netcdf-c/libdispatch/nchashmap.c

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/*
Copyright (c) 1998-2018 University Corporation for Atmospheric Research/Unidata
See LICENSE.txt for license information.
*/
#include "config.h"
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#include <stdio.h>
#include <stdlib.h>
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#include <string.h>
#include <assert.h>
#ifdef HAVE_STDINT_H
#include <stdint.h>
#endif
Provide byte-range reading of remote datasets re: issue https://github.com/Unidata/netcdf-c/issues/1251 Assume that you have the URL to a remote dataset which is a normal netcdf-3 or netcdf-4 file. This PR allows the netcdf-c to read that dataset's contents as a netcdf file using HTTP byte ranges if the remote server supports byte-range access. Originally, this PR was set up to access Amazon S3 objects, but it can also access other remote datasets such as those provided by a Thredds server via the HTTPServer access protocol. It may also work for other kinds of servers. Note that this is not intended as a true production capability because, as is known, this kind of access to can be quite slow. In addition, the byte-range IO drivers do not currently do any sort of optimization or caching. An additional goal here is to gain some experience with the Amazon S3 REST protocol. This architecture and its use documented in the file docs/byterange.dox. There are currently two test cases: 1. nc_test/tst_s3raw.c - this does a simple open, check format, close cycle for a remote netcdf-3 file and a remote netcdf-4 file. 2. nc_test/test_s3raw.sh - this uses ncdump to investigate some remote datasets. This PR also incorporates significantly changed model inference code (see the superceded PR https://github.com/Unidata/netcdf-c/pull/1259). 1. It centralizes the code that infers the dispatcher. 2. It adds support for byte-range URLs Other changes: 1. NC_HDF5_finalize was not being properly called by nc_finalize(). 2. Fix minor bug in ncgen3.l 3. fix memory leak in nc4info.c 4. add code to walk the .daprc triples and to replace protocol= fragment tag with a more general mode= tag. Final Note: Th inference code is still way too complicated. We need to move to the validfile() model used by netcdf Java, where each dispatcher is asked if it can process the file. This decentralizes the inference code. This will be done after all the major new dispatchers (PIO, Zarr, etc) have been implemented.
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#include "ncdispatch.h"
#include "nccrc.h"
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#include "nchashmap.h"
#include "nc3internal.h"
#undef DEBUG
#undef DEBUGTRACE
#undef ASSERTIONS
/**
@Internal
This hashmap is optimized to use counted strings as its
key value. It is assumed in most cases that a string plus its
length are passed in for doing lookups.
When an entry is added, a copy of the string is kept in the hash table
entry. Since we also keep the hashkey, the probability is high that
we will only do string comparisons when they will match.
*/
#undef SMALLTABLE
#ifdef ASSERTIONS
#define ASSERT(x) assert(x)
#else
#define ASSERT(x)
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#endif
#ifdef DEBUGTRACE
Provide byte-range reading of remote datasets re: issue https://github.com/Unidata/netcdf-c/issues/1251 Assume that you have the URL to a remote dataset which is a normal netcdf-3 or netcdf-4 file. This PR allows the netcdf-c to read that dataset's contents as a netcdf file using HTTP byte ranges if the remote server supports byte-range access. Originally, this PR was set up to access Amazon S3 objects, but it can also access other remote datasets such as those provided by a Thredds server via the HTTPServer access protocol. It may also work for other kinds of servers. Note that this is not intended as a true production capability because, as is known, this kind of access to can be quite slow. In addition, the byte-range IO drivers do not currently do any sort of optimization or caching. An additional goal here is to gain some experience with the Amazon S3 REST protocol. This architecture and its use documented in the file docs/byterange.dox. There are currently two test cases: 1. nc_test/tst_s3raw.c - this does a simple open, check format, close cycle for a remote netcdf-3 file and a remote netcdf-4 file. 2. nc_test/test_s3raw.sh - this uses ncdump to investigate some remote datasets. This PR also incorporates significantly changed model inference code (see the superceded PR https://github.com/Unidata/netcdf-c/pull/1259). 1. It centralizes the code that infers the dispatcher. 2. It adds support for byte-range URLs Other changes: 1. NC_HDF5_finalize was not being properly called by nc_finalize(). 2. Fix minor bug in ncgen3.l 3. fix memory leak in nc4info.c 4. add code to walk the .daprc triples and to replace protocol= fragment tag with a more general mode= tag. Final Note: Th inference code is still way too complicated. We need to move to the validfile() model used by netcdf Java, where each dispatcher is asked if it can process the file. This decentralizes the inference code. This will be done after all the major new dispatchers (PIO, Zarr, etc) have been implemented.
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#define Trace(x) {fprintf(stderr,"NC_hashmap: %s\n",x); fflush(stderr);}
#else
Provide byte-range reading of remote datasets re: issue https://github.com/Unidata/netcdf-c/issues/1251 Assume that you have the URL to a remote dataset which is a normal netcdf-3 or netcdf-4 file. This PR allows the netcdf-c to read that dataset's contents as a netcdf file using HTTP byte ranges if the remote server supports byte-range access. Originally, this PR was set up to access Amazon S3 objects, but it can also access other remote datasets such as those provided by a Thredds server via the HTTPServer access protocol. It may also work for other kinds of servers. Note that this is not intended as a true production capability because, as is known, this kind of access to can be quite slow. In addition, the byte-range IO drivers do not currently do any sort of optimization or caching. An additional goal here is to gain some experience with the Amazon S3 REST protocol. This architecture and its use documented in the file docs/byterange.dox. There are currently two test cases: 1. nc_test/tst_s3raw.c - this does a simple open, check format, close cycle for a remote netcdf-3 file and a remote netcdf-4 file. 2. nc_test/test_s3raw.sh - this uses ncdump to investigate some remote datasets. This PR also incorporates significantly changed model inference code (see the superceded PR https://github.com/Unidata/netcdf-c/pull/1259). 1. It centralizes the code that infers the dispatcher. 2. It adds support for byte-range URLs Other changes: 1. NC_HDF5_finalize was not being properly called by nc_finalize(). 2. Fix minor bug in ncgen3.l 3. fix memory leak in nc4info.c 4. add code to walk the .daprc triples and to replace protocol= fragment tag with a more general mode= tag. Final Note: Th inference code is still way too complicated. We need to move to the validfile() model used by netcdf Java, where each dispatcher is asked if it can process the file. This decentralizes the inference code. This will be done after all the major new dispatchers (PIO, Zarr, etc) have been implemented.
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#define Trace(x)
#endif
#define SEED 37
/* See lookup3.c */
extern nchashkey_t hash_fast(const char*, size_t length);
/* this should be prime */
#ifdef SMALLTABLE
#define MINTABLESIZE 7U
#else
#define MINTABLESIZE 131U
#endif
/* Flags must be powers of 2 */
/* Slot has data */
#define ACTIVE 1
/* Slot had its value deleted */
#define DELETED 2
/* Slot is unused */
#define EMPTY 0
#define MAX(a,b) ((a) > (b) ? (a) : (b))
/* Forward */
static const unsigned int NC_nprimes;
static const unsigned int NC_primes[16386];
static unsigned int findPrimeGreaterThan(size_t val);
extern void printhashmapstats(NC_hashmap* hm);
extern void printhashmap(NC_hashmap* hm);
static int
rehash(NC_hashmap* hm)
{
size_t alloc = hm->alloc;
#ifdef ASSERTIONS
size_t active = hm->active;
#endif
NC_hentry* oldtable = hm->table;
Provide byte-range reading of remote datasets re: issue https://github.com/Unidata/netcdf-c/issues/1251 Assume that you have the URL to a remote dataset which is a normal netcdf-3 or netcdf-4 file. This PR allows the netcdf-c to read that dataset's contents as a netcdf file using HTTP byte ranges if the remote server supports byte-range access. Originally, this PR was set up to access Amazon S3 objects, but it can also access other remote datasets such as those provided by a Thredds server via the HTTPServer access protocol. It may also work for other kinds of servers. Note that this is not intended as a true production capability because, as is known, this kind of access to can be quite slow. In addition, the byte-range IO drivers do not currently do any sort of optimization or caching. An additional goal here is to gain some experience with the Amazon S3 REST protocol. This architecture and its use documented in the file docs/byterange.dox. There are currently two test cases: 1. nc_test/tst_s3raw.c - this does a simple open, check format, close cycle for a remote netcdf-3 file and a remote netcdf-4 file. 2. nc_test/test_s3raw.sh - this uses ncdump to investigate some remote datasets. This PR also incorporates significantly changed model inference code (see the superceded PR https://github.com/Unidata/netcdf-c/pull/1259). 1. It centralizes the code that infers the dispatcher. 2. It adds support for byte-range URLs Other changes: 1. NC_HDF5_finalize was not being properly called by nc_finalize(). 2. Fix minor bug in ncgen3.l 3. fix memory leak in nc4info.c 4. add code to walk the .daprc triples and to replace protocol= fragment tag with a more general mode= tag. Final Note: Th inference code is still way too complicated. We need to move to the validfile() model used by netcdf Java, where each dispatcher is asked if it can process the file. This decentralizes the inference code. This will be done after all the major new dispatchers (PIO, Zarr, etc) have been implemented.
