Streamly.Internal.Data.Channel

Channel driver throws this exception to all active workers to clean up the channel.

Events that a child thread may send to a parent thread.

We measure the individual worker latencies to estimate the number of workers needed or the amount of time we have to sleep between dispatches to achieve a particular rate when controlled pace mode it used.

Rate control.

Same as readOutputQBasic but additionally update the max output queue size channel stat if the new size is more than current max.

Read the output queue of the channel. After reading set it to empty list and 0 count.

RingArray door bell. The IORef is read after adding a store-load barrier. If the IORef was set to True it is atomically reset to False.

A worker decrements the yield limit before it executes an action. However, the action may not result in an element being yielded, in that case we have to increment the yield limit.

Note that we need it to be an Int type so that we have the ability to undo a decrement that takes it below zero.

Specifies the stream yield rate in yields per second (Hertz). We keep accumulating yield credits at rateGoal. At any point of time we allow only as many yields as we have accumulated as per rateGoal since the start of time. If the consumer or the producer is slower or faster, the actual rate may fall behind or exceed rateGoal. We try to recover the gap between the two by increasing or decreasing the pull rate from the producer. However, if the yield count gap becomes more than rateBuffer (specified as a yield count) we try to recover only as much as rateBuffer.

rateLow puts a bound on how low the instantaneous rate can go when recovering the rate gap. In other words, it determines the maximum yield latency. Similarly, rateHigh puts a bound on how high the instantaneous rate can go when recovering the rate gap. In other words, it determines the minimum yield latency. We reduce the latency by increasing concurrency, therefore we can say that it puts an upper bound on concurrency.

If the rateGoal is 0 or negative the stream never yields a value. If the rateBuffer is 0 or negative we do not attempt to recover.

Specify when the Channel should stop.

An abstract type for specifying the configuration parameters of a Channel. Use Config -> Config modifier functions to modify the default configuration. See the individual modifier documentation for default values.

A magical value for the buffer size arrived at by running the smallest possible task and measuring the optimal value of the buffer for that. This is obviously dependent on hardware, this figure is based on a 2.2GHz intel core-i7 processor.

The fields prefixed by an _ are not to be accessed or updated directly but via smart accessor APIs. Use get/set routines instead of directly accessing the Config fields

Specify the maximum number of threads that can be spawned by the channel. A value of 0 resets the thread limit to default, a negative value means there is no limit. The default value is 1500.

When the actions in a stream are IO bound, having blocking IO calls, this option can be used to control the maximum number of in-flight IO requests. When the actions are CPU bound this option can be used to control the amount of CPU used by the stream.

Specify the maximum size of the buffer for storing the results from concurrent computations. If the buffer becomes full we stop spawning more concurrent tasks until there is space in the buffer. A value of 0 resets the buffer size to default, a negative value means there is no limit. The default value is 1500.

CAUTION! using an unbounded maxBuffer value (i.e. a negative value) coupled with an unbounded maxThreads value is a recipe for disaster in presence of infinite streams, or very large streams. Especially, it must not be used when pure is used in ZipAsyncM streams as pure in applicative zip streams generates an infinite stream causing unbounded concurrent generation with no limit on the buffer or threads.

The maximum number of yields that this channel would produce. The Channel automatically stops after that. This could be used to limit the speculative execution beyond the limit.

Nothing means there is no limit.

Keep in mind that checking this limit all the time has a performance overhead.

Known Bugs: currently this works only when rate is specified. Known Bugs: for ordered streams sometimes the actual count is less than expected.

Print debug information about the Channel when the stream ends. When the stream does not end normally, the channel debug information is printed when the channel is garbage collected. If you are expecting but not seeing the debug info try adding a performMajorGC before the program ends.

By default, processing of output from the worker threads is given priority over dispatching new workers. More workers are dispatched only when there is no output to process. When eager is set to True, workers are dispatched aggresively as long as there is more work to do irrespective of whether there is output pending to be processed by the stream consumer. However, dispatching may stop if maxThreads or maxBuffer is reached.

Note: This option has no effect when rate has been specified.

Note: Not supported with interleaved.

Specify when the Channel should stop.

When enabled the streams may be evaluated cocnurrently but the results are produced in the same sequence as a serial evaluation would produce.

Note: Not supported with interleaved.

Interleave the streams fairly instead of prioritizing the left stream. This schedules all streams in a round robin fashion over limited number of threads.

Note: Can only be used on finite number of streams.

Note: Not supported with ordered.

Spawn bound threads (i.e., spawn threads using forkOS instead of forkIO). The default value is False.

