System Catalog

New in v0.5.0.

Materialize exposes a system catalog that contains metadata about the running Materialize instance.

WARNING! The system tables are not part of Materialize’s stable interface. Backwards-incompatible changes to these tables may be made at any time.

Details

The system catalog consists of two schemas that are implicitly available in all databases:

mz_catalog, which exposes metadata in Materialize’s native format.
pg_catalog, which presents the data in mz_catalog in the format used by PostgreSQL.

These schemas contain sources, tables, and views that expose metadata like:

Descriptions of each database, schema, source, table, view, sink, and index in the system.
Descriptions of all running dataflows.
Metrics about dataflow execution.

Whenever possible, applications should prefer to query mz_catalog over pg_catalog. The mapping between Materialize concepts and PostgreSQL concepts is not one-to-one, and so the data in pg_catalog cannot accurately represent the particulars of Materialize. For example, PostgreSQL has no notion of sinks, and therefore pg_catalog does not display information about the sinks available in a Materialize.

`mz_catalog`

The following sections describe the available objects in the mz_catalog schema.

`mz_array_types`

The mz_array_types table contains a row for each array type in the system.

Field	Type	Meaning
`type_id`	`text`	The ID of the array type.
`element_id`	`text`	The ID of the array’s element type.

`mz_arrangement_sharing`

The mz_arrangement_sharing source describes how times each arrangement in the system is used.

Field	Type	Meaning
`operator`	`bigint`	The ID of the operator that created the arrangement. Corresponds to `mz_dataflow_operators.id`.
`worker`	`bigint`	The ID of the worker thread hosting the arrangement.
`count`	`bigint`	The number of operators that share the arrangement.

`mz_arrangement_sizes`

The mz_arrangement_sizes source describes the size of each arrangement in the system.

Field	Type	Meaning
`operator`	`bigint`	The ID of the operator that created the arrangement. Corresponds to `mz_dataflow_operators.id`.
`worker`	`bigint`	The worker hosting the arrangement.
`records`	`bigint`	The number of records in the arrangement.
`batches`	`bigint`	The number of batches in the arrangement.

`mz_avro_ocf_sinks`

The mz_avro_ocf_sinks table contains a row for each Avro OCF sink in the system.

Field	Type	Meaning
`sink_id`	`text`	The ID of the sink.
`path`	`bytea`	The path to the Avro OCF file into which the sink is writing.

`mz_base_types`

The mz_base_types table contains a row for each base type in the system.

Field	Type	Meaning
`type_id`	`text`	The ID of the type.

`mz_columns`

The mz_columns contains a row for each column in each table, source, and view in the system.

Field	Type	Meaning
`id`	`bigint`	The unique ID of the table, source, or view containing the column.
`name`	`text`	The name of the column.
`position`	`bigint`	The 1-indexed position of the column in its containing table, source, or view.
`nullable`	`boolean`	Can the column contain a `NULL` value?
`type`	`text`	The data type of the column.

`mz_databases`

The mz_databases table contains a row for each database in the system.

Field	Type	Meaning
`id`	`bigint`	Materialize’s unique ID for the database.
`oid`	`oid`	A PostgreSQL-compatible OID for the database.
`name`	`text`	The name of the database.

`mz_dataflow_channels`

The mz_dataflow_channels source describes the communication channels between dataflow operators. A communication channel connects one of the the outputs of a source operator to one of the inputs of a target operator.

Field	Type	Meaning
`id`	`bigint`	The ID of the channel.
`worker`	`bigint`	The ID of the worker thread hosting the channel.
`source_node`	`bigint`	The ID of the source operator. Corresponds to `mz_dataflow_operators.id`.
`source_port`	`bigint`	The source operator’s output port.
`target_node`	`bigint`	The ID of the target operator. Corresponds to `mz_dataflow_operators.id`.
`target_port`	`bigint`	The target operator’s input port.

`mz_dataflow_names`

The mz_dataflow_names view describes the dataflows in the system.