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Trace("rehash");
hm->alloc = findPrimeGreaterThan(alloc<<1);
if(hm->alloc == 0) return 0;
hm->table = (NC_hentry*)calloc(sizeof(NC_hentry), hm->alloc);
hm->active = 0;
while(alloc > 0) {
NC_hentry* h = &oldtable[--alloc];
if(h->flags == ACTIVE) {
NC_hashmapadd(hm, h->data, h->key, h->keysize);
if(h->key) free(h->key);
}
}
free(oldtable);
ASSERT(active == hm->active);
return 1;
}
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/* Locate where given object is or should be placed in indexp.
if fail to find spot return 0 else 1.
If deletok then a deleted slot is ok to return;
return invariant: return == 0 || *indexp is defined
*/
static int
locate(NC_hashmap* hash, nchashkey_t hashkey, const char* key, size_t keysize, size_t* indexp, int deletedok)
{
size_t i;
size_t index;
size_t step = 1; /* simple linear probe */
int deletefound = 0;
size_t deletedindex = 0; /* first deleted entry encountered */
NC_hentry* entry;
Provide byte-range reading of remote datasets re: issue https://github.com/Unidata/netcdf-c/issues/1251 Assume that you have the URL to a remote dataset which is a normal netcdf-3 or netcdf-4 file. This PR allows the netcdf-c to read that dataset's contents as a netcdf file using HTTP byte ranges if the remote server supports byte-range access. Originally, this PR was set up to access Amazon S3 objects, but it can also access other remote datasets such as those provided by a Thredds server via the HTTPServer access protocol. It may also work for other kinds of servers. Note that this is not intended as a true production capability because, as is known, this kind of access to can be quite slow. In addition, the byte-range IO drivers do not currently do any sort of optimization or caching. An additional goal here is to gain some experience with the Amazon S3 REST protocol. This architecture and its use documented in the file docs/byterange.dox. There are currently two test cases: 1. nc_test/tst_s3raw.c - this does a simple open, check format, close cycle for a remote netcdf-3 file and a remote netcdf-4 file. 2. nc_test/test_s3raw.sh - this uses ncdump to investigate some remote datasets. This PR also incorporates significantly changed model inference code (see the superceded PR https://github.com/Unidata/netcdf-c/pull/1259). 1. It centralizes the code that infers the dispatcher. 2. It adds support for byte-range URLs Other changes: 1. NC_HDF5_finalize was not being properly called by nc_finalize(). 2. Fix minor bug in ncgen3.l 3. fix memory leak in nc4info.c 4. add code to walk the .daprc triples and to replace protocol= fragment tag with a more general mode= tag. Final Note: Th inference code is still way too complicated. We need to move to the validfile() model used by netcdf Java, where each dispatcher is asked if it can process the file. This decentralizes the inference code. This will be done after all the major new dispatchers (PIO, Zarr, etc) have been implemented.
2019-01-02 09:27:36 +08:00
Trace("locate");
/* Compute starting point */
assert(hash->alloc > 0);
index = (size_t)(hashkey % hash->alloc);
/* Search table using linear probing */
for (i = 0; i < hash->alloc; i++) {
entry = &hash->table[index];
if(entry->flags & ACTIVE) {
if(indexp) *indexp = index; /* assume a match */
if(entry->hashkey == hashkey && entry->keysize == keysize) {
/* Check content */
if(memcmp(entry->key,key,keysize)==0)
return 1;
}
/* Keep looking */
} else if(entry->flags & DELETED) {
if(!deletefound) {/* save this position */
deletefound = 1;
deletedindex = index;
}
/* Keep looking */
} else { /* Empty slot */
if(indexp) *indexp = index;
return 1;
}
/* linear probe */
assert(hash->alloc > 0);
index = (index + step) % hash->alloc;
}
if(deletedok && deletefound) {
if(indexp) *indexp = deletedindex;
return 1;
}
return 0;
}
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/* Return the hash key for specified key; takes key+size*/
/* Wrapper for crc64*/
nchashkey_t
NC_hashmapkey(const char* key, size_t size)
{
return NC_crc64(0,(void*)key,(unsigned int)size);
}
NC_hashmap*
NC_hashmapnew(size_t startsize)
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{
NC_hashmap* hm = NULL;
Provide byte-range reading of remote datasets re: issue https://github.com/Unidata/netcdf-c/issues/1251 Assume that you have the URL to a remote dataset which is a normal netcdf-3 or netcdf-4 file. This PR allows the netcdf-c to read that dataset's contents as a netcdf file using HTTP byte ranges if the remote server supports byte-range access. Originally, this PR was set up to access Amazon S3 objects, but it can also access other remote datasets such as those provided by a Thredds server via the HTTPServer access protocol. It may also work for other kinds of servers. Note that this is not intended as a true production capability because, as is known, this kind of access to can be quite slow. In addition, the byte-range IO drivers do not currently do any sort of optimization or caching. An additional goal here is to gain some experience with the Amazon S3 REST protocol. This architecture and its use documented in the file docs/byterange.dox. There are currently two test cases: 1. nc_test/tst_s3raw.c - this does a simple open, check format, close cycle for a remote netcdf-3 file and a remote netcdf-4 file. 2. nc_test/test_s3raw.sh - this uses ncdump to investigate some remote datasets. This PR also incorporates significantly changed model inference code (see the superceded PR https://github.com/Unidata/netcdf-c/pull/1259). 1. It centralizes the code that infers the dispatcher. 2. It adds support for byte-range URLs Other changes: 1. NC_HDF5_finalize was not being properly called by nc_finalize(). 2. Fix minor bug in ncgen3.l 3. fix memory leak in nc4info.c 4. add code to walk the .daprc triples and to replace protocol= fragment tag with a more general mode= tag. Final Note: Th inference code is still way too complicated. We need to move to the validfile() model used by netcdf Java, where each dispatcher is asked if it can process the file. This decentralizes the inference code. This will be done after all the major new dispatchers (PIO, Zarr, etc) have been implemented.
2019-01-02 09:27:36 +08:00
Trace("NC_hashmapnew");
hm = (NC_hashmap*)malloc(sizeof(NC_hashmap));
if(startsize == 0 || startsize < MINTABLESIZE)
startsize = MINTABLESIZE;
else {
startsize *= 4;
startsize /= 3;
startsize = findPrimeGreaterThan(startsize);
if(startsize == 0) {nullfree(hm); return 0;}
}
hm->table = (NC_hentry*)calloc(sizeof(NC_hentry), (size_t)startsize);
hm->alloc = startsize;
hm->active = 0;
return hm;
2010-06-03 21:24:43 +08:00
}
int
NC_hashmapadd(NC_hashmap* hash, uintptr_t data, const char* key, size_t keysize)
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{
NC_hentry* entry;
nchashkey_t hashkey;
Provide byte-range reading of remote datasets re: issue https://github.com/Unidata/netcdf-c/issues/1251 Assume that you have the URL to a remote dataset which is a normal netcdf-3 or netcdf-4 file. This PR allows the netcdf-c to read that dataset's contents as a netcdf file using HTTP byte ranges if the remote server supports byte-range access. Originally, this PR was set up to access Amazon S3 objects, but it can also access other remote datasets such as those provided by a Thredds server via the HTTPServer access protocol. It may also work for other kinds of servers. Note that this is not intended as a true production capability because, as is known, this kind of access to can be quite slow. In addition, the byte-range IO drivers do not currently do any sort of optimization or caching. An additional goal here is to gain some experience with the Amazon S3 REST protocol. This architecture and its use documented in the file docs/byterange.dox. There are currently two test cases: 1. nc_test/tst_s3raw.c - this does a simple open, check format, close cycle for a remote netcdf-3 file and a remote netcdf-4 file. 2. nc_test/test_s3raw.sh - this uses ncdump to investigate some remote datasets. This PR also incorporates significantly changed model inference code (see the superceded PR https://github.com/Unidata/netcdf-c/pull/1259). 1. It centralizes the code that infers the dispatcher. 2. It adds support for byte-range URLs Other changes: 1. NC_HDF5_finalize was not being properly called by nc_finalize(). 2. Fix minor bug in ncgen3.l 3. fix memory leak in nc4info.c 4. add code to walk the .daprc triples and to replace protocol= fragment tag with a more general mode= tag. Final Note: Th inference code is still way too complicated. We need to move to the validfile() model used by netcdf Java, where each dispatcher is asked if it can process the file. This decentralizes the inference code. This will be done after all the major new dispatchers (PIO, Zarr, etc) have been implemented.
