Notes On the Internals of the NetCDF-C Library ============================ # Notes On the Internals of the NetCDF-C Library {#intern_head} \tableofcontents This document attempts to record important information about the internal architecture and operation of the netcdf-c library. # 1. Including C++ Code in the netcdf-c Library {#intern_c++} The state of C compiler technology has reached the point where it is possible to include C++ code into the netcdf-c library code base. Two examples are: 1. The AWS S3 SDK wrapper *libdispatch/ncs3sdk.cpp* file. 2. The TinyXML wrapper *ncxml\_tinyxml2.cpp* file. However there are some consequences that must be handled for this to work. Specifically, the compiler must be told that the C++ runtime is needed in the following ways. ## Modifications to *lib\_flags.am* Suppose we have a flag *ENABLE\_XXX* where that XXX feature entails using C++ code. Then the following must be added to *lib\_flags.am* ```` if ENABLE_XXX AM_LDFLAGS += -lstdc++ endif ```` ## Modifications to *libxxx/Makefile.am* The Makefile in which the C++ code is included and compiled (assumed here to be the *libxxx* directory) must have this set. ```` AM_CXXFLAGS = -std=c++11 ```` It is possible that other values (e.g. *-std=c++14*) may also work. # 2. Managing instances of complex data types For a long time, there have been known problems with the management of complex types containing VLENs. This also involves the string type because it is stored as a VLEN of chars. The term complex type refers to any type that directly or recursively references a VLEN type. So an array of VLENS, a compound with a VLEN field, and so on. In order to properly handle instances of these complex types, it is necessary to have function that can recursively walk instances of such types to perform various actions on them. The term "deep" is also used to mean recursive. Two deep walking operations are provided by the netcdf-c library to aid in managing instances of complex structures. * free'ing an instance of the complex type * copying an instance of the complex type. Previously The netcdf-c library only did shallow free and shallow copy of complex types. This meant that only the top level was properly free'd or copied, but deep internal blocks in the instance were not touched. This led to a host of memory leaks and failures when the deep data was effectively shared between the netcdf-c library internally and the user's data. Note that the term "vector" is used to mean a contiguous (in memory) sequence of instances of some type. Given an array with, say, dimensions 2 X 3 X 4, this will be stored in memory as a vector of length 2*3*4=24 instances. The use cases are primarily these. ## nc\_get\_vars Suppose one is reading a vector of instances using nc\_get\_vars (or nc\_get\_vara or nc\_get\_var, etc.). These functions will return the vector in the top-level memory provided. All interior blocks (form nested VLEN or strings) will have been dynamically allocated. Note that computing the size of the vector may be tricky because the strides must be taken into account. After using this vector of instances, it is necessary to free (aka reclaim) the dynamically allocated memory, otherwise a memory leak occurs. So, the recursive reclaim function is used to walk the returned instance vector and do a deep reclaim of the data. Currently functions are defined in netcdf.h that are supposed to handle this: nc\_free\_vlen(), nc\_free\_vlens(), and nc\_free\_string(). Unfortunately, these functions only do a shallow free, so deeply nested instances are not properly handled by them. They are marked in the description as deprecated in favor of the newer recursive function. ## nc\_put\_vars Suppose one is writing a vector of instances using nc\_put\_vars (or nc\_put\_vara or nc\_put\_var, etc.). These functions will write the contents of the vector to the specified variable. Note that internally, the data passed to the nc\_put\_xxx function is immediately written so there is no need to copy it internally. But the caller may need to reclaim the vector of data that was created and passed in to the nc\_put\_xxx function. After writing this vector of instances, and assuming it was dynamically created, at some point it will be necessary to reclaim that data. So again, the recursive reclaim function can be used to walk the returned instance vector and do a deep reclaim of the data. ## nc\_put\_att Suppose one is writing a vector of instances as the data of an attribute using, say, nc\_put\_att. Internally, the incoming attribute data must be copied and stored so that changes/reclamation of the input data will not affect the attribute. Note that this copying behavior is different from writing to a variable, where the data is written immediately. Again, the code inside the netcdf library used to use only shallow copying rather than deep copy. As a result, one saw effects such as described in Github Issue https://github.com/Unidata/netcdf-c/issues/2143. Also, after defining the attribute, it may be necessary for the user to free the data that was provided as input to nc\_put\_att() as in the nc\_put\_xxx functions (previously described). ## nc\_get\_att Suppose one is reading a vector of instances as the data