Presto C++ Features¶
Endpoints¶
HTTP endpoints related to tasks are registered to Proxygen in TaskResource.cpp. Important endpoints implemented include:
POST: v1/task: This processes a TaskUpdateRequest
GET: v1/task: This returns a serialized TaskInfo (used for comprehensive metrics, may be reported less frequently)
GET: v1/task/status: This returns a serialized TaskStatus (used for query progress tracking, must be reported frequently)
Other HTTP endpoints include:
POST: v1/memory * Reports memory, but no assignments are adjusted unlike in Java workers.
GET: v1/info
GET: v1/status
The request/response flow of Presto C++ is identical to Java workers. The tasks or new splits are registered via TaskUpdateRequest. Resource utilization and query progress are sent to the coordinator via task endpoints.
Remote Function Execution¶
Presto C++ supports remote execution of scalar functions. This feature is useful for cases when the function code is not written in C++, or if for security or flexibility reasons, the function code cannot be linked to the same executable as the main engine.
Remote function signatures need to be provided using a JSON file, following the format implemented by JsonFileBasedFunctionNamespaceManager. The following properties allow the configuration of remote function execution:
remote-function-server.signature.files.directory.path¶
Type:
stringDefault value:
""
The local filesystem path where JSON files containing remote function signatures are located. If not empty, the Presto native worker will recursively search, open, parse, and register function definitions from these JSON files.
remote-function-server.catalog-name¶
Type:
stringDefault value:
""
The catalog name to be added as a prefix to the function names registered
in Velox. The function name pattern registered is
catalog.schema.function_name, where catalog is defined by this
parameter, and schema and function_name are read from the input
JSON file.
If empty, the function is registered as schema.function_name.
remote-function-server.serde¶
Type:
stringDefault value:
"presto_page"
The serialization/deserialization method to use when communicating with
the remote function server. Supported values are presto_page or
spark_unsafe_row.
remote-function-server.thrift.address¶
Type:
stringDefault value:
""
The location (ip address or hostname) that hosts the remote function
server, if any remote functions were registered using
remote-function-server.signature.files.directory.path.
If not specified, falls back to the loopback interface (::1)
remote-function-server.thrift.port¶
Type:
integerDefault value:
0
The port that hosts the remote function server. If not specified and remote functions are trying to be registered, an exception is thrown.
remote-function-server.thrift.uds-path¶
Type:
stringDefault value:
""
The UDS (unix domain socket) path to communicate with a local remote
function server. If specified, takes precedence over
remote-function-server.thrift.address and
remote-function-server.thrift.port.
JWT authentication support¶
C++ based Presto supports JWT authentication for internal communication. For details on the generally supported parameters visit JWT.
There is also an additional parameter:
internal-communication.jwt.expiration-seconds¶
Type
integerDefault value:
300
There is a time period between creating the JWT on the client and verification by the server. If the time period is less than or equal to the parameter value, the request is valid. If the time period exceeds the parameter value, the request is rejected as authentication failure (HTTP 401).
Async Data Cache and Prefetching¶
connector.num-io-threads-hw-multiplier¶
Type
doubleDefault value:
1.0Presto on Spark default value:
0.0
Size of IO executor for connectors to do preload/prefetch. Prefetch is
disabled if connector.num-io-threads-hw-multiplier is set to zero.
async-data-cache-enabled¶
Type
boolDefault value:
truePresto on Spark default value:
false
Whether async data cache is enabled.
async-cache-ssd-gb¶
Type
integerDefault value:
0
Size of the SSD cache when async data cache is enabled.
enable-old-task-cleanup¶
Type
boolDefault value:
truePresto on Spark default value:
false
Enable periodic clean up of old tasks. The default value is true for Presto C++.
For Presto on Spark this property defaults to false, as zombie or stuck tasks
are handled by Spark by speculative execution.
old-task-cleanup-ms¶
Type
integerDefault value:
60000
Duration after which a task should be considered as old and will be eligible
for cleanup. Only applicable when enable-old-task-cleanup is true.
Old task is defined as a PrestoTask which has not received heartbeat for at least
old-task-cleanup-ms, or is not running and has an end time more than
old-task-cleanup-ms ago.