2019-01-02 09:27:36 +08:00
Trace("NC_hashmapadd");
if(key == NULL || keysize == 0)
return 0;
hashkey = NC_hashmapkey(key,keysize);
if((hash->alloc*3)/4 <= hash->active)
{if(!rehash(hash)) return 0;}
for(;;) {
size_t index;
if(!locate(hash,hashkey,key,keysize,&index,1)) {
if(!rehash(hash)) return 0;
continue; /* try on larger table */
}
entry = &hash->table[index];
if(entry->flags & ACTIVE) {
/* key already exists in table => overwrite data */
entry->data = data;
return 1;
} else { /* !ACTIVE || DELETED */
entry->flags = ACTIVE;
entry->data = data;
entry->hashkey = hashkey;
entry->keysize = keysize;
entry->key = malloc(keysize+1);
if(entry->key == NULL)
return 0;
memcpy(entry->key,key,keysize);
entry->key[keysize] = '\0'; /* ensure null terminated */
++hash->active;
return 1;
}
}
return 0;
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}
int
NC_hashmapremove(NC_hashmap* hash, const char* key, size_t keysize, uintptr_t* datap)
2010-06-03 21:24:43 +08:00
{
nchashkey_t hashkey;
size_t index;
NC_hentry* h;
Provide byte-range reading of remote datasets re: issue https://github.com/Unidata/netcdf-c/issues/1251 Assume that you have the URL to a remote dataset which is a normal netcdf-3 or netcdf-4 file. This PR allows the netcdf-c to read that dataset's contents as a netcdf file using HTTP byte ranges if the remote server supports byte-range access. Originally, this PR was set up to access Amazon S3 objects, but it can also access other remote datasets such as those provided by a Thredds server via the HTTPServer access protocol. It may also work for other kinds of servers. Note that this is not intended as a true production capability because, as is known, this kind of access to can be quite slow. In addition, the byte-range IO drivers do not currently do any sort of optimization or caching. An additional goal here is to gain some experience with the Amazon S3 REST protocol. This architecture and its use documented in the file docs/byterange.dox. There are currently two test cases: 1. nc_test/tst_s3raw.c - this does a simple open, check format, close cycle for a remote netcdf-3 file and a remote netcdf-4 file. 2. nc_test/test_s3raw.sh - this uses ncdump to investigate some remote datasets. This PR also incorporates significantly changed model inference code (see the superceded PR https://github.com/Unidata/netcdf-c/pull/1259). 1. It centralizes the code that infers the dispatcher. 2. It adds support for byte-range URLs Other changes: 1. NC_HDF5_finalize was not being properly called by nc_finalize(). 2. Fix minor bug in ncgen3.l 3. fix memory leak in nc4info.c 4. add code to walk the .daprc triples and to replace protocol= fragment tag with a more general mode= tag. Final Note: Th inference code is still way too complicated. We need to move to the validfile() model used by netcdf Java, where each dispatcher is asked if it can process the file. This decentralizes the inference code. This will be done after all the major new dispatchers (PIO, Zarr, etc) have been implemented.
2019-01-02 09:27:36 +08:00
Trace("NC_hashmapremove");
if(key == NULL || keysize == 0)
return 0;
hashkey = NC_hashmapkey(key,keysize);
if(!locate(hash,hashkey,key,keysize,&index,0))
return 0; /* not present */
h = &hash->table[index];
if(h->flags & ACTIVE) { /* matching entry found */
h->flags = DELETED; /* also turn off ACTIVE */
if(h->key) free(h->key);
h->key = NULL;
h->keysize = 0;
--hash->active;
if(datap) *datap = h->data;
return 1;
} else /* !ACTIVE && !DELETED => not in table*/
return 0;
2010-06-03 21:24:43 +08:00
}
int
NC_hashmapget(NC_hashmap* hash, const char* key, size_t keysize, uintptr_t* datap)
2010-06-03 21:24:43 +08:00
{
nchashkey_t hashkey;
Provide byte-range reading of remote datasets re: issue https://github.com/Unidata/netcdf-c/issues/1251 Assume that you have the URL to a remote dataset which is a normal netcdf-3 or netcdf-4 file. This PR allows the netcdf-c to read that dataset's contents as a netcdf file using HTTP byte ranges if the remote server supports byte-range access. Originally, this PR was set up to access Amazon S3 objects, but it can also access other remote datasets such as those provided by a Thredds server via the HTTPServer access protocol. It may also work for other kinds of servers. Note that this is not intended as a true production capability because, as is known, this kind of access to can be quite slow. In addition, the byte-range IO drivers do not currently do any sort of optimization or caching. An additional goal here is to gain some experience with the Amazon S3 REST protocol. This architecture and its use documented in the file docs/byterange.dox. There are currently two test cases: 1. nc_test/tst_s3raw.c - this does a simple open, check format, close cycle for a remote netcdf-3 file and a remote netcdf-4 file. 2. nc_test/test_s3raw.sh - this uses ncdump to investigate some remote datasets. This PR also incorporates significantly changed model inference code (see the superceded PR https://github.com/Unidata/netcdf-c/pull/1259). 1. It centralizes the code that infers the dispatcher. 2. It adds support for byte-range URLs Other changes: 1. NC_HDF5_finalize was not being properly called by nc_finalize(). 2. Fix minor bug in ncgen3.l 3. fix memory leak in nc4info.c 4. add code to walk the .daprc triples and to replace protocol= fragment tag with a more general mode= tag. Final Note: Th inference code is still way too complicated. We need to move to the validfile() model used by netcdf Java, where each dispatcher is asked if it can process the file. This decentralizes the inference code. This will be done after all the major new dispatchers (PIO, Zarr, etc) have been implemented.
2019-01-02 09:27:36 +08:00
Trace("NC_hashmapget");
if(key == NULL || keysize == 0)
return 0;
hashkey = NC_hashmapkey(key,keysize);
if(hash->active) {
size_t index;
NC_hentry* h;
if(!locate(hash,hashkey,key,keysize,&index,0))
return 0; /* not present */
h = &hash->table[index];
if(h->flags & ACTIVE) {
This PR adds EXPERIMENTAL support for accessing data in the cloud using a variant of the Zarr protocol and storage format. This enhancement is generically referred to as "NCZarr". The data model supported by NCZarr is netcdf-4 minus the user-defined types and the String type. In this sense it is similar to the CDF-5 data model. More detailed information about enabling and using NCZarr is described in the document NUG/nczarr.md and in a [Unidata Developer's blog entry](https://www.unidata.ucar.edu/blogs/developer/en/entry/overview-of-zarr-support-in). WARNING: this code has had limited testing, so do use this version for production work. Also, performance improvements are ongoing. Note especially the following platform matrix of successful tests: Platform | Build System | S3 support ------------------------------------ Linux+gcc | Automake | yes Linux+gcc | CMake | yes Visual Studio | CMake | no Additionally, and as a consequence of the addition of NCZarr, major changes have been made to the Filter API. NOTE: NCZarr does not yet support filters, but these changes are enablers for that support in the future. Note that it is possible (probable?) that there will be some accidental reversions if the changes here did not correctly mimic the existing filter testing. In any case, previously filter ids and parameters were of type unsigned int. In order to support the more general zarr filter model, this was all converted to char*. The old HDF5-specific, unsigned int operations are still supported but they are wrappers around the new, char* based nc_filterx_XXX functions. This entailed at least the following changes: 1. Added the files libdispatch/dfilterx.c and include/ncfilter.h 2. Some filterx utilities have been moved to libdispatch/daux.c 3. A new entry, "filter_actions" was added to the NCDispatch table and the version bumped. 4. An overly complex set of structs was created to support funnelling all of the filterx operations thru a single dispatch "filter_actions" entry. 5. Move common code to from libhdf5 to libsrc4 so that it is accessible to nczarr. Changes directly related to Zarr: 1. Modified CMakeList.txt and configure.ac to support both C and C++ -- this is in support of S3 support via the awd-sdk libraries. 2. Define a size64_t type to support nczarr. 3. More reworking of libdispatch/dinfermodel.c to support zarr and to regularize the structure of the fragments section of a URL. Changes not directly related to Zarr: 1. Make client-side filter registration be conditional, with default off. 2. Hack include/nc4internal.h to make some flags added by Ed be unique: e.g. NC_CREAT, NC_INDEF, etc. 3. cleanup include/nchttp.h and libdispatch/dhttp.c. 4. Misc. changes to support compiling under Visual Studio including: * Better testing under windows for dirent.h and opendir and closedir. 5. Misc. changes to the oc2 code to support various libcurl CURLOPT flags and to centralize error reporting. 6. By default, suppress the vlen tests that have unfixed memory leaks; add option to enable them. 7. Make part of the nc_test/test_byterange.sh test be contingent on remotetest.unidata.ucar.edu being accessible. Changes Left TO-DO: 1. fix provenance code, it is too HDF5 specific.
