen. When beginning to diagnose a problem, start by selecting all categories. Click Record to begin recording a trace.

During the trace collection, events are collected into an in-memory ring buffer. This ring buffer is fixed in size, so it will eventually fill up to 100%. However, new events are still being collected while older events are being removed. While recording the trace, trigger the behavior or workload you are interested in exploring.

After collecting for several seconds, click Stop. The collected trace will be downloaded and displayed. Use the ? key to display help text about using the tracing interface to explore the trace.

Saving a trace

You can save collected traces as JSON files for later analysis by clicking Save after collecting the trace. To load and analyze a saved JSON file, click Load and choose the file.

RPC Timeout Traces

If client applications are experiencing RPC timeouts, the Kudu tablet server WARNING level logs should contain a log entry which includes an RPC-level trace. For example:

W0922 00:56:52.313848 10858 inbound_call.cc:193] Call kudu.consensus.ConsensusService.UpdateConsensus
from (request call id 3555909) took 1464ms (client timeout 1000).
W0922 00:56:52.314888 10858 inbound_call.cc:197] Trace:
0922 00:56:50.849505 (+     0us) service_pool.cc:97] Inserting onto call queue
0922 00:56:50.849527 (+    22us) service_pool.cc:158] Handling call
0922 00:56:50.849574 (+    47us) raft_consensus.cc:1008] Updating replica for 2 ops
0922 00:56:50.849628 (+    54us) raft_consensus.cc:1050] Early marking committed up to term: 8 index: 880241
0922 00:56:50.849968 (+   340us) raft_consensus.cc:1056] Triggering prepare for 2 ops
0922 00:56:50.850119 (+   151us) log.cc:420] Serialized 1555 byte log entry
0922 00:56:50.850213 (+    94us) raft_consensus.cc:1131] Marking committed up to term: 8 index: 880241
0922 00:56:50.850218 (+     5us) raft_consensus.cc:1148] Updating last received op as term: 8 index: 880243
0922 00:56:50.850219 (+     1us) raft_consensus.cc:1195] Filling consensus response to leader.
0922 00:56:50.850221 (+     2us) raft_consensus.cc:1169] Waiting on the replicates to finish logging
0922 00:56:52.313763 (+1463542us) raft_consensus.cc:1182] finished
0922 00:56:52.313764 (+     1us) raft_consensus.cc:1190] UpdateReplicas() finished
0922 00:56:52.313788 (+    24us) inbound_call.cc:114] Queueing success response

These traces can give an indication of which part of the request was slow. Please include them in bug reports related to RPC latency outliers.

Kernel Stack Watchdog Traces

Each Kudu server process has a background thread called the Stack Watchdog, which monitors the other threads in the server in case they have blocked for longer-than-expected periods of time. These traces can indicate operating system issues or bottlenecked storage.

When the watchdog thread identifies a case of thread blockage, it logs an entry in the WARNING log like the following:

W0921 23:51:54.306350 10912 kernel_stack_watchdog.cc:111] Thread 10937 stuck at /data/kudu/consensus/log.cc:505 for 537ms:
Kernel stack:
[<ffffffffa00b209d>] do_get_write_access+0x29d/0x520 [jbd2]
[<ffffffffa00b2471>] jbd2_journal_get_write_access+0x31/0x50 [jbd2]
[<ffffffffa00fe6d8>] __ext4_journal_get_write_access+0x38/0x80 [ext4]
[<ffffffffa00d9b23>] ext4_reserve_inode_write+0x73/0xa0 [ext4]
[<ffffffffa00d9b9c>] ext4_mark_inode_dirty+0x4c/0x1d0 [ext4]
[<ffffffffa00d9e90>] ext4_dirty_inode+0x40/0x60 [ext4]
[<ffffffff811ac48b>] __mark_inode_dirty+0x3b/0x160
[<ffffffff8119c742>] file_update_time+0xf2/0x170
[<ffffffff8111c1e0>] __generic_file_aio_write+0x230/0x490
[<ffffffff8111c4c8>] generic_file_aio_write+0x88/0x100
[<ffffffffa00d3fb1>] ext4_file_write+0x61/0x1e0 [ext4]
[<ffffffff81180f5b>] do_sync_readv_writev+0xfb/0x140
[<ffffffff81181ee6>] do_readv_writev+0xd6/0x1f0
[<ffffffff81182046>] vfs_writev+0x46/0x60
[<ffffffff81182102>] sys_pwritev+0xa2/0xc0
[<ffffffff8100b072>] system_call_fastpath+0x16/0x1b
[<ffffffffffffffff>] 0xffffffffffffffff

User stack:
    @       0x3a1ace10c4  (unknown)
    @          0x1262103  (unknown)
    @          0x12622d4  (unknown)
    @          0x12603df  (unknown)
    @           0x8e7bfb  (unknown)
    @           0x8f478b  (unknown)
    @           0x8f55db  (unknown)
    @          0x12a7b6f  (unknown)
    @       0x3a1b007851  (unknown)
    @       0x3a1ace894d  (unknown)
    @              (nil)  (unknown)

These traces can be useful for diagnosing root-cause latency issues when they are caused by systems below Kudu, such as disk controllers or file systems.

Issues using Kudu

ClassNotFoundException: com.cloudera.kudu.hive.KuduStorageHandler

Users will encounter this exception when trying to use a Kudu table via Hive. This is not a case of a missing jar, but simply that Impala stores Kudu metadata in Hive in a format that’s unreadable to other tools, including Hive itself and Spark. There is no workaround for Hive users. Spark users need to create temporary tables.