Field	Type	Meaning
`id`	`bigint`	The ID of the dataflow.
`worker`	`bigint`	The ID of the worker thread hosting the dataflow.
`local_id`	`bigint`	The scope-local index of the dataflow.
`name`	`text`	The internal name of the dataflow.

`mz_dataflow_operator_addresses`

The mz_dataflow_operator_addresses source describes how the dataflow channels and operators in the system are nested into scopes.

Field	Type	Meaning
`id`	`bigint`	The ID of the channel or operator. Corresponds to `mz_dataflow_channels.id` or `mz_dataflow_operators.id`.
`worker`	`bigint`	The ID of the worker thread hosting the channel or operator.
`address`	`bigint list`	A list of scope-local indexes indicating the path from the root to this channel or operator.

`mz_dataflow_operator_dataflows`

The mz_dataflow_operator_dataflows view describes the dataflow to which each dataflow operator belongs.

Field	Type	Meaning
`id`	`bigint`	The ID of the operator.
`name`	`text`	The internal name of the operator.
`worker`	`bigint`	The ID of the worker thread hosting the operator.
`dataflow_id`	`bigint`	The ID of the dataflow hosting the operator.
`dataflow_name`	`text`	The name of the dataflow hosting the operator.

`mz_dataflow_operators`

The mz_dataflow_operators source describes the dataflow operators in the system.

Field	Type	Meaning
`id`	`bigint`	The ID of the operator.
`worker`	`bigint`	The ID of the worker thread hosting the operator.
`name`	`text`	The name of the operator.

`mz_functions`

The mz_functions table contains a row for each function in the system.

Field	Type	Meaning
`id`	`text`	Materialize’s unique ID for the function.
`oid`	`oid`	A PostgreSQL-compatible OID for the function.
`schema_id`	`bigint`	The ID of the schema to which the function belongs.
`name`	`text`	The name of the function.
`arg_ids`	`text array`	The function’s arguments’ types. Elements refers to `mz_types.id`.
`variadic_id`	`text`	The variadic array parameter’s elements, or `NULL` if the function does not have a variadic parameter. Refers to `mz_types.id`.

`mz_indexes`

The mz_indexes table contains a row for each index in the system.

Field	Type	Meaning
`id`	`text`	Materialize’s unique ID for the index.
`oid`	`oid`	A PostgreSQL-compatible OID for the index.
`name`	`text`	The name of the index.
`on_id`	`text`	The ID of the relation on which the index is built.
`volatility`	`text`	Whether the the index is volatile. Either `volatile`, `nonvolatile`, or `unknown`.

`mz_index_columns`

The mz_index_columns table contains a row for each column in each index in the system. For example, an index on (a, b + 1) would have two rows in this table, one for each of the two columns in the index.

For a given row, if field_number is null then expression will be nonnull, or vice-versa.

Field	Type	Meaning
`index_id`	`text`	The ID of the index which contains this column.
`index_position`	`bigint`	The 1-indexed position of this column within the index. (The order of columns in an index does not necessarily match the order of columns in the relation on which the index is built.)
`on_position`	`bigint`	If not `NULL`, specifies the 1-indexed position of a column in the relation on which this index is built that determines the value of this index column.
`on_expression`	`text`	If not `NULL`, specifies a SQL expression that is evaluated to compute the value of this index column. The expression may contain references to any of the columns of the relation.
`nullable`	`boolean`	Can this column of the index evaluate to `NULL`?

`mz_kafka_broker_rtt`

The mz_kafka_broker_rtt table contains round-trip time (RTT) statistics for the Kafka consumers in the system.