2020-06-29 08:02:47 +08:00
if(datap) *datap = h->data;
return 1;
} else /* Not found */
return 0;
2017-08-16 02:03:15 +08:00
}
return 0;
2010-06-03 21:24:43 +08:00
}
/** Change the data for the specified key
Return 1 if found, 0 otherwise
*/
2010-06-03 21:24:43 +08:00
int
NC_hashmapsetdata(NC_hashmap* hash, const char* key, size_t keysize, uintptr_t newdata)
2010-06-03 21:24:43 +08:00
{
size_t index;
NC_hentry* h;
nchashkey_t hashkey;
Provide byte-range reading of remote datasets re: issue https://github.com/Unidata/netcdf-c/issues/1251 Assume that you have the URL to a remote dataset which is a normal netcdf-3 or netcdf-4 file. This PR allows the netcdf-c to read that dataset's contents as a netcdf file using HTTP byte ranges if the remote server supports byte-range access. Originally, this PR was set up to access Amazon S3 objects, but it can also access other remote datasets such as those provided by a Thredds server via the HTTPServer access protocol. It may also work for other kinds of servers. Note that this is not intended as a true production capability because, as is known, this kind of access to can be quite slow. In addition, the byte-range IO drivers do not currently do any sort of optimization or caching. An additional goal here is to gain some experience with the Amazon S3 REST protocol. This architecture and its use documented in the file docs/byterange.dox. There are currently two test cases: 1. nc_test/tst_s3raw.c - this does a simple open, check format, close cycle for a remote netcdf-3 file and a remote netcdf-4 file. 2. nc_test/test_s3raw.sh - this uses ncdump to investigate some remote datasets. This PR also incorporates significantly changed model inference code (see the superceded PR https://github.com/Unidata/netcdf-c/pull/1259). 1. It centralizes the code that infers the dispatcher. 2. It adds support for byte-range URLs Other changes: 1. NC_HDF5_finalize was not being properly called by nc_finalize(). 2. Fix minor bug in ncgen3.l 3. fix memory leak in nc4info.c 4. add code to walk the .daprc triples and to replace protocol= fragment tag with a more general mode= tag. Final Note: Th inference code is still way too complicated. We need to move to the validfile() model used by netcdf Java, where each dispatcher is asked if it can process the file. This decentralizes the inference code. This will be done after all the major new dispatchers (PIO, Zarr, etc) have been implemented.
2019-01-02 09:27:36 +08:00
Trace("NC_hashmapsetdata");
if(key == NULL || keysize == 0)
return 0;
hashkey = NC_hashmapkey(key,keysize);
if(hash == NULL || hash->active == 0)
return 0; /* no such entry */
if(!locate(hash,hashkey,key,keysize,&index,0))
return 0; /* not present */
h = &hash->table[index];
assert((h->flags & ACTIVE) == ACTIVE);
h->data = newdata;
return 1;
2010-06-03 21:24:43 +08:00
}
size_t
NC_hashmapcount(NC_hashmap* hash)
2010-06-03 21:24:43 +08:00
{
Provide byte-range reading of remote datasets re: issue https://github.com/Unidata/netcdf-c/issues/1251 Assume that you have the URL to a remote dataset which is a normal netcdf-3 or netcdf-4 file. This PR allows the netcdf-c to read that dataset's contents as a netcdf file using HTTP byte ranges if the remote server supports byte-range access. Originally, this PR was set up to access Amazon S3 objects, but it can also access other remote datasets such as those provided by a Thredds server via the HTTPServer access protocol. It may also work for other kinds of servers. Note that this is not intended as a true production capability because, as is known, this kind of access to can be quite slow. In addition, the byte-range IO drivers do not currently do any sort of optimization or caching. An additional goal here is to gain some experience with the Amazon S3 REST protocol. This architecture and its use documented in the file docs/byterange.dox. There are currently two test cases: 1. nc_test/tst_s3raw.c - this does a simple open, check format, close cycle for a remote netcdf-3 file and a remote netcdf-4 file. 2. nc_test/test_s3raw.sh - this uses ncdump to investigate some remote datasets. This PR also incorporates significantly changed model inference code (see the superceded PR https://github.com/Unidata/netcdf-c/pull/1259). 1. It centralizes the code that infers the dispatcher. 2. It adds support for byte-range URLs Other changes: 1. NC_HDF5_finalize was not being properly called by nc_finalize(). 2. Fix minor bug in ncgen3.l 3. fix memory leak in nc4info.c 4. add code to walk the .daprc triples and to replace protocol= fragment tag with a more general mode= tag. Final Note: Th inference code is still way too complicated. We need to move to the validfile() model used by netcdf Java, where each dispatcher is asked if it can process the file. This decentralizes the inference code. This will be done after all the major new dispatchers (PIO, Zarr, etc) have been implemented.
2019-01-02 09:27:36 +08:00
Trace("NC_hashmapcount");
return hash->active;
2010-06-03 21:24:43 +08:00
}
This PR adds EXPERIMENTAL support for accessing data in the cloud using a variant of the Zarr protocol and storage format. This enhancement is generically referred to as "NCZarr". The data model supported by NCZarr is netcdf-4 minus the user-defined types and the String type. In this sense it is similar to the CDF-5 data model. More detailed information about enabling and using NCZarr is described in the document NUG/nczarr.md and in a [Unidata Developer's blog entry](https://www.unidata.ucar.edu/blogs/developer/en/entry/overview-of-zarr-support-in). WARNING: this code has had limited testing, so do use this version for production work. Also, performance improvements are ongoing. Note especially the following platform matrix of successful tests: Platform | Build System | S3 support ------------------------------------ Linux+gcc | Automake | yes Linux+gcc | CMake | yes Visual Studio | CMake | no Additionally, and as a consequence of the addition of NCZarr, major changes have been made to the Filter API. NOTE: NCZarr does not yet support filters, but these changes are enablers for that support in the future. Note that it is possible (probable?) that there will be some accidental reversions if the changes here did not correctly mimic the existing filter testing. In any case, previously filter ids and parameters were of type unsigned int. In order to support the more general zarr filter model, this was all converted to char*. The old HDF5-specific, unsigned int operations are still supported but they are wrappers around the new, char* based nc_filterx_XXX functions. This entailed at least the following changes: 1. Added the files libdispatch/dfilterx.c and include/ncfilter.h 2. Some filterx utilities have been moved to libdispatch/daux.c 3. A new entry, "filter_actions" was added to the NCDispatch table and the version bumped. 4. An overly complex set of structs was created to support funnelling all of the filterx operations thru a single dispatch "filter_actions" entry. 5. Move common code to from libhdf5 to libsrc4 so that it is accessible to nczarr. Changes directly related to Zarr: 1. Modified CMakeList.txt and configure.ac to support both C and C++ -- this is in support of S3 support via the awd-sdk libraries. 2. Define a size64_t type to support nczarr. 3. More reworking of libdispatch/dinfermodel.c to support zarr and to regularize the structure of the fragments section of a URL. Changes not directly related to Zarr: 1. Make client-side filter registration be conditional, with default off. 2. Hack include/nc4internal.h to make some flags added by Ed be unique: e.g. NC_CREAT, NC_INDEF, etc. 3. cleanup include/nchttp.h and libdispatch/dhttp.c. 4. Misc. changes to support compiling under Visual Studio including: * Better testing under windows for dirent.h and opendir and closedir. 5. Misc. changes to the oc2 code to support various libcurl CURLOPT flags and to centralize error reporting. 6. By default, suppress the vlen tests that have unfixed memory leaks; add option to enable them. 7. Make part of the nc_test/test_byterange.sh test be contingent on remotetest.unidata.ucar.edu being accessible. Changes Left TO-DO: 1. fix provenance code, it is too HDF5 specific.
