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 and xfs filesystems support hole punching. Older versions that do not support hole punching will 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.
|
Note
|
ext4 mountpoints may actually be backed by ext2 or ext3 formatted devices, which do not support hole punching. The hole punching test will fail when run on such filesystems. There are several different ways to determine whether an ext4 mountpoint is backed by an ext2, ext3, or ext4 formatted device; see this Stack Exchange post for details. |
Changing Directory Configurations documentation.
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.
|
Warning
|
The file block manager is known to scale and perform poorly, and should only be used for small-scale evaluation and development. |
When Kudu starts, it checks each configured data directory, expecting either for all to be initialized or for all to be empty. If a server fails to start with a log message like
Check failed: _s.ok() Bad status: Already present: FS layout already exists; not overwriting existing layout: FSManager roots already exist: /data0/kudu/data
then this precondition has failed. This could be because Kudu was configured with non-empty data directories on first startup, or because a previously-running, healthy Kudu process was restarted and at least one data directory was deleted or is somehow corrupted, perhaps because of a disk error. If in the latter situation, consult the Changing Directory Configurations documentation.
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
or
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).
To install NTP, use the appropriate command for your operating system:
| OS | Command |
|---|---|
Debian/Ubuntu |
|
RHEL/CentOS |
|
If NTP is installed but not running, start it using one of these commands:
| OS | Command |
|---|---|
Debian/Ubuntu |
|
RHEL/CentOS |
|
When NTP is installed, you can monitor the synchronization status by running
ntptime. For example, a healthy system may report:
ntp_gettime() returns code 0 (OK) time de24c0cf.8d5da274 Tue, Feb 6 2018 16:03:27.552, (.552210980), maximum error 224455 us, estimated error 383 us, TAI offset 0 ntp_adjtime() returns code 0 (OK) modes 0x0 (), offset 1279.543 us, frequency 2.500 ppm, interval 1 s, maximum error 224455 us, estimated error 383 us, status 0x2001 (PLL,NANO), time constant 10, precision 0.001 us, tolerance 500 ppm,
In particular, note the following most important pieces of output:
-
maximum error 22455 us: this value is well under the 10-second maximum error required by Kudu. -
status 0x2001 (PLL,NANO): this indicates a healthy synchronization status.
In contrast, a system without NTP properly configured and running will output something like the following:
ntp_gettime() returns code 5 (ERROR) time de24c240.0c006000 Tue, Feb 6 2018 16:09:36.046, (.046881), maximum error 16000000 us, estimated error 16000000 us, TAI offset 0 ntp_adjtime() returns code 5 (ERROR) modes 0x0 (), offset 0.000 us, frequency 2.500 ppm, interval 1 s, maximum error 16000000 us, estimated error 16000000 us, status 0x40 (UNSYNC), time constant 10, precision 1.000 us, tolerance 500 ppm,
Note the UNSYNC status and the 16-second maximum error.
If more detailed information is needed, the ntpq or ntpdc tools
can be used to dump further information about which network time servers
are currently acting as sources:
$ ntpq -nc lpeers
remote refid st t when poll reach delay offset jitter
==============================================================================
-108.59.2.24 130.133.1.10 2 u 13 64 1 71.743 0.373 0.016
+192.96.202.120 129.6.15.28 2 u 12 64 1 72.583 -0.426 0.028
-69.10.161.7 204.26.59.157 3 u 11 64 1 15.741 2.641 0.021
-173.255.206.154 45.56.123.24 3 u 10 64 1 43.502 0.199 0.029
-69.195.159.158 128.138.140.44 2 u 9 64 1 53.885 -0.016 0.013
*216.218.254.202 .CDMA. 1 u 6 64 1 1.475 -0.400 0.012
+129.250.35.250 249.224.99.213 2 u 7 64 1 1.342 -0.640 0.018
45.76.244.193 216.239.35.4 2 u 6 64 1 17.380 -0.754 0.051
69.89.207.199 212.215.1.157 2 u 5 64 1 57.796 -3.411 0.059
171.66.97.126 .GPSs. 1 u 4 64 1 1.024 -0.374 0.018
66.228.42.59 211.172.242.174 3 u 3 64 1 72.409 0.895 0.964
91.189.89.198 17.253.34.125 2 u 2 64 1 135.195 -0.329 0.171
162.210.111.4 216.218.254.202 2 u 1 64 1 28.570 0.693 0.306
199.102.46.80 .GPS. 1 u 2 64 1 55.652 -0.039 0.019
91.189.89.199 17.253.34.125 2 u 1 64 1 135.265 -0.413 0.037
$ ntpq -nc opeers
remote local st t when poll reach delay offset disp
==============================================================================
-108.59.2.24 10.17.100.238 2 u 17 64 1 71.743 0.373 187.573
+192.96.202.120 10.17.100.238 2 u 16 64 1 72.583 -0.426 187.594
-69.10.161.7 10.17.100.238 3 u 15 64 1 15.741 2.641 187.569
-173.255.206.154 10.17.100.238 3 u 14 64 1 43.502 0.199 187.580
-69.195.159.158 10.17.100.238 2 u 13 64 1 53.885 -0.016 187.561
*216.218.254.202 10.17.100.238 1 u 10 64 1 1.475 -0.400 187.543
+129.250.35.250 10.17.100.238 2 u 11 64 1 1.342 -0.640 187.588
45.76.244.193 10.17.100.238 2 u 10 64 1 17.380 -0.754 187.596
69.89.207.199 10.17.100.238 2 u 9 64 1 57.796 -3.411 187.541
171.66.97.126 10.17.100.238 1 u 8 64 1 1.024 -0.374 187.578
66.228.42.59 10.17.100.238 3 u 7 64 1 72.409 0.895 187.589
91.189.89.198 10.17.100.238 2 u 6 64 1 135.195 -0.329 187.584
162.210.111.4 10.17.100.238 2 u 5 64 1 28.570 0.693 187.606
199.102.46.80 10.17.100.238 1 u 4 64 1 55.652 -0.039 187.587
91.189.89.199 10.17.100.238 2 u 3 64 1 135.265 -0.413 187.621
|
Tip
|
Both opeers and lpeers may be helpful as lpeers lists refid and
jitter, while lpeers lists dispersion.
