implement rolling hyper-log-log algorithm

pgxn/neon/Makefile

@@ -6,6 +6,7 @@ OBJS = \
 	$(WIN32RES) \
 	extension_server.o \
 	file_cache.o \
+	hll.o \
 	libpagestore.o \
 	neon.o \
 	neon_utils.o \
@@ -22,7 +23,7 @@ SHLIB_LINK_INTERNAL = $(libpq)
 SHLIB_LINK = -lcurl
 
 EXTENSION = neon
-DATA = neon--1.0.sql neon--1.0--1.1.sql neon--1.1--1.2.sql neon--1.2--1.3.sql neon--1.3--1.2.sql neon--1.2--1.1.sql neon--1.1--1.0.sql
+DATA = neon--1.0.sql neon--1.0--1.1.sql neon--1.1--1.2.sql neon--1.2--1.3.sql neon--1.3--1.2.sql neon--1.2--1.1.sql neon--1.1--1.0.sql  neon--1.3--1.4.sql neon--1.4--1.3.sql
 PGFILEDESC = "neon - cloud storage for PostgreSQL"
 
 EXTRA_CLEAN = \

pgxn/neon/file_cache.c

@@ -26,7 +26,6 @@
 #include "miscadmin.h"
 #include "pagestore_client.h"
 #include "common/hashfn.h"
-#include "lib/hyperloglog.h"
 #include "pgstat.h"
 #include "postmaster/bgworker.h"
 #include RELFILEINFO_HDR
@@ -40,6 +39,8 @@
 #include "utils/dynahash.h"
 #include "utils/guc.h"
 
+#include "hll.h"
+
 /*
  * Local file cache is used to temporary store relations pages in local file system.
  * All blocks of all relations are stored inside one file and addressed using shared hash map.
@@ -62,7 +63,6 @@
 #define BLOCKS_PER_CHUNK	128 /* 1Mb chunk */
 #define MB					((uint64)1024*1024)
 
-#define HYPER_LOG_LOG_BIT_WIDTH   10
 #define SIZE_MB_TO_CHUNKS(size) ((uint32)((size) * MB / BLCKSZ / BLOCKS_PER_CHUNK))
 
 typedef struct FileCacheEntry
@@ -87,8 +87,7 @@ typedef struct FileCacheControl
 	uint64		writes;
 	dlist_head	lru;			/* double linked list for LRU replacement
 								 * algorithm */
-	hyperLogLogState wss_estimation; /* estimation of wroking set size */
-	uint8_t		hyperloglog_hashes[(1 << HYPER_LOG_LOG_BIT_WIDTH) + 1];
+	HyperLogLogState wss_estimation; /* estimation of working set size */
 } FileCacheControl;
 
 static HTAB *lfc_hash;
@@ -238,12 +237,7 @@ lfc_shmem_startup(void)
 		dlist_init(&lfc_ctl->lru);
 
 		/* Initialize hyper-log-log structure for estimating working set size */
-		initHyperLogLog(&lfc_ctl->wss_estimation, HYPER_LOG_LOG_BIT_WIDTH);
-
-		/* We need hashes in shared memory */
-		pfree(lfc_ctl->wss_estimation.hashesArr);
-		memset(lfc_ctl->hyperloglog_hashes, 0, sizeof lfc_ctl->hyperloglog_hashes);
-		lfc_ctl->wss_estimation.hashesArr = lfc_ctl->hyperloglog_hashes;
+		initSHLL(&lfc_ctl->wss_estimation);
 
 		/* Recreate file cache on restart */
 		fd = BasicOpenFile(lfc_path, O_RDWR | O_CREAT | O_TRUNC);
@@ -545,7 +539,7 @@ lfc_read(NRelFileInfo rinfo, ForkNumber forkNum, BlockNumber blkno,
 
 	/* Approximate working set */
 	tag.blockNum = blkno;
-	addHyperLogLog(&lfc_ctl->wss_estimation, hash_bytes((uint8_t const*)&tag, sizeof(tag)));
+	addSHLL(&lfc_ctl->wss_estimation, hash_bytes((uint8_t const*)&tag, sizeof(tag)));
 
 	if (entry == NULL || (entry->bitmap[chunk_offs >> 5] & (1 << (chunk_offs & 31))) == 0)
 	{
@@ -986,20 +980,38 @@ local_cache_pages(PG_FUNCTION_ARGS)
 		SRF_RETURN_DONE(funcctx);
 }
 
+PG_FUNCTION_INFO_V1(approximate_working_set_size_seconds);
+
+Datum
+approximate_working_set_size_seconds(PG_FUNCTION_ARGS)
+{
+	if (lfc_size_limit != 0)
+	{
+		int32 dc;
+		time_t duration = PG_ARGISNULL(0) ? (time_t)-1 : PG_GETARG_INT32(0);
+		LWLockAcquire(lfc_lock, LW_SHARED);
+		dc = (int32) estimateSHLL(&lfc_ctl->wss_estimation, duration);
+		LWLockRelease(lfc_lock);
+		PG_RETURN_INT32(dc);
+	}
+	PG_RETURN_NULL();
+}
+
 PG_FUNCTION_INFO_V1(approximate_working_set_size);
 