Field	Type	Meaning
`consumer_name`	`text`	The internal name of the Kafka consumer.
`source_id`	`text`	The ID of the source that created this consumer object. Corresponds to `mz_source_info.source_id`.
`dataflow_id`	`bigint`	The ID of the dataflow reading from the consumer. Corresponds to `mz_source_info.dataflow_id`.
`broker_name`	`text`	The name of the Kafka broker.
`min`	`bigint`	The minimum RTT in milliseconds.
`max`	`bigint`	The maximum RTT in milliseconds.
`avg`	`bigint`	The average RTT in milliseconds.
`sum`	`bigint`	The sum of all RTTs in milliseconds.
`cnt`	`bigint`	The number of round trips recorded.
`stddev`	`bigint`	The standard deviation of the RTT in milliseconds.
`p50`	`bigint`	The 50th percentile RTT in milliseconds.
`p90`	`bigint`	The 90th percentile RTT in milliseconds.
`p95`	`bigint`	The 95th percentile RTT in milliseconds.
`p99`	`bigint`	The 99th percentile RTT in milliseconds.
`p99_99`	`bigint`	The 99.99th percentile RTT in milliseconds.

`mz_kafka_consumer_partitions`

The mz_kafka_consumer_partitions table contains a row for each partition being read by a Kafka consumer in the system.

Field	Type	Meaning
`consumer_name`	`text`	The handle name for the consumer.
`source_id`	`text`	The ID of the source that created this consumer object. Corresponds to `mz_source_info.source_id`.
`dataflow_id`	`bigint`	The ID of the dataflow reading from the consumer. Corresponds to `mz_source_info.dataflow_id`.
`partition_id`	`text`	The ID of the topic partition the consumer is reading from.
`rx_msgs`	`bigint`	The number of messages read by this consumer since materialized startup.
`rx_bytes`	`bigint`	The number of bytes read by this consumer since materialized startup.
`tx_msgs`	`bigint`	The number of messages sent by this consumer since materialized startup.
`tx_bytes`	`bigint`	The number of bytes sent by this consumer since materialized startup.
`lo_offset`	`bigint`	The partition’s low watermark offset on the broker.
`hi_offset`	`bigint`	The partition’s high watermark offset on the broker.
`ls_offset`	`bigint`	The partition’s last stable offset on the broker.
`app_offset`	`bigint`	The offset of the last message passed to materialized + 1.
`consumer_lag`	`bigint`	Difference between the `hi_offset` and `app_offset`.
`initial_high_offset`	`bigint`	The first known partition’s high watermark offset on the broker, based on `hi_offset`.

`mz_kafka_sinks`

The mz_kafka_sinks table contains a row for each Kafka sink in the system.

Field	Type	Meaning
`sink_id`	`text`	The ID of the sink.
`topic`	`text`	The name of the Kafka topic into which the sink is writing.
`consistency_topic`	`text`	The name of the Kafka topic into which the sink is writing consistency information. This is `NULL` when the sink does not write consistency information.

`mz_list_types`

The mz_list_types table contains a row for each list type in the system.

Field	Type	Meaning
`type_id`	`text`	The ID of the list type.
`element_id`	`text`	The IID of the list’s element type.

`mz_message_counts`

The mz_message_counts source describes the messages sent and received over the dataflow channels in the system.

Field	Type	Meaning
`channel`	`bigint`	The ID of the channel. Corresponds to `mz_dataflow_channels.id`.
`source_worker`	`bigint`	The ID of the worker thread sending the message.
`target_worker`	`bigint`	The ID of the worker thread receiving the message.
`sent`	`bigint`	The number of messages sent.
`received`	`bigint`	The number of messages received.

`mz_materialization_dependencies`

The mz_materialization_dependencies source describes the sources that each dataflow depends on.

Field	Type	Meaning
`dataflow`	`text`	The ID of the index that created the dataflow. Corresponds to `mz_indexes.id`.
`source`	`text`	The ID of the source. Corresponds to `mz_sources.id`.
`worker`	`bigint`	The ID of the worker thread hosting the dataflow.

`mz_materialization_frontiers`

The mz_materialization_frontiers view describes the frontier for each dataflow in the system across all workers. The frontier describes the earliest timestamp at which the output of the dataflow may change; data prior to that timestamp is sealed.

For per-worker frontier information, see mz_worker_materialization_frontiers.

