mukund-thakur commented on a change in pull request #2069: URL: https://github.com/apache/hadoop/pull/2069#discussion_r450905137
########## File path: hadoop-common-project/hadoop-common/src/site/markdown/filesystem/iostatistics.md ########## @@ -0,0 +1,432 @@ +<!--- + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. See accompanying LICENSE file. +--> + +# Statistic collection with the IOStatistics API + +```java +@InterfaceAudience.Public +@InterfaceStability.Unstable +``` + +The `IOStatistics` API is intended to provide statistics on individual IO +classes -such as input and output streams, *in a standard way which +applications can query* + +Many filesystem-related classes have implemented statistics gathering +and provided private/unstable ways to query this, but as they were +not common across implementations it was unsafe for applications +to reference these values. Example: `S3AInputStream` and its statistics +API. This is used in internal tests, but cannot be used downstream in +applications such as Apache Hive or Apache HBase. + +The IOStatistics API is intended to + +1. Be instance specific:, rather than shared across multiple instances + of a class, or thread local. +1. Be public and stable enough to be used by applications. +1. Be easy to use in applications written in Java, Scala, and, via libhdfs, C/C++ +1. Have foundational interfaces and classes in the `hadoop-common` JAR. + +## Core Model + +Any class *may* implement `IOStatisticsSource` in order to +provide statistics. + +Wrapper I/O Classes such as `FSDataInputStream` anc `FSDataOutputStream` *should* +implement the interface and forward it to the wrapped class, if they also +implement it -and return `null` if they do not. + +`IOStatisticsSource` implementations `getIOStatistics()` return an +instance of `IOStatistics` enumerating the statistics of that specific +instance. + +The `IOStatistics` Interface exports five kinds of statistic: + + +| Category | Type | Description | +|------|------|-------------| +| `counter` | `long` | a counter which may increase in value; SHOULD BE >= 0 | +| `gauge` | `long` | an arbitrary value which can down as well as up; SHOULD BE >= 0| +| `minimum` | `long` | an minimum value; MAY BE negative | +| `maximum` | `long` | a maximum value; MAY BE negative | +| `meanStatistic` | `MeanStatistic` | an arithmetic mean and sample size; mean MAY BE negative| + +Four are simple `long` values, with the variations how they are likely to +change and how they are aggregated. + + +#### Aggregation of Statistic Values + +For the different statistic category, the result of `aggregate(x, y)` is + +| Category | Aggregation | +|------------------|-------------| +| `counter` | `min(0, x) + min(0, y)` | +| `gauge` | `min(0, x) + min(0, y)` | +| `minimum` | `min(x, y)` | +| `maximum` | `max(x, y)` | +| `meanStatistic` | calculation of the mean of `x` and `y` ) | + + +#### Class `MeanStatistic` + +## package `org.apache.hadoop.fs.statistics` + +This package contains the public statistics APIs intended +for use by applications. + +<!-- ============================================================= --> +<!-- Class: MeanStatistic --> +<!-- ============================================================= --> + +`MeanStatistic` is a tuple of `(mean, samples)` to support aggregation. + +A `MeanStatistic` with a sample of `0` is considered an empty statistic. + +All `MeanStatistic` instances where `sample = 0` are considered equal, +irrespective of the `mean` value. + +Algorithm to calculate the mean : + +```python +if x.samples = 0: + y +else if y.samples = 0 : + x +else: + samples' = x.samples + y.samples + mean' = (x.mean * x.samples) + (y.mean * y.samples) / samples' + (samples', mean') +``` + +Implicitly, this means that if both samples are empty, then the aggregate value is also empty. + +```java +public final class MeanStatistic implements Serializable, Cloneable { + /** + * Arithmetic mean. + */ + private double mean; + + /** + * Number of samples used to calculate + * the mean. + */ + private long samples; + + /** + * Get the mean value. + * @return the mean + */ + public double getMean() { + return mean; + } + + /** + * Get the sample count. + * @return the sample count; 0 means empty + */ + public long getSamples() { + return samples; + } + + /** + * Is a statistic empty? + * @return true if the sample count is 0 + */ + public boolean isEmpty() { + return samples == 0; + } + /** + * Add another mean statistic to create a new statistic. + * When adding two statistics, if either is empty then + * a copy of the non-empty statistic is returned. + * If both are empty then a new empty statistic is returned. + * + * @param other other value + * @return the aggregate mean + */ + public MeanStatistic add(final MeanStatistic other) { + /* Implementation elided. */ + } + @Override + public int hashCode() { + return Objects.hash(mean, samples); + } + + @Override + public boolean equals(final Object o) { + if (this == o) { return true; } + if (o == null || getClass() != o.getClass()) { return false; } + MeanStatistic that = (MeanStatistic) o; + if (this.isEmpty()) { + return that.isEmpty(); + } + return Double.compare(that.mean, mean) == 0 && + samples == that.samples; + } + + @Override + public MeanStatistic clone() { + return new MeanStatistic(this); + } + + public MeanStatistic copy() { + return new MeanStatistic(this); + } + +} +``` + +<!