|
chrony for time synchronizationSome operating systems offer chrony as an alternative to ntpd for network time
synchronization. Kudu has been tested most thoroughly using ntpd and use of
chrony is considered experimental.
In order to use chrony for synchronization, chrony.conf must be configured
with the rtcsync option.
In order to provide stable time synchronization with low maximum error, follow these best NTP configuration best practices.
Always configure at least four time sources for NTP. In addition to providing redundancy in case one or more time sources becomes unavailable, The NTP protocol is designed to increase its accuracy with a diversity of sources. Even if your organization provides one or more local time servers, configuring additional remote servers is highly recommended for a robust setup.
Pick servers in your server’s local geography. For example, if your servers are located in Europe, pick servers from the European NTP pool. If your servers are running in a public cloud environment, consult the cloud provider’s documentation for a recommended NTP setup. Many cloud providers offer highly accurate clock synchronization as a service.
Use the iburst option for faster synchronization at startup. The iburst option
instructs ntpd to send an initial "burst" of time queries at startup. This typically
results in a faster time synchronization when a machine restarts.
An example NTP server list may appear as follows:
# Use my organization's internal NTP servers. server ntp1.myorg.internal iburst server ntp2.myorg.internal iburst # Provide several public pool servers for # redundancy and robustness. server 0.pool.ntp.org iburst server 1.pool.ntp.org iburst server 2.pool.ntp.org iburst server 3.pool.ntp.org iburst
|
Tip
|
After configuring NTP, use the ntpq tool described above to verify that ntpd was
able to connect to a variety of peers. If no public peers appear, it is possiblbe that
the NTP protocol is being blocked by a firewall or other network connectivity issue.
|
As of Kudu 1.6.0, Kudu daemons are able to continue to operate during a brief loss of
NTP synchronization. If NTP synchronization is lost for several hours, however, daemons
may crash. If a daemon crashes due to NTP synchronization issues, consult the ERROR log
for a dump of related information which may help to diagnose the issue.
|
Tip
|
Kudu 1.5.0 and earlier versions were less resilient to brief NTP outages. In addition, they contained a bug which could cause Kudu to incorrectly measure the maximum error, resulting in crashes. If you experience crashes related to clock synchronization on these earlier versions of Kudu and it appears that the system’s NTP configuration is correct, consider upgrading to Kudu 1.6.0 or later. |
|
Tip
|
NTP requires a network connection and may take a few minutes to synchronize the clock at startup. 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. |
When using the log block manager (the default on Linux), Kudu uses
sparse files to store data. A
sparse file has a different apparent size than the actual amount of disk space
it uses. This means that some tools may inaccurately report the disk space
used by Kudu. For example, the size listed by ls -l does not accurately
reflect the disk space used by Kudu data files:
$ ls -lh /data/kudu/tserver/data
total 117M
-rw------- 1 kudu kudu 160M Mar 26 19:37 0b9807b8b17d48a6a7d5b16bf4ac4e6d.data
-rw------- 1 kudu kudu 4.4K Mar 26 19:37 0b9807b8b17d48a6a7d5b16bf4ac4e6d.metadata
-rw------- 1 kudu kudu 32M Mar 26 19:37 2f26eeacc7e04b65a009e2c9a2a8bd20.data
-rw------- 1 kudu kudu 4.3K Mar 26 19:37 2f26eeacc7e04b65a009e2c9a2a8bd20.metadata
-rw------- 1 kudu kudu 672M Mar 26 19:37 30a2dd2cd3554d8a9613f588a8d136ff.data
-rw------- 1 kudu kudu 4.4K Mar 26 19:37 30a2dd2cd3554d8a9613f588a8d136ff.metadata
-rw------- 1 kudu kudu 32M Mar 26 19:37 7434c83c5ec74ae6af5974e4909cbf82.data
-rw------- 1 kudu kudu 4.3K Mar 26 19:37 7434c83c5ec74ae6af5974e4909cbf82.metadata
-rw------- 1 kudu kudu 672M Mar 26 19:37 772d070347a04f9f8ad2ad3241440090.data
-rw------- 1 kudu kudu 4.4K Mar 26 19:37 772d070347a04f9f8ad2ad3241440090.metadata
-rw------- 1 kudu kudu 160M Mar 26 19:37 86e50a95531f46b6a79e671e6f5f4151.data
-rw------- 1 kudu kudu 4.4K Mar 26 19:37 86e50a95531f46b6a79e671e6f5f4151.metadata
-rw------- 1 kudu kudu 687 Mar 26 19:26 block_manager_instanceNotice that the total size reported is 117MiB, while the first file’s size is
listed as 160MiB. Adding the -s option to ls will cause ls to output the
file’s disk space usage.