 Datum
 approximate_working_set_size(PG_FUNCTION_ARGS)
 {
-	int32 dc = -1;
 	if (lfc_size_limit != 0)
 	{
+		int32 dc;
 		bool reset = PG_GETARG_BOOL(0);
 		LWLockAcquire(lfc_lock, reset ? LW_EXCLUSIVE : LW_SHARED);
-		dc = (int32) estimateHyperLogLog(&lfc_ctl->wss_estimation);
+		dc = (int32) estimateSHLL(&lfc_ctl->wss_estimation, (time_t)-1);
 		if (reset)
-			memset(lfc_ctl->hyperloglog_hashes, 0, sizeof lfc_ctl->hyperloglog_hashes);
+			memset(lfc_ctl->wss_estimation.regs, 0, sizeof lfc_ctl->wss_estimation.regs);
 		LWLockRelease(lfc_lock);
+		PG_RETURN_INT32(dc);
 	}
-	PG_RETURN_INT32(dc);
+	PG_RETURN_NULL();
 }

pgxn/neon/hll.c

@@ -0,0 +1,193 @@
+/*-------------------------------------------------------------------------
+ *
+ * hll.c
+ *	  Sliding HyperLogLog cardinality estimator
+ *
+ * Portions Copyright (c) 2014-2023, PostgreSQL Global Development Group
+ *
+ * Implements https://hal.science/hal-00465313/document
+ * 
+ * Based on Hideaki Ohno's C++ implementation.  This is probably not ideally
+ * suited to estimating the cardinality of very large sets;  in particular, we
+ * have not attempted to further optimize the implementation as described in
+ * the Heule, Nunkesser and Hall paper "HyperLogLog in Practice: Algorithmic
+ * Engineering of a State of The Art Cardinality Estimation Algorithm".
+ *
+ * A sparse representation of HyperLogLog state is used, with fixed space
+ * overhead.
+ *
+ * The copyright terms of Ohno's original version (the MIT license) follow.
+ *
+ * IDENTIFICATION
+ *	  src/backend/lib/hyperloglog.c
+ *
+ *-------------------------------------------------------------------------
+ */
+
+/*
+ * Copyright (c) 2013 Hideaki Ohno <hide.o.j55{at}gmail.com>
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the 'Software'), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED 'AS IS', WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
+ * IN THE SOFTWARE.
+ */
+
+#include <math.h>
+
+#include "postgres.h"
+#include "funcapi.h"
+#include "port/pg_bitutils.h"
+#include "utils/timestamp.h"
+#include "hll.h"
+
+
+#define POW_2_32			(4294967296.0)
+#define NEG_POW_2_32		(-4294967296.0)
+
+#define ALPHA_MM ((0.7213 / (1.0 + 1.079 / HLL_N_REGISTERS)) * HLL_N_REGISTERS * HLL_N_REGISTERS)
+
+/*
+ * Worker for addHyperLogLog().
+ *
+ * Calculates the position of the first set bit in first b bits of x argument
+ * starting from the first, reading from most significant to least significant
+ * bits.
+ *
+ * Example (when considering fist 10 bits of x):
+ *
+ * rho(x = 0b1000000000)   returns 1
+ * rho(x = 0b0010000000)   returns 3
+ * rho(x = 0b0000000000)   returns b + 1
+ *
+ * "The binary address determined by the first b bits of x"
+ *
+ * Return value "j" used to index bit pattern to watch.
+ */
+static inline uint8
+rho(uint32 x, uint8 b)
+{
+	uint8		j = 1;
+
+	if (x == 0)
+		return b + 1;
+
+	j = 32 - pg_leftmost_one_pos32(x);
+
+	if (j > b)
+		return b + 1;
+
+	return j;
+}
+
+/*
+ * Initialize HyperLogLog track state
+ */
+void
+initSHLL(HyperLogLogState *cState)
+{
+	memset(cState->regs, 0, sizeof(cState->regs));
+}
+
+/*
+ * Adds element to the estimator, from caller-supplied hash.
+ *
+ * It is critical that the hash value passed be an actual hash value, typically
+ * generated using hash_any().  The algorithm relies on a specific bit-pattern
+ * observable in conjunction with stochastic averaging.  There must be a
+ * uniform distribution of bits in hash values for each distinct original value
+ * observed.
+ */
+void
+addSHLL(HyperLogLogState *cState, uint32 hash)
+{
+	uint8		count;
+	uint32		index;
+	size_t		i;
+	size_t		j;
+
+	TimestampTz	now = GetCurrentTimestamp();
+	/* Use the first "k" (registerWidth) bits as a zero based index */
+	index = hash >> HLL_C_BITS;
+
+	/* Compute the rank of the remaining 32 - "k" (registerWidth) bits */
+	count = rho(hash << HLL_BIT_WIDTH, HLL_C_BITS);
+
+	cState->regs[index][count] = now;
+}
+
+static uint8
+getMaximum(const TimestampTz* reg, TimestampTz since)
+{
+	uint8 max = 0;
+
+	for (size_t i = 0; i < HLL_C_BITS + 1; i++)
+	{
+		if (reg[i] >= since)
+		{
+			max = i;
+		}
+	}
+
+	return max;
+}
+
+
+/*
+ * Estimates cardinality, based on elements added so far
+ */
+double
+estimateSHLL(HyperLogLogState *cState, time_t duration)
+{
+	double		result;
+	double		sum = 0.0;
+	size_t		i;
+	uint8       R[HLL_N_REGISTERS];
+	/* 0 indicates uninitialized timestamp, so if we need to cover the whole range than starts with 1 */
+	TimestampTz since = duration == (time_t)-1 ? 1 : GetCurrentTimestamp() - duration * USECS_PER_SEC;
+
+	for (i = 0; i < HLL_N_REGISTERS; i++)
+	{
+		R[i] = getMaximum(cState->regs[i], since);
+		sum += 1.0 / pow(2.0, R[i]);
+	}
+
+	/* result set to "raw" HyperLogLog estimate (E in the HyperLogLog paper) */
+	result = ALPHA_MM / sum;
+
+	if (result <= (5.0 / 2.0) * HLL_N_REGISTERS)
+	{
+		/* Small range correction */
+		int			zero_count = 0;
+
+		for (i = 0; i < HLL_N_REGISTERS; i++)
+		{
+			zero_count += R[i] == 0;
+		}
+
+		if (zero_count != 0)
+			result = HLL_N_REGISTERS * log((double) HLL_N_REGISTERS /
+										   zero_count);
+	}
+	else if (result > (1.0 / 30.0) * POW_2_32)
+	{
+		/* Large range correction */
+		result = NEG_POW_2_32 * log(1.0 - (result / POW_2_32));
+	}
+
+	return result;
+}
+