2020-06-29 08:02:47 +08:00
int
NC_hashmapith(NC_hashmap* map, size_t i, uintptr_t* datap, const char** keyp)
{
NC_hentry* h = NULL;
2020-06-29 09:07:08 +08:00
if(map == NULL || i >= map->alloc) return NC_EINVAL;
This PR adds EXPERIMENTAL support for accessing data in the cloud using a variant of the Zarr protocol and storage format. This enhancement is generically referred to as "NCZarr". The data model supported by NCZarr is netcdf-4 minus the user-defined types and the String type. In this sense it is similar to the CDF-5 data model. More detailed information about enabling and using NCZarr is described in the document NUG/nczarr.md and in a [Unidata Developer's blog entry](https://www.unidata.ucar.edu/blogs/developer/en/entry/overview-of-zarr-support-in). WARNING: this code has had limited testing, so do use this version for production work. Also, performance improvements are ongoing. Note especially the following platform matrix of successful tests: Platform | Build System | S3 support ------------------------------------ Linux+gcc | Automake | yes Linux+gcc | CMake | yes Visual Studio | CMake | no Additionally, and as a consequence of the addition of NCZarr, major changes have been made to the Filter API. NOTE: NCZarr does not yet support filters, but these changes are enablers for that support in the future. Note that it is possible (probable?) that there will be some accidental reversions if the changes here did not correctly mimic the existing filter testing. In any case, previously filter ids and parameters were of type unsigned int. In order to support the more general zarr filter model, this was all converted to char*. The old HDF5-specific, unsigned int operations are still supported but they are wrappers around the new, char* based nc_filterx_XXX functions. This entailed at least the following changes: 1. Added the files libdispatch/dfilterx.c and include/ncfilter.h 2. Some filterx utilities have been moved to libdispatch/daux.c 3. A new entry, "filter_actions" was added to the NCDispatch table and the version bumped. 4. An overly complex set of structs was created to support funnelling all of the filterx operations thru a single dispatch "filter_actions" entry. 5. Move common code to from libhdf5 to libsrc4 so that it is accessible to nczarr. Changes directly related to Zarr: 1. Modified CMakeList.txt and configure.ac to support both C and C++ -- this is in support of S3 support via the awd-sdk libraries. 2. Define a size64_t type to support nczarr. 3. More reworking of libdispatch/dinfermodel.c to support zarr and to regularize the structure of the fragments section of a URL. Changes not directly related to Zarr: 1. Make client-side filter registration be conditional, with default off. 2. Hack include/nc4internal.h to make some flags added by Ed be unique: e.g. NC_CREAT, NC_INDEF, etc. 3. cleanup include/nchttp.h and libdispatch/dhttp.c. 4. Misc. changes to support compiling under Visual Studio including: * Better testing under windows for dirent.h and opendir and closedir. 5. Misc. changes to the oc2 code to support various libcurl CURLOPT flags and to centralize error reporting. 6. By default, suppress the vlen tests that have unfixed memory leaks; add option to enable them. 7. Make part of the nc_test/test_byterange.sh test be contingent on remotetest.unidata.ucar.edu being accessible. Changes Left TO-DO: 1. fix provenance code, it is too HDF5 specific.
2020-06-29 08:02:47 +08:00
h = &map->table[i];
if(h && (h->flags & ACTIVE)) {
if(datap) *datap = h->data;
if(keyp) *((char**)keyp) = h->key;
} else {
if(datap) *datap = 0;
if(keyp) *((char**)keyp) = NULL;
}
return NC_NOERR;
}
2010-06-03 21:24:43 +08:00
int
NC_hashmapfree(NC_hashmap* hash)
2010-06-03 21:24:43 +08:00
{
Provide byte-range reading of remote datasets re: issue https://github.com/Unidata/netcdf-c/issues/1251 Assume that you have the URL to a remote dataset which is a normal netcdf-3 or netcdf-4 file. This PR allows the netcdf-c to read that dataset's contents as a netcdf file using HTTP byte ranges if the remote server supports byte-range access. Originally, this PR was set up to access Amazon S3 objects, but it can also access other remote datasets such as those provided by a Thredds server via the HTTPServer access protocol. It may also work for other kinds of servers. Note that this is not intended as a true production capability because, as is known, this kind of access to can be quite slow. In addition, the byte-range IO drivers do not currently do any sort of optimization or caching. An additional goal here is to gain some experience with the Amazon S3 REST protocol. This architecture and its use documented in the file docs/byterange.dox. There are currently two test cases: 1. nc_test/tst_s3raw.c - this does a simple open, check format, close cycle for a remote netcdf-3 file and a remote netcdf-4 file. 2. nc_test/test_s3raw.sh - this uses ncdump to investigate some remote datasets. This PR also incorporates significantly changed model inference code (see the superceded PR https://github.com/Unidata/netcdf-c/pull/1259). 1. It centralizes the code that infers the dispatcher. 2. It adds support for byte-range URLs Other changes: 1. NC_HDF5_finalize was not being properly called by nc_finalize(). 2. Fix minor bug in ncgen3.l 3. fix memory leak in nc4info.c 4. add code to walk the .daprc triples and to replace protocol= fragment tag with a more general mode= tag. Final Note: Th inference code is still way too complicated. We need to move to the validfile() model used by netcdf Java, where each dispatcher is asked if it can process the file. This decentralizes the inference code. This will be done after all the major new dispatchers (PIO, Zarr, etc) have been implemented.
2019-01-02 09:27:36 +08:00
Trace("NC_hashmapfree");
if(hash) {
int i;
#ifdef DEBUG
printhashmapstats(hash);
#endif
for(i=0;i<hash->alloc;i++) {
NC_hentry* he = &hash->table[i];
if((he->flags & ACTIVE) && he->key != NULL)
free(he->key);
}
free(hash->table);
free(hash);
2010-06-03 21:24:43 +08:00
}
return 1;
2010-06-03 21:24:43 +08:00
}
/**
Friend: ncindex.c
Only used by ncindex.c.
Allows a hack by ncindex.
*/
int
NC_hashmapdeactivate(NC_hashmap* map, uintptr_t data)
{
size_t i;
NC_hentry* h;
for(h=map->table,i=0;i<map->alloc;i++,h++) {
if((h->flags & ACTIVE) && h->data == data) {
h->flags = DELETED;
if(h->key) free(h->key);
h->key = NULL;
h->keysize = 0;
--map->active;
return 1;
}
}
return 0;
}
/**************************************************/
/* Prime table */
/* Function that returns true if n is prime else returns false */
/* This will currently fail if `n > 180503 * 180503` */
static int isPrime(size_t n)
{
2022-04-27 04:39:51 +08:00
size_t i;
2022-04-27 23:52:00 +08:00
if (n <= 1) return 0;
if (n <= 3) return 1;
2022-04-27 04:39:51 +08:00
for (i=1; i < NC_nprimes - 1; i++) {
size_t prime = NC_primes[i];
if (n % prime == 0) {
return 0;
}
if (prime * prime > n) {
break;
}
}
return 1;
}
/* Function to return the smallest prime number greater than N */
static int nextPrime(size_t val)
{
if (val <= 1)
return 2;
size_t prime = val;
if (prime % 2 == 0) { /* Make sure `prime` is odd */
prime--;
}
/* Loop continuously until isPrime returns */
/* true for a number greater than n */
for (;;) {
prime += 2;
if (isPrime(prime))
break;
}
return prime;
}
/*
Binary search prime table for first prime just greater than or
equal to val
*/
static unsigned int
findPrimeGreaterThan(size_t val)
2010-06-03 21:24:43 +08:00
{
int n = NC_nprimes;
int L = 1; /* skip leading flag number */
int R = (n - 2); /* skip trailing flag */
unsigned int v = 0;
int m;
if(val >= 0xFFFFFFFF)
return 0; /* Too big */
v = (unsigned int)val;
if (v > NC_primes[n - 2]) {
/*
If we have a value greater than the largest value in the
NC_primes table, then search for a prime instead of just
doing a simple lookup.
*/
return nextPrime(val);
}
for(;;) {
if(L >= R) break;
m = (L + R) / 2;
/* is this an acceptable prime? */
if(NC_primes[m-1] < v && NC_primes[m] >= v)
return NC_primes[m]; /* acceptable*/
else if(NC_primes[m-1] >= v)
R = m;
else if(NC_primes[m] < v)
L = m;
}
return 0;
2010-06-03 21:24:43 +08:00
}
/*
Table of the the first 2^14 primes.
Add leading and trailing values to simplify
search binary algorithm.