Currently, this only takes effect only for concurrent folds.

Specify the stream evaluation rate of a channel.

A Nothing value means there is no smart rate control, concurrent execution blocks only if maxThreads or maxBuffer is reached, or there are no more concurrent tasks to execute. This is the default.

When rate (throughput) is specified, concurrent production may be ramped up or down automatically to achieve the specified stream throughput. The specific behavior for different styles of Rate specifications is documented under Rate. The effective maximum production rate achieved by a channel is governed by:

• The maxThreads limit
• The maxBuffer limit
• The maximum rate that the stream producer can achieve
• The maximum rate that the stream consumer can achieve

Maximum production rate is given by:

\(rate = \frac{maxThreads}{latency}\)

If we know the average latency of the tasks we can set maxThreads accordingly.

Same as rate (Just $ Rate (r/2) r (2*r) maxBound)

Specifies the average production rate of a stream in number of yields per second (i.e. Hertz). Concurrent production is ramped up or down automatically to achieve the specified average yield rate. The rate can go down to half of the specified rate on the lower side and double of the specified rate on the higher side.

Same as rate (Just $ Rate r r (2*r) maxBound)

Specifies the minimum rate at which the stream should yield values. As far as possible the yield rate would never be allowed to go below the specified rate, even though it may possibly go above it at times, the upper limit is double of the specified rate.

Same as rate (Just $ Rate (r/2) r r maxBound)

Specifies the maximum rate at which the stream should yield values. As far as possible the yield rate would never be allowed to go above the specified rate, even though it may possibly go below it at times, the lower limit is half of the specified rate. This can be useful in applications where certain resource usage must not be allowed to go beyond certain limits.

Same as rate (Just $ Rate r r r 0)

Specifies a constant yield rate. If for some reason the actual rate goes above or below the specified rate we do not try to recover it by increasing or decreasing the rate in future. This can be useful in applications like graphics frame refresh where we need to maintain a constant refresh rate.

Never called from a worker thread.

MVar diagnostics has some overhead - around 5% on AsyncT null benchmark, we can keep it on in production to debug problems quickly if and when they happen, but it may result in unexpected output when threads are left hanging until they are GCed because the consumer went away.

This is a magic number and it is overloaded, and used at several places to achieve batching:

1. If we have to sleep to slowdown this is the minimum period that we accumulate before we sleep. Also, workers do not stop until this much sleep time is accumulated.
3. Collected latencies are computed and transferred to measured latency after a minimum of this period.

Always moves workerPendingLatency to workerCollectedLatency:

• workerCollectedLatency always incremented by workerPendingLatency
• workerPendingLatency always reset to 0

Moves workerCollectedLatency to svarAllTimeLatency periodically, when the collected batch size hits a limit, or time limit is over, or latency changes beyond a limit. Updates done when the batch is collected:

• svarAllTimeLatency yield count updated
• workerMeasuredLatency set to (new+prev)/2
• workerPollingInterval set using max of new/prev worker latency
• workerCollectedLatency reset to 0

See also getWorkerLatency.

This is safe even if we are adding more threads concurrently because if a child thread is adding another thread then anyway workerThreads will not be empty.

Describes how to pace the work based on current measurement estimates. If the rate is higher than expected we may have to sleep for some time (BlockWait), or send just one worker with limited yield count (PartialWorker) or send more than one workers with max yield count of each limited to the total maximum target count.

Estimate how many workers and yield count (Work) is required to maintian the target yield rate of the channel.

This is used by the worker dispatcher to estimate how many workers to dispatch. It is also used periodically by the workers to decide whether to stop or continue working.

Using the channel worker latency and channel yield count stats from the current measurement interval, estimate how many workers are needed to maintain the target rate and compare that with current number of workers. Returns true if we have have more than required workers.

Update the local yield count of the worker and check if:

• the channel yield rate is beyond max limit
• worker's yield count is beyond max limit

Low level API to add an event on the channel's output queue. Atomically adds the event to the queue and rings the doorbell if needed to wakeup the consumer thread.

Add a ChildYield event to the channel's output queue.

This is a wrapper over sendEvent, it does a few more things:

• performs a buffer limit check, returns False if exceeded

When rate control is enabled and WorkerInfo is supplied::

• increments the worker yield count
• periodically pushes the worker latency stats to the channel
• performs a rate limit check, returns False if exceeded

Add a ChildStop event to the channel's output queue. When rate control is enabled, it pushes the worker latency stats to the channel.

Add a ChildStop event with exception to the channel's output queue.