Command line flags
materialized binary supports the following command line flags:
||Where data is persisted
Known issue. The short form of this option was inadvertently removed in v0.7.0. It will be restored in v0.7.1.
||N/A||Advanced. Amount of compaction to perform when idle.|
||N/A||NOP—prints binary’s list of command line flags|
||N/A||Disables telemetry reporting.|
||Disabled||Dangerous. Enable experimental features.|
||1s||The frequency at which to update introspection sources.|
||30s||The update interval for the
||The host and port on which to listen for HTTP and SQL connections|
||1ms||The amount of historical detail to retain in arrangements|
||Where to emit log messages|
||Which log messages to emit|
||demand||Advanced. Timely progress tracking mode.|
||N/A||Path to TLS certificate authority (CA)
New in v0.7.1.
||N/A||Path to TLS certificate file|
||N/A||How stringently to demand TLS authentication and encryption
New in v0.7.1.
||N/A||Path to TLS private key file|
||NCPUs / 2||Dataflow worker threads|
||N/A||Print version and exit|
||N/A||Print version and additional build information, and exit|
||Disabled||Start without creating any dataflows for user indexes.|
If a command line flag takes an argument, you can alternatively set that flag via an environment variable named after the flag. If both the environment variable and command line flag are specified, the command line flag takes precedence.
The process for converting a flag name to an environment variable name is as follows:
- Convert all characters to uppercase
- Replace all hyphens with underscores
- add an
For example, the
--data-directory command line flag corresponds to the
MZ_DATA_DIRECTORY environment variable.
Note that command line flags that do not take arguments, like
--disable-telemetry, do not yet have corresponding environment variables.
materialized creates a directory where it persists metadata. By
default, this directory is called
mzdata and is situated in the current
working directory of the materialized process. Currently, only metadata is
mzdata. You can specify a different directory using the
--data-directory flag. Upon start,
materialized checks for an existing data
directory, and will reinstall source and view definitions from it if one is
materialized instance runs a specified number of timely dataflow worker
threads. Worker threads can only be specified at startup by setting the
--workers flag, and cannot be changed without shutting down
and restarting. If
--workers is not set,
materialized will default to using
half of the machine’s physical cores as the thread count. In the future,
dynamically changing the number of worker threads will be possible over
distributed clusters, see
Changed in v0.4.0:
--threads flag to
Changed in v0.5.1: When unspecified, default to using half of the machine’s physical cores.
How many worker threads should you run?
Adding worker threads allows Materialize to handle more throughput. Reducing worker threads consumes fewer resources, and reduces tail latencies.
In general, you should use the fewest number of worker threads that can handle your peak throughputs. This is also the most resource efficient.
You should never run Materialize in a configuration greater than
n is the number of physical cores. Note that major cloud providers
list the number of hyperthreaded cores (or virtual CPUs). Divide this number
by two to get the number of physical cores available. The reasoning is simple:
Timely Dataflow is very computationally efficient and typically uses all
available computational resources. Under high throughput, you should see each
worker pinning a core at 100% CPU, with no headroom for hyperthreading. One
additional core is required for metadata management and coordination. Timely
workers that have to fight for physical resources will only block each other.
r5d.4xlarge instance has 16 VCPUs, or 8 physical cores. The
recommended worker setting on this VM is
materialized binds to
0.0.0.0:6875. This means that Materialize
will accept any incoming SQL connection to port 6875 from anywhere. It is the
responsibility of the network firewall to limit incoming connections. If you
wish to configure
materialized to only listen to, e.g. localhost connections,
you can set
localhost:6875. You can also use this to change
the port that Materialize listens on from the default
--logical-compaction-window option specifies the duration of time for
which Materialize is required to maintain full historical detail in its
arrangements. Note that compaction happens
lazily, so Materialize may retain more historical detail than requested, but it
will never retain less.
The value of the option is any valid SQL interval
10ms (10 milliseconds) or
1min 30s (1 minute, 30
seconds). The special value
off disables logical compaction and
corresponds to an unboundedly large duration.
The logical compaction window ends at the current time and extends backwards in time for the configured duration. The default window is 1 millisecond.
See the Deployment section for guidance on tuning the compaction window.
--log-file option specifies the path to a file in which Materialize will
write its log messages. The value
stderr is treated
specially and specifies the standard error stream.
If the option is unspecified, Materialize writes log messages to the
materialized.log file in the data directory and
additionally forwards any log messages at the
ERROR levels to the
standard error stream. Forwarding does not occur if you explicitly specify a log
New in v0.7.2.
--log-filter option specifies which log
messages Materialize will emit. Its value is a
comma-separated list of filter directives. Each filter directive has the
A filter directive registers interest in log messages from the specified module that are at least as severe as the specified level. If a directive omits the module, then it implicitly applies to all modules. When directives conflict, the last directive wins. Materialize will only emit log messages that match at least one filter directive.
Specifying module paths in filter directives requires familiarity with Materialize’s codebase and is intended for advanced users.
The valid levels for a log message are documented in the logging
section of the monitoring documentation and are not
case sensitive. The special level
off may be used in a directive to suppress
all log messages, even those at the
As an example, the following filter specifies the
TRACE level for the
module, which handles SQL network connections, and the
INFO level for all
Changed in v0.7.1:
In prior versions of Materialize, this option was undocumented but available
under the name
Materialize maintains several built-in sources and views in
mz_catalog that describe the internal state of the
dataflow execution layer, like
--introspection-frequency option determines the frequency at which the
base sources are updated. The default frequency is
1s. To disable
introspection entirely, use the special value
Higher frequencies provide more up-to-date introspection but increase load on the system. Lower frequencies increase staleness in exchange for decreased load. The default frequency is a good choice for most deployments.