The du and df utilities report the actual disk space usage by default.
$ du -h /data/kudu/tserver/data
118M /data/kudu/tserver/dataThe apparent size can be shown with the --apparent-size flag to du.
$ du -h --apparent-size /data/kudu/tserver/data
1.7G /data/kudu/tserver/dataKudu 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-tserverBy 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. For more information on processing and using minidump files, see scripts/dump_breakpad_symbols.py.
|
Note
|
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. |
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.
The tracing interface is accessed via a web browser as part of the embedded web server in each of the Kudu daemons.
| Daemon | URL |
|---|---|
Tablet Server |
|
Master |
|
Warning
|
The tracing interface is known to work in recent versions of Google Chrome. Other browsers may not work as expected. |
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.
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.
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 192.168.1.102:43499 (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.
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 filesystems.
Kudu has a hard and soft memory limit. The hard memory limit is the maximum amount a Kudu process
is allowed to use, and is controlled by the --memory_limit_hard_bytes flag. The soft memory limit
is a percentage of the hard memory limit, controlled by the flag memory_limit_soft_percentage and
with a default value of 80%, that determines the amount of memory a process may use before it will
start rejecting some write operations.
If the logs or RPC traces contain messages like
Service unavailable: Soft memory limit exceeded (at 96.35% of capacity)
then Kudu is rejecting writes due to memory backpressure. This may result in write timeouts. There are several ways to relieve the memory pressure on Kudu:
-
If the host has more memory available for Kudu, increase
--memory_limit_hard_bytes. -
Increase the rate at which Kudu can flush writes from memory to disk by increasing the number of disks or increasing the number of maintenance manager threads
--maintenance_manager_num_threads. Generally, the recommended ratio of maintenance manager threads to data directories is 1:3. -
Reduce the volume of writes flowing to Kudu on the application side.
For advanced debugging of memory usage, administrators may enable heap sampling on Kudu daemons. This allows Kudu developers to associate memory usage with the specific lines of code and data structures responsible. When reporting a bug related to memory usage or an apparent memory leak, heap profiling can give quantitative data to pinpoint the issue.
|
Warning
|
Heap sampling is an advanced troubleshooting technique and may cause performance degradation or instability of the Kudu service. Currently it is not recommended to enable this in a production environment unless specifically requested by the Kudu development team. |
To enable heap sampling on a Kudu daemon, pass the flag --heap-sample-every-n-bytes=524588.
If heap sampling is enabled, the current sampled heap occupancy can be retrieved over HTTP
by visiting http://tablet-server.example.com:8050/pprof/heap or
http://master.example.com:8051/pprof/heap. The output is a machine-readable dump of the
stack traces with their associated heap usage.
Rather than visiting the heap profile page directly in a web browser, it is typically
more useful to use the pprof tool that is distributed as part of the gperftools
open source project. For example, a developer with a local build tree can use the
following command to collect the sampled heap usage and output an SVG diagram:
thirdparty/installed/uninstrumented/bin/pprof -svg 'http://localhost:8051/pprof/heap' > /tmp/heap.svg
The resulting SVG may be visualized in a web browser or sent to the Kudu community to help troubleshoot memory occupancy issues.
|
Tip
|
Heap samples contain only summary information about allocations and do not contain any data from the heap. It is safe to share heap samples in public without fear of exposing confidential or sensitive data. |
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.
Users will encounter this error when Kudu is unable to create more threads,
usually on versions of Kudu older than 1.7. It happens on tablet servers, and
is a sign that the tablet server hosts too many tablet replicas. To fix the
issue, users can raise the nproc ulimit as detailed in the documentation for
their operating system or distribution. However, the better solution is to
reduce the number of replicas on the tablet server. This may involve rethinking
the table’s partitioning schema. For the recommended limits on number of
replicas per tablet server, see the known issues and scaling limitations
documentation for the appropriate Kudu release. The
releases page has links to documentation
for previous versions of Kudu; for the latest release, see the
known issues page.