*/
static const unsigned int NC_primes[16386] = {
0U,
2U, 3U, 5U, 7U, 11U, 13U, 17U, 19U, 23U, 29U,
31U, 37U, 41U, 43U, 47U, 53U, 59U, 61U, 67U, 71U,
73U, 79U, 83U, 89U, 97U, 101U, 103U, 107U, 109U, 113U,
127U, 131U, 137U, 139U, 149U, 151U, 157U, 163U, 167U, 173U,
179U, 181U, 191U, 193U, 197U, 199U, 211U, 223U, 227U, 229U,
233U, 239U, 241U, 251U, 257U, 263U, 269U, 271U, 277U, 281U,
283U, 293U, 307U, 311U, 313U, 317U, 331U, 337U, 347U, 349U,
353U, 359U, 367U, 373U, 379U, 383U, 389U, 397U, 401U, 409U,
419U, 421U, 431U, 433U, 439U, 443U, 449U, 457U, 461U, 463U,
467U, 479U, 487U, 491U, 499U, 503U, 509U, 521U, 523U, 541U,
547U, 557U, 563U, 569U, 571U, 577U, 587U, 593U, 599U, 601U,
607U, 613U, 617U, 619U, 631U, 641U, 643U, 647U, 653U, 659U,
661U, 673U, 677U, 683U, 691U, 701U, 709U, 719U, 727U, 733U,
739U, 743U, 751U, 757U, 761U, 769U, 773U, 787U, 797U, 809U,
811U, 821U, 823U, 827U, 829U, 839U, 853U, 857U, 859U, 863U,
877U, 881U, 883U, 887U, 907U, 911U, 919U, 929U, 937U, 941U,
947U, 953U, 967U, 971U, 977U, 983U, 991U, 997U, 1009U, 1013U,
1019U, 1021U, 1031U, 1033U, 1039U, 1049U, 1051U, 1061U, 1063U, 1069U,
1087U, 1091U, 1093U, 1097U, 1103U, 1109U, 1117U, 1123U, 1129U, 1151U,
1153U, 1163U, 1171U, 1181U, 1187U, 1193U, 1201U, 1213U, 1217U, 1223U,
1229U, 1231U, 1237U, 1249U, 1259U, 1277U, 1279U, 1283U, 1289U, 1291U,
1297U, 1301U, 1303U, 1307U, 1319U, 1321U, 1327U, 1361U, 1367U, 1373U,
1381U, 1399U, 1409U, 1423U, 1427U, 1429U, 1433U, 1439U, 1447U, 1451U,
1453U, 1459U, 1471U, 1481U, 1483U, 1487U, 1489U, 1493U, 1499U, 1511U,
1523U, 1531U, 1543U, 1549U, 1553U, 1559U, 1567U, 1571U, 1579U, 1583U,
1597U, 1601U, 1607U, 1609U, 1613U, 1619U, 1621U, 1627U, 1637U, 1657U,
1663U, 1667U, 1669U, 1693U, 1697U, 1699U, 1709U, 1721U, 1723U, 1733U,
1741U, 1747U, 1753U, 1759U, 1777U, 1783U, 1787U, 1789U, 1801U, 1811U,
1823U, 1831U, 1847U, 1861U, 1867U, 1871U, 1873U, 1877U, 1879U, 1889U,
1901U, 1907U, 1913U, 1931U, 1933U, 1949U, 1951U, 1973U, 1979U, 1987U,
1993U, 1997U, 1999U, 2003U, 2011U, 2017U, 2027U, 2029U, 2039U, 2053U,
2063U, 2069U, 2081U, 2083U, 2087U, 2089U, 2099U, 2111U, 2113U, 2129U,
2131U, 2137U, 2141U, 2143U, 2153U, 2161U, 2179U, 2203U, 2207U, 2213U,
2221U, 2237U, 2239U, 2243U, 2251U, 2267U, 2269U, 2273U, 2281U, 2287U,
2293U, 2297U, 2309U, 2311U, 2333U, 2339U, 2341U, 2347U, 2351U, 2357U,
2371U, 2377U, 2381U, 2383U, 2389U, 2393U, 2399U, 2411U, 2417U, 2423U,
2437U, 2441U, 2447U, 2459U, 2467U, 2473U, 2477U, 2503U, 2521U, 2531U,
2539U, 2543U, 2549U, 2551U, 2557U, 2579U, 2591U, 2593U, 2609U, 2617U,
2621U, 2633U, 2647U, 2657U, 2659U, 2663U, 2671U, 2677U, 2683U, 2687U,
2689U, 2693U, 2699U, 2707U, 2711U, 2713U, 2719U, 2729U, 2731U, 2741U,
2749U, 2753U, 2767U, 2777U, 2789U, 2791U, 2797U, 2801U, 2803U, 2819U,
2833U, 2837U, 2843U, 2851U, 2857U, 2861U, 2879U, 2887U, 2897U, 2903U,
2909U, 2917U, 2927U, 2939U, 2953U, 2957U, 2963U, 2969U, 2971U, 2999U,
3001U, 3011U, 3019U, 3023U, 3037U, 3041U, 3049U, 3061U, 3067U, 3079U,
3083U, 3089U, 3109U, 3119U, 3121U, 3137U, 3163U, 3167U, 3169U, 3181U,
3187U, 3191U, 3203U, 3209U, 3217U, 3221U, 3229U, 3251U, 3253U, 3257U,
3259U, 3271U, 3299U, 3301U, 3307U, 3313U, 3319U, 3323U, 3329U, 3331U,
3343U, 3347U, 3359U, 3361U, 3371U, 3373U, 3389U, 3391U, 3407U, 3413U,
3433U, 3449U, 3457U, 3461U, 3463U, 3467U, 3469U, 3491U, 3499U, 3511U,
3517U, 3527U, 3529U, 3533U, 3539U, 3541U, 3547U, 3557U, 3559U, 3571U,
3581U, 3583U, 3593U, 3607U, 3613U, 3617U, 3623U, 3631U, 3637U, 3643U,
3659U, 3671U, 3673U, 3677U, 3691U, 3697U, 3701U, 3709U, 3719U, 3727U,
3733U, 3739U, 3761U, 3767U, 3769U, 3779U, 3793U, 3797U, 3803U, 3821U,
3823U, 3833U, 3847U, 3851U, 3853U, 3863U, 3877U, 3881U, 3889U, 3907U,
3911U, 3917U, 3919U, 3923U, 3929U, 3931U, 3943U, 3947U, 3967U, 3989U,
4001U, 4003U, 4007U, 4013U, 4019U, 4021U, 4027U, 4049U, 4051U, 4057U,
4073U, 4079U, 4091U, 4093U, 4099U, 4111U, 4127U, 4129U, 4133U, 4139U,
4153U, 4157U, 4159U, 4177U, 4201U, 4211U, 4217U, 4219U, 4229U, 4231U,
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162749U, 162751U, 162779U, 162787U, 162791U, 162821U, 162823U, 162829U, 162839U, 162847U,
162853U, 162859U, 162881U, 162889U, 162901U, 162907U, 162917U, 162937U, 162947U, 162971U,
162973U, 162989U, 162997U, 163003U, 163019U, 163021U, 163027U, 163061U, 163063U, 163109U,
163117U, 163127U, 163129U, 163147U, 163151U, 163169U, 163171U, 163181U, 163193U, 163199U,
163211U, 163223U, 163243U, 163249U, 163259U, 163307U, 163309U, 163321U, 163327U, 163337U,
163351U, 163363U, 163367U, 163393U, 163403U, 163409U, 163411U, 163417U, 163433U, 163469U,
163477U, 163481U, 163483U, 163487U, 163517U, 163543U, 163561U, 163567U, 163573U, 163601U,
163613U, 163621U, 163627U, 163633U, 163637U, 163643U, 163661U, 163673U, 163679U, 163697U,
163729U, 163733U, 163741U, 163753U, 163771U, 163781U, 163789U, 163811U, 163819U, 163841U,
163847U, 163853U, 163859U, 163861U, 163871U, 163883U, 163901U, 163909U, 163927U, 163973U,
163979U, 163981U, 163987U, 163991U, 163993U, 163997U, 164011U, 164023U, 164039U, 164051U,
164057U, 164071U, 164089U, 164093U, 164113U, 164117U, 164147U, 164149U, 164173U, 164183U,
164191U, 164201U, 164209U, 164231U, 164233U, 164239U, 164249U, 164251U, 164267U, 164279U,
164291U, 164299U, 164309U, 164321U, 164341U, 164357U, 164363U, 164371U, 164377U, 164387U,
164413U, 164419U, 164429U, 164431U, 164443U, 164447U, 164449U, 164471U, 164477U, 164503U,
164513U, 164531U, 164569U, 164581U, 164587U, 164599U, 164617U, 164621U, 164623U, 164627U,
164653U, 164663U, 164677U, 164683U, 164701U, 164707U, 164729U, 164743U, 164767U, 164771U,
164789U, 164809U, 164821U, 164831U, 164837U, 164839U, 164881U, 164893U, 164911U, 164953U,
164963U, 164987U, 164999U, 165001U, 165037U, 165041U, 165047U, 165049U, 165059U, 165079U,
165083U, 165089U, 165103U, 165133U, 165161U, 165173U, 165181U, 165203U, 165211U, 165229U,
165233U, 165247U, 165287U, 165293U, 165311U, 165313U, 165317U, 165331U, 165343U, 165349U,
165367U, 165379U, 165383U, 165391U, 165397U, 165437U, 165443U, 165449U, 165457U, 165463U,
165469U, 165479U, 165511U, 165523U, 165527U, 165533U, 165541U, 165551U, 165553U, 165559U,
165569U, 165587U, 165589U, 165601U, 165611U, 165617U, 165653U, 165667U, 165673U, 165701U,
165703U, 165707U, 165709U, 165713U, 165719U, 165721U, 165749U, 165779U, 165799U, 165811U,
165817U, 165829U, 165833U, 165857U, 165877U, 165883U, 165887U, 165901U, 165931U, 165941U,
165947U, 165961U, 165983U, 166013U, 166021U, 166027U, 166031U, 166043U, 166063U, 166081U,