Changed in v0.9.1: In prior versions of Materialize, the metrics scraping interval was linked to the introspection interval.
--metrics-scraping-interval option determines the interval at which the
prometheus metrics are collected to update the
mz_metrics table. The default
30s. To disable prometheus metrics collection entirely, use the
Lower intervals provide more up-to-date metrics but increase load on the system. Higher intervals increase staleness in exchange for decreased load. The default interval is a good choice for most deployments.
Changed in v0.7.3:
Materialize imports its own Prometheus metrics
into the systems tables
mz_metrics (counters and gauge readings),
mz_metric_histograms (histogram distributions) and
information and help for each metric). These readings are imported once per
--metrics-scraping-interval period, and are retained for the duration given with
--retain-prometheus-metrics (defaulting to 5 minutes). Higher retention
periods lead to greater memory usage.
Materialize can use Transport Layer Security (TLS) to:
- Encrypt traffic between SQL and HTTP clients and the
- Authenticate SQL and HTTP clients
New in v0.7.1:
Whether Materialize requires TLS encryption or authentication is determined by
the value of the
Materialize will reject HTTPS connections and SQL connections that negotiate TLS. This is the default mode if
||Requires TLS encryption.
Materialize will reject HTTP connections and SQL connections that do not negotiate TLS.
Materialize verifies that the client certificate is issued by the certificate authority (CA) specified by the
For HTTPS connections, this user is taken directly from the CN field. For SQL connections, the name of the user in the connection parameters must match the name specified in the CN field.
This is the default mode if
In all TLS modes but
disable, you will need to supply two files, one
containing a TLS certificate and one containing the corresponding private key.
materialized at these files using the
If the TLS mode is
verify-full, you will additionally need to
supply the path to a TLS certificate authority (CA) via the
Client certificates will be verified using this CA.
The following example demonstrates how to configure a server in
$ materialized -w1 --tls-cert=server.crt --tls-key=server.key --tls-ca=root.crt
Materialize statically links against a vendored copy of OpenSSL. It does not
use any SSL library that may be provided by your system. To see the version of
OpenSSL used by a particular
materialized binary, inquire with the
$ materialize -vv
materialized v0.2.3-dev (c62c988e8167875b92122719eee5709cf81cdac4) OpenSSL 1.1.1g 21 Apr 2020 librdkafka v1.4.2
Materialize configures OpenSSL according to Mozilla’s Intermediate compatibility level, which requires TLS v1.2+ and recent cipher suites. Using weaker cipher suites or older TLS protocol versions is not supported.
Generating TLS certificates
You can generate a self-signed certificate for development use with the
openssl command-line tool:
$ openssl req -new -x509 -days 365 -nodes -text \ -out server.crt -keyout server.key -subj "/CN=<SERVER-HOSTNAME>"
Production deployments typically should not use self-signed certificates. Acquire a certificate from a proper certificate authority (CA) instead.
New in v0.4.0.
Materialize offers access to experimental features through the
flag. Unlike most features in Materialize, experimental features' syntax and/or
semantics can shift at any time, and there is no guarantee that future
versions of Materialize will be interoperable with the experimental features.
Using experimental mode means that you are likely to lose access to all of your sources and views within Materialize and will have to recreate them and re-ingest all of your data.
Because of this volatility:
- You can only initialize new servers in experimental mode.
- Servers started in experimental mode must always be started in experimental mode.
We recommend only using experimental mode to explore Materialize, i.e. absolutely never in production. If your explorations yield interesting results or things you’d like to see changed, let us know on GitHub.
Disabling experimental mode
You cannot disable experimental mode for a server. You can, however, extract your
view and source definitions (
SHOW CREATE VIEW,
SHOW CREATE SOURCE,
etc.), and then create a new server with those items.
Materialize periodically communicates with
telemetry.materialize.com to report
usage data and check for new versions. You can opt out of this communication
We record the following data:
- Public IP of the host running Materialize
- Cluster ID, a unique ID which is persistent across Materialize restarts
- Session ID, a unique ID which is reset on each Materialize restart
- Materialize version
- Number of worker threads
- Count of sinks, sources, and views by type
We use this data to guide our product roadmap. Unless you are using Materialize Cloud, we do not and cannot correlate this data to your identity.
There are several command-line options that tune various parameters for Materialize’s underlying dataflow engine:
--differential-idle-merge-effortcontrols how aggressively Materialize will perform compaction when idle.
--timely-progress-modesets Timely Dataflow’s progress tracking mode.
Using these parameters correctly requires substantial knowledge about how the underlying Timely and Differential Dataflow engines work. Typically you should only set these parameters in consultation with Materialize engineers.
Disable user indexes
New in v0.9.2.
If you cannot boot a Materialize server because it runs out of memory, you can use
--disable-user-indexes to prevent Materialize from creating any
indexes on user-created objects. For
example, if you add a view that contains a cross join that causes your server to
immediately run out of memory on boot, you can use
boot the server and then drop the offending view.
In this mode users…
- Can access objects within the system catalog to help determine which indexes are causing the crash.
- Can only
SELECTfrom user-created objects that do not rely on user-created indexes. In essence, this means users can still
- Tables, but they will never return any data.
- Views that contain only references to constant values or depend entirely on system tables' indexes.
INSERTdata into tables.
- Can create new objects, but any created indexes are disabled.
After troubleshooting any issues, you can enable individual indexes or restart Materialize without disabling user indexes to enable all indexes at once.
For assistance with this mode, see:
Special environment variables
Materialize respects several environment variables that have conventional meanings in Unix systems.
variables specify a proxy to use for outgoing HTTP and HTTPS traffic. There is
no precise specification of how these variables behave, but Materialize’s
behavior generally matches the behavior of other HTTP clients.
For precise details of Materialize’s behavior, consult the documentation of