Field	Type	Meaning
`global_id`	`text`	The ID of the index that created the dataflow. Corresponds to `mz_indexes.id`.
`time`	`bigint`	The next timestamp at which the materialization may change.

`mz_materializations`

The mz_materializations source describes the indexes in the system.

Field	Type	Meaning
`name`	`text`	The ID of the index. (`name` is a misnomer.)
`worker`	`bigint`	The ID of the worker thread hosting the index.

`mz_map_types`

The mz_map_types table contains a row for each map type in the system.

Field	Type	Meaning
`type_id`	`text`	The ID of the map type.
`key_id`	`text`	The ID of the map’s key type.
`value_id`	`text`	The ID of the map’s value type.

`mz_metrics`

The mz_metrics table contains recordings for each Prometheus metric in the system that is a counter or gauge. The values are recorded every second and retained for five minutes.

Field	Type	Meaning
`metric`	`text`	The name of the metric.
`time`	`timestamp`	The time at which the metric was recorded.
`labels`	`jsonb`	The metric’s labels and their associated values as a JSON object.
`value`	`double precision`	The value of the counter or gauge.

`mz_metrics_meta`

The mz_metrics_meta table describes metadata about each Prometheus metric in the system.

Field	Type	Meaning
`metric`	`text`	The name of the metric.
`type`	`text`	The type of the metric (`counter`, `gauge`, or `histogram`).
`help`	`text`	The description of the metric.

`mz_metric_histograms`

The mz_metric_histograms table contains recordings for each Prometheus metric in the system that is a histogram. The values are recorded every second and retained for five minutes. Each row of the table represents one bucket of one histogram from one recording. Note that Prometheus histograms are cumulative.

Field	Type	Meaning
`metric`	`text`	The name of the metric.
`time`	`timestamp`	The time at which the metric was recor
`labels`	`jsonb`	The metric’s labels and their associated values as a JSON object.
`bound`	`double precision`	The upper bound of the bucket.
`count`	`bigint`	The (cumulative) count of observations in the bucket.

`mz_objects`

The mz_objects view contains a row for each table, source, view, sink, and index in the system.

Field	Type	Meaning
`id`	`text`	Materialize’s unique ID for the object.
`oid`	`oid`	A PostgreSQL-compatible OID for the object.
`schema_id`	`bigint`	The ID of the schema to which the object belongs.
`name`	`text`	The name of the object.
`type`	`text`	The type of the object: either `table`, `source`, `view`, `sink`, or `index`.

`mz_peek_active`

The mz_peek_active source describes all read queries (“peeks”) that are pending in the dataflow layer.

Field	Type	Meaning
`uuid`	`text`	The ID of the connection that requested the peek. `uuid` is a misnomer; connection IDs are 32-bit unsigned integers.
`worker`	`bigint`	The ID of the worker thread servicing the peek.
`id`	`text`	The ID of the index the peek is targeting.
`time`	`bigint`	The timestamp the peek has requested.

`mz_peek_durations`

The mz_peek_durations source describes a histogram of the duration of read queries (“peeks”) in the dataflow layer.

Field	Type	Meaning
`worker`	`bigint`	The ID of the worker thread servicing the peek.
`duration_ns`	`bigint`	The upper bound of the bucket in nanoseconds.
`count`	`bigint`	The (noncumulative) count of peeks in this bucket.

`mz_perf_dependency_frontiers`

The mz_perf_dependency_frontiers view describes the lag between a dataflow’s outputs and its sources. It contains a row for every dataflow in the system that depends on at least one source.

Field	Type	Meaning
`dataflow`	`text`	The name of the dataflow hosting the source.
`source`	`text`	The name of the source.
`lag_ms`	`bigint`	The amount of lag between when a record is emitted by the source and when the output of the dataflow reflects that record.

`mz_pseudo_types`

The mz_pseudo_types table contains a row for each psuedo type in the system.

Field	Type	Meaning
`type_id`	`text`	The ID of the type.