166099U, 166147U, 166151U, 166157U, 166169U, 166183U, 166189U, 166207U, 166219U, 166237U,
166247U, 166259U, 166273U, 166289U, 166297U, 166301U, 166303U, 166319U, 166349U, 166351U,
166357U, 166363U, 166393U, 166399U, 166403U, 166409U, 166417U, 166429U, 166457U, 166471U,
166487U, 166541U, 166561U, 166567U, 166571U, 166597U, 166601U, 166603U, 166609U, 166613U,
166619U, 166627U, 166631U, 166643U, 166657U, 166667U, 166669U, 166679U, 166693U, 166703U,
166723U, 166739U, 166741U, 166781U, 166783U, 166799U, 166807U, 166823U, 166841U, 166843U,
166847U, 166849U, 166853U, 166861U, 166867U, 166871U, 166909U, 166919U, 166931U, 166949U,
166967U, 166973U, 166979U, 166987U, 167009U, 167017U, 167021U, 167023U, 167033U, 167039U,
167047U, 167051U, 167071U, 167077U, 167081U, 167087U, 167099U, 167107U, 167113U, 167117U,
167119U, 167149U, 167159U, 167173U, 167177U, 167191U, 167197U, 167213U, 167221U, 167249U,
167261U, 167267U, 167269U, 167309U, 167311U, 167317U, 167329U, 167339U, 167341U, 167381U,
167393U, 167407U, 167413U, 167423U, 167429U, 167437U, 167441U, 167443U, 167449U, 167471U,
167483U, 167491U, 167521U, 167537U, 167543U, 167593U, 167597U, 167611U, 167621U, 167623U,
167627U, 167633U, 167641U, 167663U, 167677U, 167683U, 167711U, 167729U, 167747U, 167759U,
167771U, 167777U, 167779U, 167801U, 167809U, 167861U, 167863U, 167873U, 167879U, 167887U,
167891U, 167899U, 167911U, 167917U, 167953U, 167971U, 167987U, 168013U, 168023U, 168029U,
168037U, 168043U, 168067U, 168071U, 168083U, 168089U, 168109U, 168127U, 168143U, 168151U,
168193U, 168197U, 168211U, 168227U, 168247U, 168253U, 168263U, 168269U, 168277U, 168281U,
168293U, 168323U, 168331U, 168347U, 168353U, 168391U, 168409U, 168433U, 168449U, 168451U,
168457U, 168463U, 168481U, 168491U, 168499U, 168523U, 168527U, 168533U, 168541U, 168559U,
168599U, 168601U, 168617U, 168629U, 168631U, 168643U, 168673U, 168677U, 168697U, 168713U,
168719U, 168731U, 168737U, 168743U, 168761U, 168769U, 168781U, 168803U, 168851U, 168863U,
168869U, 168887U, 168893U, 168899U, 168901U, 168913U, 168937U, 168943U, 168977U, 168991U,
169003U, 169007U, 169009U, 169019U, 169049U, 169063U, 169067U, 169069U, 169079U, 169093U,
169097U, 169111U, 169129U, 169151U, 169159U, 169177U, 169181U, 169199U, 169217U, 169219U,
169241U, 169243U, 169249U, 169259U, 169283U, 169307U, 169313U, 169319U, 169321U, 169327U,
169339U, 169343U, 169361U, 169369U, 169373U, 169399U, 169409U, 169427U, 169457U, 169471U,
169483U, 169489U, 169493U, 169501U, 169523U, 169531U, 169553U, 169567U, 169583U, 169591U,
169607U, 169627U, 169633U, 169639U, 169649U, 169657U, 169661U, 169667U, 169681U, 169691U,
169693U, 169709U, 169733U, 169751U, 169753U, 169769U, 169777U, 169783U, 169789U, 169817U,
169823U, 169831U, 169837U, 169843U, 169859U, 169889U, 169891U, 169909U, 169913U, 169919U,
169933U, 169937U, 169943U, 169951U, 169957U, 169987U, 169991U, 170003U, 170021U, 170029U,
170047U, 170057U, 170063U, 170081U, 170099U, 170101U, 170111U, 170123U, 170141U, 170167U,
170179U, 170189U, 170197U, 170207U, 170213U, 170227U, 170231U, 170239U, 170243U, 170249U,
170263U, 170267U, 170279U, 170293U, 170299U, 170327U, 170341U, 170347U, 170351U, 170353U,
170363U, 170369U, 170371U, 170383U, 170389U, 170393U, 170413U, 170441U, 170447U, 170473U,
170483U, 170497U, 170503U, 170509U, 170537U, 170539U, 170551U, 170557U, 170579U, 170603U,
170609U, 170627U, 170633U, 170641U, 170647U, 170669U, 170689U, 170701U, 170707U, 170711U,
170741U, 170749U, 170759U, 170761U, 170767U, 170773U, 170777U, 170801U, 170809U, 170813U,
170827U, 170837U, 170843U, 170851U, 170857U, 170873U, 170881U, 170887U, 170899U, 170921U,
170927U, 170953U, 170957U, 170971U, 171007U, 171023U, 171029U, 171043U, 171047U, 171049U,
171053U, 171077U, 171079U, 171091U, 171103U, 171131U, 171161U, 171163U, 171167U, 171169U,
171179U, 171203U, 171233U, 171251U, 171253U, 171263U, 171271U, 171293U, 171299U, 171317U,
171329U, 171341U, 171383U, 171401U, 171403U, 171427U, 171439U, 171449U, 171467U, 171469U,
171473U, 171481U, 171491U, 171517U, 171529U, 171539U, 171541U, 171553U, 171559U, 171571U,
171583U, 171617U, 171629U, 171637U, 171641U, 171653U, 171659U, 171671U, 171673U, 171679U,
171697U, 171707U, 171713U, 171719U, 171733U, 171757U, 171761U, 171763U, 171793U, 171799U,
171803U, 171811U, 171823U, 171827U, 171851U, 171863U, 171869U, 171877U, 171881U, 171889U,
171917U, 171923U, 171929U, 171937U, 171947U, 172001U, 172009U, 172021U, 172027U, 172031U,
172049U, 172069U, 172079U, 172093U, 172097U, 172127U, 172147U, 172153U, 172157U, 172169U,
172171U, 172181U, 172199U, 172213U, 172217U, 172219U, 172223U, 172243U, 172259U, 172279U,
172283U, 172297U, 172307U, 172313U, 172321U, 172331U, 172343U, 172351U, 172357U, 172373U,
172399U, 172411U, 172421U, 172423U, 172427U, 172433U, 172439U, 172441U, 172489U, 172507U,
172517U, 172519U, 172541U, 172553U, 172561U, 172573U, 172583U, 172589U, 172597U, 172603U,
172607U, 172619U, 172633U, 172643U, 172649U, 172657U, 172663U, 172673U, 172681U, 172687U,
172709U, 172717U, 172721U, 172741U, 172751U, 172759U, 172787U, 172801U, 172807U, 172829U,
172849U, 172853U, 172859U, 172867U, 172871U, 172877U, 172883U, 172933U, 172969U, 172973U,
172981U, 172987U, 172993U, 172999U, 173021U, 173023U, 173039U, 173053U, 173059U, 173081U,
173087U, 173099U, 173137U, 173141U, 173149U, 173177U, 173183U, 173189U, 173191U, 173207U,
173209U, 173219U, 173249U, 173263U, 173267U, 173273U, 173291U, 173293U, 173297U, 173309U,
173347U, 173357U, 173359U, 173429U, 173431U, 173473U, 173483U, 173491U, 173497U, 173501U,
173531U, 173539U, 173543U, 173549U, 173561U, 173573U, 173599U, 173617U, 173629U, 173647U,
173651U, 173659U, 173669U, 173671U, 173683U, 173687U, 173699U, 173707U, 173713U, 173729U,
173741U, 173743U, 173773U, 173777U, 173779U, 173783U, 173807U, 173819U, 173827U, 173839U,
173851U, 173861U, 173867U, 173891U, 173897U, 173909U, 173917U, 173923U, 173933U, 173969U,
173977U, 173981U, 173993U, 174007U, 174017U, 174019U, 174047U, 174049U, 174061U, 174067U,
174071U, 174077U, 174079U, 174091U, 174101U, 174121U, 174137U, 174143U, 174149U, 174157U,
174169U, 174197U, 174221U, 174241U, 174257U, 174259U, 174263U, 174281U, 174289U, 174299U,
174311U, 174329U, 174331U, 174337U, 174347U, 174367U, 174389U, 174407U, 174413U, 174431U,
174443U, 174457U, 174467U, 174469U, 174481U, 174487U, 174491U, 174527U, 174533U, 174569U,
174571U, 174583U, 174599U, 174613U, 174617U, 174631U, 174637U, 174649U, 174653U, 174659U,