Session Properties¶
The following are the native session properties for C++ based Presto.
driver_cpu_time_slice_limit_ms¶
Type:
integerDefault value:
1000
Native Execution only. Defines the maximum CPU time in milliseconds that a driver thread is permitted to run before it must yield to other threads,facilitating fair CPU usage across multiple threads.
A positive value enforces this limit, ensuring threads do not monopolize CPU resources.
Negative values are considered invalid and are treated as a request to use the system default setting,
which is 1000 ms in this case.
Note: Setting the property to 0 allows a thread to run indefinitely
without yielding, which is not recommended in a shared environment as it can lead to
resource contention.
legacy_timestamp¶
Type:
booleanDefault value:
true
Native Execution only. Use legacy TIME and TIMESTAMP semantics.
native_aggregation_spill_memory_threshold¶
Type:
integerDefault value:
0
Native Execution only. Specifies the maximum memory in bytes
that a final aggregation operation can utilize before it starts spilling to disk.
If set to 0, there is no limit, allowing the aggregation to consume unlimited memory resources,
which may impact system performance.
native_debug_validate_output_from_operators¶
Type:
booleanDefault value:
false
If set to true, then during the execution of tasks, the output vectors of every operator are validated for consistency.
It can help identify issues where a malformed vector causes failures or crashes, facilitating the debugging of operator output issues.
Note: This is an expensive check and should only be used for debugging purposes.
native_join_spill_enabled¶
Type:
booleanDefault value:
true
Native Execution only. Enable join spilling on native engine.
native_join_spill_memory_threshold¶
Type:
integerDefault value:
0
Native Execution only. Specifies the maximum memory, in bytes, that a hash join operation can use before starting to spill to disk.
A value of 0 indicates no limit, permitting the join operation to use unlimited memory resources, which might affect overall system performance.
native_join_spiller_partition_bits¶
Type:
integerDefault value:
2
Native Execution only. Specifies the number of bits (N)
used to calculate the spilling partition number for hash join and RowNumber operations.
The partition number is determined as 2 raised to the power of N, defining how data is partitioned during the spill process.
native_max_spill_file_size¶
Type:
integerDefault value:
0
Specifies the maximum allowed spill file size in bytes. If set to 0, there is no limit on the spill file size,
allowing spill files to grow as large as necessary based on available disk space.
Use native_max_spill_file_size to manage disk space usage during operations that require spilling to disk.
native_max_spill_level¶
Type:
integerDefault value:
4
Native Execution only. The maximum allowed spilling level for hash join build.
0 is the initial spilling level, -1 means unlimited.
native_order_by_spill_memory_threshold¶
Type:
integerDefault value:
0
Native Execution only. Specifies the maximum memory, in bytes, that the ORDER BY operation can utilize before starting to spill data to disk.
If set to 0, there is no limit on memory usage, potentially leading to large memory allocations for sorting operations.
Use this threshold to manage memory usage more efficiently during ORDER BY operations.
native_row_number_spill_enabled¶
Type:
booleanDefault value:
true
Native Execution only. Enable row number spilling on native engine.
native_simplified_expression_evaluation_enabled¶
Type:
booleanDefault value:
false
Native Execution only. Enable simplified path in expression evaluation.
native_spill_compression_codec¶
Type:
varcharDefault value:
none
Native Execution only. Specifies the compression CODEC used to compress spilled data.
Supported compression CODECs are: ZLIB, SNAPPY, LZO, ZSTD, LZ4, and GZIP.
Setting this property to none disables compression.
native_spill_file_create_config¶
Type:
varcharDefault value:
""
Native Execution only. Specifies the configuration parameters used to create spill files. These parameters are provided to the underlying file system, allowing for customizable spill file creation based on the requirements of the environment. The format and options of these parameters are determined by the capabilities of the underlying file system and may include settings such as file location, size limits, and file system-specific optimizations.
native_spill_write_buffer_size¶
Type:
bigintDefault value:
1048576
Native Execution only. The maximum size in bytes to buffer the serialized spill data before writing to disk for IO efficiency.
If set to 0, buffering is disabled.
native_topn_row_number_spill_enabled¶
Type:
booleanDefault value:
true
Native Execution only. Enable topN row number spilling on native engine.
native_window_spill_enabled¶
Type:
booleanDefault value:
true
Native Execution only. Enable window spilling on native engine.
native_writer_spill_enabled¶
Type:
booleanDefault value:
true
Native Execution only. Enable writer spilling on native engine.