`mz_records_per_dataflow`

The mz_records_per_dataflow view describes the number of records in each dataflow on each worker in the system.

For the same information aggregated across all workers, see mz_records_per_dataflow_global.

Field	Type	Meaning
`id`	`bigint`	The ID of the dataflow. Corresponds to `mz_dataflow_names.id`.
`name`	`text`	The internal name of the dataflow.
`worker`	`bigint`	The ID of the worker thread hosting the dataflow.
`records`	`numeric`	The number of records in the dataflow.

`mz_records_per_dataflow_global`

The mz_records_per_dataflow_global view describes the number of records in each dataflow in the system.

For the same information broken down across workers, see mz_records_per_dataflow.

Field	Type	Meaning
`id`	`bigint`	The ID of the dataflow. Corresponds to `mz_dataflow_names.id`.
`name`	`text`	The internal name of the dataflow.
`records`	`numeric`	The number of records in the dataflow.

`mz_records_per_dataflow_operator`

The mz_records_per_dataflow_operator view describes the number of records in each dataflow operator in the system.

Field	Type	Meaning
`id`	`bigint`	The ID of the operator. Corresponds to `mz_dataflow_operators.id`.
`name`	`text`	The internal name of the dataflow.
`worker`	`bigint`	The ID of the worker thread hosting the dataflow.
`dataflow_id`	`bigint`	The ID of the dataflow. Corresponds to `mz_dataflow_names.id`.
`records`	`numeric`	The number of records in the dataflow.

`mz_relations`

The mz_relations view contains a row for each table, source, and view in the system.

Field	Type	Meaning
`id`	`text`	Materialize’s unique ID for the relation.
`oid`	`oid`	A PostgreSQL-compatible OID for the relation.
`schema_id`	`bigint`	The ID of the schema to which the relation belongs.
`name`	`text`	The name of the relation.
`type`	`text`	The type of the relation: either `table`, `source`, or `view`.

`mz_roles`

The mz_roles table contains a row for each role in the system.

Field	Type	Meaning
`id`	`bigint`	Materialize’s unique ID for the role.
`oid`	`oid`	A PostgreSQL-compatible OID for the role.
`name`	`text`	The name of the role.

`mz_scheduling_elapsed`

The mz_scheduling_elapsed source describes the total amount of time spent in each dataflow operator.

Field	Type	Meaning
`id`	`bigint`	The ID of the operator. Corresponds to `mz_dataflow_operators.id`.
`worker`	`bigint`	The ID of the worker thread hosting the operator.
`elapsed_ns`	`bigint`	The total elapsed time spent in the operator in nanoseconds.

`mz_scheduling_histogram`

The mz_scheduling_histogram source stores a histogram describing the duration of each invocation for each dataflow operator.

Field	Type	Meaning
`id`	`bigint`	The ID of the operator. Corresponds to `mz_dataflow_operators.id`.
`worker`	`bigint`	The ID of the worker thread hosting the operator.
`duration_ns`	`bigint`	The upper bound of the bucket.
`count`	`bigint`	The number of recordings in the bucket.

`mz_scheduling_parks`

The mz_scheduling_parks source stores a histogram describing dataflow worker park events. A park event occurs when a worker has no outstanding work.

Field	Type	Meaning
`worker`	`bigint`	The ID of the worker thread.
`slept_for`	`bigint`	The actual length of the park event.
`requested`	`bigint`	The requested length of the park event.
`count`	`bigint`	The number of park events in this bucket.

`mz_schemas`

The mz_schemas table contains a row for each schema in the system.

Field	Type	Meaning
`id`	`bigint`	Materialize’s unique ID for the schema.
`oid`	`oid`	A PostgreSQL-compatible oid for the schema.
`database_id`	`bigint`	The ID of the database containing the schema.
`name`	`text`	The name of the schema.

`mz_sinks`

The mz_sinks table contains a row for each sink in the system.