174673U, 174679U, 174703U, 174721U, 174737U, 174749U, 174761U, 174763U, 174767U, 174773U,
174799U, 174821U, 174829U, 174851U, 174859U, 174877U, 174893U, 174901U, 174907U, 174917U,
174929U, 174931U, 174943U, 174959U, 174989U, 174991U, 175003U, 175013U, 175039U, 175061U,
175067U, 175069U, 175079U, 175081U, 175103U, 175129U, 175141U, 175211U, 175229U, 175261U,
175267U, 175277U, 175291U, 175303U, 175309U, 175327U, 175333U, 175349U, 175361U, 175391U,
175393U, 175403U, 175411U, 175433U, 175447U, 175453U, 175463U, 175481U, 175493U, 175499U,
175519U, 175523U, 175543U, 175573U, 175601U, 175621U, 175631U, 175633U, 175649U, 175663U,
175673U, 175687U, 175691U, 175699U, 175709U, 175723U, 175727U, 175753U, 175757U, 175759U,
175781U, 175783U, 175811U, 175829U, 175837U, 175843U, 175853U, 175859U, 175873U, 175891U,
175897U, 175909U, 175919U, 175937U, 175939U, 175949U, 175961U, 175963U, 175979U, 175991U,
175993U, 176017U, 176021U, 176023U, 176041U, 176047U, 176051U, 176053U, 176063U, 176081U,
176087U, 176089U, 176123U, 176129U, 176153U, 176159U, 176161U, 176179U, 176191U, 176201U,
176207U, 176213U, 176221U, 176227U, 176237U, 176243U, 176261U, 176299U, 176303U, 176317U,
176321U, 176327U, 176329U, 176333U, 176347U, 176353U, 176357U, 176369U, 176383U, 176389U,
176401U, 176413U, 176417U, 176419U, 176431U, 176459U, 176461U, 176467U, 176489U, 176497U,
176503U, 176507U, 176509U, 176521U, 176531U, 176537U, 176549U, 176551U, 176557U, 176573U,
176591U, 176597U, 176599U, 176609U, 176611U, 176629U, 176641U, 176651U, 176677U, 176699U,
176711U, 176713U, 176741U, 176747U, 176753U, 176777U, 176779U, 176789U, 176791U, 176797U,
176807U, 176809U, 176819U, 176849U, 176857U, 176887U, 176899U, 176903U, 176921U, 176923U,
176927U, 176933U, 176951U, 176977U, 176983U, 176989U, 177007U, 177011U, 177013U, 177019U,
177043U, 177091U, 177101U, 177109U, 177113U, 177127U, 177131U, 177167U, 177173U, 177209U,
177211U, 177217U, 177223U, 177239U, 177257U, 177269U, 177283U, 177301U, 177319U, 177323U,
177337U, 177347U, 177379U, 177383U, 177409U, 177421U, 177427U, 177431U, 177433U, 177467U,
177473U, 177481U, 177487U, 177493U, 177511U, 177533U, 177539U, 177553U, 177589U, 177601U,
177623U, 177647U, 177677U, 177679U, 177691U, 177739U, 177743U, 177761U, 177763U, 177787U,
177791U, 177797U, 177811U, 177823U, 177839U, 177841U, 177883U, 177887U, 177889U, 177893U,
177907U, 177913U, 177917U, 177929U, 177943U, 177949U, 177953U, 177967U, 177979U, 178001U,
178021U, 178037U, 178039U, 178067U, 178069U, 178091U, 178093U, 178103U, 178117U, 178127U,
178141U, 178151U, 178169U, 178183U, 178187U, 178207U, 178223U, 178231U, 178247U, 178249U,
178259U, 178261U, 178289U, 178301U, 178307U, 178327U, 178333U, 178349U, 178351U, 178361U,
178393U, 178397U, 178403U, 178417U, 178439U, 178441U, 178447U, 178469U, 178481U, 178487U,
178489U, 178501U, 178513U, 178531U, 178537U, 178559U, 178561U, 178567U, 178571U, 178597U,
178601U, 178603U, 178609U, 178613U, 178621U, 178627U, 178639U, 178643U, 178681U, 178691U,
178693U, 178697U, 178753U, 178757U, 178781U, 178793U, 178799U, 178807U, 178813U, 178817U,
178819U, 178831U, 178853U, 178859U, 178873U, 178877U, 178889U, 178897U, 178903U, 178907U,
178909U, 178921U, 178931U, 178933U, 178939U, 178951U, 178973U, 178987U, 179021U, 179029U,
179033U, 179041U, 179051U, 179057U, 179083U, 179089U, 179099U, 179107U, 179111U, 179119U,
179143U, 179161U, 179167U, 179173U, 179203U, 179209U, 179213U, 179233U, 179243U, 179261U,
179269U, 179281U, 179287U, 179317U, 179321U, 179327U, 179351U, 179357U, 179369U, 179381U,
179383U, 179393U, 179407U, 179411U, 179429U, 179437U, 179441U, 179453U, 179461U, 179471U,
179479U, 179483U, 179497U, 179519U, 179527U, 179533U, 179549U, 179563U, 179573U, 179579U,
179581U, 179591U, 179593U, 179603U, 179623U, 179633U, 179651U, 179657U, 179659U, 179671U,
179687U, 179689U, 179693U, 179717U, 179719U, 179737U, 179743U, 179749U, 179779U, 179801U,
179807U, 179813U, 179819U, 179821U, 179827U, 179833U, 179849U, 179897U, 179899U, 179903U,
179909U, 179917U, 179923U, 179939U, 179947U, 179951U, 179953U, 179957U, 179969U, 179981U,
179989U, 179999U, 180001U, 180007U, 180023U, 180043U, 180053U, 180071U, 180073U, 180077U,
180097U, 180137U, 180161U, 180179U, 180181U, 180211U, 180221U, 180233U, 180239U, 180241U,
180247U, 180259U, 180263U, 180281U, 180287U, 180289U, 180307U, 180311U, 180317U, 180331U,
180337U, 180347U, 180361U, 180371U, 180379U, 180391U, 180413U, 180419U, 180437U, 180463U,
180473U, 180491U, 180497U, 180503U,
0xFFFFFFFF
};
static const unsigned int NC_nprimes = (sizeof(NC_primes) / sizeof(unsigned int));
/**************************************************/
/* Debug support */
void
printhashmapstats(NC_hashmap* hm)
2010-06-03 21:24:43 +08:00
{
size_t n,i;
size_t step = 1;
size_t maxchain = 0;
for(n=0;n<hm->alloc;n++) {
size_t chainlen = 0;
size_t index = n;
/* Follow chain at this index */
for(i=0;i<hm->alloc;i++) {
NC_hentry* entry = &hm->table[index];
switch (entry->flags) {
case ACTIVE: chainlen++; break; /* Keep looking */
case DELETED: chainlen++; break; /* Keep looking */
default: /* empty slot, stop walking */
if(chainlen > maxchain) maxchain = chainlen;
goto next;
}
/* linear probe */
index = (index + step) % hm->alloc;
}
next: continue;
}
fprintf(stderr,"hashmap: alloc=%lu active=%lu maxchain=%lu\n",
(unsigned long)hm->alloc,(unsigned long)hm->active,(unsigned long)maxchain);
fflush(stderr);
}
void
printhashmap(NC_hashmap* hm)
{
size_t i;
int running;
if(hm == NULL) {fprintf(stderr,"NULL"); fflush(stderr); return;}
fprintf(stderr,"{size=%lu count=%lu table=0x%lx}\n",
(unsigned long)hm->alloc,(unsigned long)hm->active,(unsigned long)((uintptr_t)hm->table));
if(hm->alloc > 4000) {
fprintf(stderr,"MALFORMED\n");
return;
}
running = 0;
for(i=0;i<hm->alloc;i++) {
NC_hentry e = hm->table[i];
if(e.flags == ACTIVE) {
fprintf(stderr,"[%ld] flags=ACTIVE hashkey=%lu data=%p keysize=%u key=(%llu)|%s|\n",
(unsigned long)i,(unsigned long)e.hashkey,(void*)e.data,(unsigned)e.keysize,(unsigned long long)(uintptr_t)e.key,e.key);
running = 0;
} else if(e.flags == DELETED) {
fprintf(stderr,"[%ld] flags=DELETED hashkey=%lu\n",
(unsigned long)i,(unsigned long)e.hashkey);
running = 0;
} else {/*empty*/
if(running == 0)
fprintf(stderr,"[%ld] flags=EMPTY\n",(unsigned long)i);
else if(running == 1)
fprintf(stderr,"...\n");
running++;
2010-06-03 21:24:43 +08:00
}
}
fflush(stderr);
2010-06-03 21:24:43 +08:00
}