pgxn/neon/hll.h

@@ -0,0 +1,86 @@
+/*-------------------------------------------------------------------------
+ *
+ * hll.h
+ *	  Sliding HyperLogLog cardinality estimator
+ *
+ * Portions Copyright (c) 2014-2023, PostgreSQL Global Development Group
+ *
+ * Implements https://hal.science/hal-00465313/document
+ * 
+ * Based on Hideaki Ohno's C++ implementation.  This is probably not ideally
+ * suited to estimating the cardinality of very large sets;  in particular, we
+ * have not attempted to further optimize the implementation as described in
+ * the Heule, Nunkesser and Hall paper "HyperLogLog in Practice: Algorithmic
+ * Engineering of a State of The Art Cardinality Estimation Algorithm".
+ *
+ * A sparse representation of HyperLogLog state is used, with fixed space
+ * overhead.
+ *
+ * The copyright terms of Ohno's original version (the MIT license) follow.
+ *
+ * IDENTIFICATION
+ *	  src/backend/lib/hyperloglog.c
+ *
+ *-------------------------------------------------------------------------
+ */
+
+/*
+ * Copyright (c) 2013 Hideaki Ohno <hide.o.j55{at}gmail.com>
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the 'Software'), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED 'AS IS', WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
+ * IN THE SOFTWARE.
+ */
+
+#ifndef HLL_H
+#define HLL_H
+
+#define HLL_BIT_WIDTH   10
+#define HLL_C_BITS      (32 - HLL_BIT_WIDTH)
+#define HLL_N_REGISTERS (1 << HLL_BIT_WIDTH)
+
+/*
+ * HyperLogLog is an approximate technique for computing the number of distinct
+ * entries in a set.  Importantly, it does this by using a fixed amount of
+ * memory.  See the 2007 paper "HyperLogLog: the analysis of a near-optimal
+ * cardinality estimation algorithm" for more.
+ *
+ * Instead of a single counter for every bits register, we have a timestamp
+ * for every valid number of bits we can encounter. Every time we encounter
+ * a certain number of bits, we update the timestamp in those registers to
+ * the current timestamp.
+ *
+ * We can query the sketch's stored cardinality for the range of some timestamp
+ * up to now: For each register, we return the highest bits bucket that has a
+ * modified timestamp >= the query timestamp. This value is the number of bits
+ * for this register in the normal HLL calculation.
+ *
+ * The memory usage is 2^B * (C + 1) * sizeof(TimetampTz), or 184kiB.
+ * Usage could be halved if we decide to reduce the required time dimension
+ * precision; as 32 bits in second precision should be enough for statistics.
+ * However, that is not yet implemented.
+ */
+typedef struct HyperLogLogState
+{
+	TimestampTz regs[HLL_N_REGISTERS][HLL_C_BITS + 1];
+} HyperLogLogState;
+
+extern void   initSHLL(HyperLogLogState *cState);
+extern void   addSHLL(HyperLogLogState *cState, uint32 hash);
+extern double estimateSHLL(HyperLogLogState *cState, time_t dutration);
+
+#endif