Field	Type	Meaning
`id`	`text`	Materialize’s unique ID for the sink.
`oid`	`oid`	A PostgreSQL-compatible OID for the sink.
`schema_id`	`bigint`	The ID of the schema to which the sink belongs.
`name`	`text`	The name of the sink.
`connector_type`	`text`	The type of the sink: `avro-ocf` or `kafka`.
`volatility`	`text`	Whether the sink is volatile. Either `volatile`, `nonvolatile`, or `unknown`.

`mz_source_info`

The mz_source_info table contains a row for each partition of each source in the system.

Field	Type	Meaning
`source_name`	`text`	Materialize’s internal name for the source.
`source_id`	`text`	Materialize’s unique ID for the source. Corresponds to `mz_sources.id`.
`dataflow_id`	`bigint`	The ID of the dataflow responsible for processing this source.
`partition_id`	`text`	The ID of the partition within the source. The concept of partition varies by source type. Not all sources types have multiple partitions, in which case there will be only one entry for partition ID `0`.
`offset`	`bigint`	The highest offset processed by this source.
`timestamp`	`bigint`	The largest `mz_timestamp` processed by this source.

`mz_sources`

The mz_sources table contains a row for each source in the system.

Field	Type	Meaning
`id`	`text`	Materialize’s unique ID for the source.
`oid`	`oid`	A PostgreSQL-compatible OID for the source.
`schema_id`	`bigint`	The ID of the schema to which the source belongs.
`name`	`text`	The name of the source.
`connector_type`	`text`	The type of the source: `avro-ocf`, `file`, `kafka`, `kinesis`, `s3`, `postgres`, or `pubnub`.
`volatility`	`text`	Whether the source is volatile. Either `volatile`, `nonvolatile`, or `unknown`.

`mz_tables`

The mz_tables table contains a row for each table in the system.

Field	Type	Meaning
`id`	`text`	Materialize’s unique ID for the table.
`oid`	`oid`	A PostgreSQL-compatible OID for the table.
`schema_id`	`bigint`	The ID of the schema to which the table belongs.
`name`	`text`	The name of the table.

`mz_types`

The mz_types table contains a row for each type in the system.

Field	Type	Meaning
`id`	`text`	Materialize’s unique ID for the type.
`oid`	`oid`	A PostgreSQL-compatible OID for the type.
`schema_id`	`bigint`	The ID of the schema to which the type belongs.
`name`	`text`	The name of the type.

`mz_views`

The mz_views table contains a row for each view in the system.

Field	Type	Meaning
`id`	`text`	Materialize’s unique ID for the view.
`oid`	`oid`	A PostgreSQL-compatible OID for the view.
`schema_id`	`bigint`	The ID of the schema to which the view belongs.
`name`	`text`	The name of the view.
`volatility`	`text`	Whether the view is volatile. Either `volatile`, `nonvolatile`, or `unknown`.

`mz_worker_materialization_frontiers`

The mz_worker_materialization_frontiers source describes each worker’s frontier for each dataflow in the system. The frontier describes the earliest timestamp at which the output of the dataflow may change; data prior to that timestamp is sealed.

For frontier information aggregated across all workers, see mz_materialization_frontiers.

Field	Type	Meaning
`global_id`	`text`	The ID of the index that created the dataflow. Corresponds to `mz_indexes.id`.
`worker`	`bigint`	The ID of the worker thread hosting the dataflow.
`time`	`bigint`	The next timestamp at which the dataflow may change.

`pg_catalog`

Materialize has compatibility shims for the following tables from PostgreSQL’s system catalog:

These compatibility shims are largely incomplete. Most are lacking some columns that are present in PostgreSQL, or if they do include the column the result set its value may always be NULL. The precise nature of the incompleteness is intentionally undocumented. New tools developed against Materialize should use the documented mz_catalog API instead.

If you are having trouble making a PostgreSQL tool work with Materialize, please file a GitHub issue. Many PostgreSQL tools can be made to work with Materialize with minor changes to the pg_catalog compatibility shim.

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