-- ============================================================= --> +<!-- Interface: IOStatisticsSource --> +<!-- ============================================================= --> + +### class `org.apache.hadoop.fs.statistics.IOStatisticsSource` + +```java + +/** + * A source of IO statistics. + * These statistics MUST be instance specific, not thread local. + */ +@InterfaceStability.Unstable +public interface IOStatisticsSource { + + /** + * Return a statistics instance. + * It is not a requirement that the same instance is returned every time. + * {@link IOStatisticsSource}. + * If the object implementing this is Closeable, this method + * may return null if invoked on a closed object, even if + * it returns a valid instance when called earlier. + * @return an IOStatistics instance or null + */ + IOStatistics getIOStatistics(); +} +``` + +This is the interface which an object instance MUST implement if they are a source of +IOStatistics information. + +#### Invariants + +The result of `getIOStatistics()` must be one of + +* `null` +* an immutable `IOStatistics` for which each map of entries is +an empty map. +* an instance of an `IOStatistics` whose statistics MUST BE unique to that +instance of the class implementing `IOStatisticsSource`. + +Less formally: if the statistics maps returned are non-empty, all the statistics +must be collected from the current instance, and not from any other instances, the way +some of the `FileSystem` statistics are collected. + + +The result of `getIOStatistics()`, if non-null, MAY be a different instance +on every invocation. + + +<!-- ============================================================= --> +<!-- Interface: IOStatistics --> +<!-- ============================================================= --> + +### class `org.apache.hadoop.fs.statistics.IOStatistics` + +These are per-instance statistics provided by an object which +implements `IOStatisticsSource`. + +```java +@InterfaceAudience.Public +@InterfaceStability.Unstable +public interface IOStatistics { + + /** + * Map of counters. + * @return the current map of counters. + */ + Map<String, Long> counters(); + + /** + * Map of gauges. + * @return the current map of gauges. + */ + Map<String, Long> gauges(); + + /** + * Map of minumums. + * @return the current map of minumums. + */ + Map<String, Long> minumums(); + + /** + * Map of maximums. + * @return the current map of maximums. + */ + Map<String, Long> maximums(); + + /** + * Map of meanStatistics. + * @return the current map of MeanStatistic statistics. + */ + Map<String, MeanStatistic> meanStatistics(); + +} +``` + +### Statistic Naming + +The naming policy of statistics is designed to be readable, shareable +and ideally consistent across `IOStatisticSource` implementations. + +* Characters in key names MUST match the regular expression + `[a-z|0-9|_]` with the exception of the first character, which + MUST be in the range `[a-z]`. Thus the full regular expression + for a valid statistic name is: + + [a-z][a-z|0-9|_]+ + +* Where possible, the names of statistics SHOULD be those defined + with common names. + + org.apache.hadoop.fs.statistics.StreamStatisticNames + org.apache.hadoop.fs.statistics.StoreStatisticNames + + Note 1.: these are evolving; for clients to safely reference their + statistics by name they SHOULD be copied to the application. + (i.e. for an application compiled hadoop 3.4.2 to link against hadoop 3.4.1, + copy the strings). + + Note 2: keys defined in these classes SHALL NOT be removed + from subsequent Hadoop releases. + +* A common statistic name MUST NOT be used to report any other statistic and + MUST use the pre-defined unit of measurement. + +* A statistic name in one of the maps SHOULD NOT be re-used in another map. + This aids diagnostics of logged statistics. + +### Statistic Maps + +For each map of statistics returned: + +* The operations to add/remove entries are unsupported: the map returned + It MAY be mutable by the source of statistics. + +* The map MAY be emoty. 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