of an attribute using, say, nc\_get\_att. Internally, the existing attribute data must be copied and returned to the caller, and the caller is responsible for reclaiming the returned data. Again, the code inside the netcdf library used to only do shallow copying rather than deep copy. So this could lead to memory leaks and errors because the deep data was shared between the library and the user. ## New Instance Walking API Proper recursive functions were added to the netcdf-c library to provide reclaim and copy functions and use those as needed. These functions are defined in libdispatch/dinstance.c and their signatures are defined in include/netcdf.h. For back compatibility, corresponding "ncaux\_XXX" functions are defined in include/netcdf\_aux.h. ```` int nc_reclaim_data(int ncid, nc_type xtypeid, void* memory, size_t count); int nc_reclaim_data_all(int ncid, nc_type xtypeid, void* memory, size_t count); int nc_copy_data(int ncid, nc_type xtypeid, const void* memory, size_t count, void* copy); int nc_copy_data_all(int ncid, nc_type xtypeid, const void* memory, size_t count, void** copyp); ```` There are two variants. The first two, nc\_reclaim\_data() and nc\_copy\_data(), assume the top-level vector is managed by the caller. For reclaim, this is so the user can use, for example, a statically allocated vector. For copy, it assumes the user provides the space into which the copy is stored. The second two, nc\_reclaim\_data\_all() and nc\_copy\_data\_all(), allows the functions to manage the top-level. So for nc\_reclaim\_data\_all, the top level is assumed to be dynamically allocated and will be free'd by nc\_reclaim\_data\_all(). The nc\_copy\_data\_all() function will allocate the top level and return a pointer to it to the user. The user can later pass that pointer to nc\_reclaim\_data\_all() to reclaim the instance(s). # Internal Changes The netcdf-c library internals are changed to use the proper reclaim and copy functions. This also allows some simplification of the code since the stdata and vldata fields of NC\_ATT\_INFO are no longer needed. Currently this is commented out using the SEPDATA \#define macro. When the bugs are found and fixed, all this code will be removed. ## Optimizations In order to make these functions as efficient as possible, it is desirable to classify all types as to whether or not they contain variable-size data. If a type is fixed sized (i.e. does not contain variable-size data) then it can be freed or copied as a single chunk. This significantly increases the performance for such types. For variable-size types, it is necessary to walk each instance of the type and recursively reclaim or copy it. As another optimization, if the type is a vector of strings, then the per-instance walk can be sped up by doing the reclaim or copy inline. The rules for classifying types as fixed or variable size are as follows. 1. All atomic types, except string, are fixed size. 2. All enum type and opaque types are fixed size. 3. All string types and VLEN types are variable size. 4. A compound type is fixed size if all of the types of its fields are fixed size. Otherwise it has variable size. The classification of types can be made at the time the type is defined or is read in from some existing file. The reclaim and copy functions use this information to speed up the handling of fixed size types. # Warnings 1. The new API functions require that the type information be accessible. This means that you cannot use these functions after the file has been closed. After the file is closed, you are on your own. 2. There is still one known failure that has not been solved; it is possibly an HDF5 memory leak. All the failures revolve around some variant of this .cdl file. The proximate cause of failure is the use of a VLEN FillValue. ```` netcdf x { types: float(*) row_of_floats ; dimensions: m = 5 ; variables: row_of_floats ragged_array(m) ; row_of_floats ragged_array:_FillValue = {-999} ; data: ragged_array = {10, 11, 12, 13, 14}, {20, 21, 22, 23}, {30, 31, 32}, {40, 41}, _ ; } ```` # 3. Inferring File Types As described in the companion document -- docs/dispatch.md -- when nc\_create() or nc\_open() is called, it must figure out what kind of file is being created or opened. Once it has figured out the file kind, the appropriate "dispatch table" can be used to process that file. ## The Role of URLs Figuring out the kind of file is referred to as model inference and is, unfortunately, a complicated process. The complication is mostly a result of allowing a path argument to be a URL. Inferring the file kind from a URL requires deep processing of the URL structure: the protocol, the host, the path, and the fragment parts in particular. The query part is currently not used because it usually contains information to be processed by the server receiving the URL. The "fragment" part of the URL may be unfamiliar. The last part of a URL may optionally contain a fragment, which is syntactically of this form in this pseudo URL specification. ```` :///?# ```` The form of the fragment is similar to a query and takes this general form. ```` '#'=&=&... ```` The key is a simple name, the value is any sequence of characters, although URL special characters such as '&' must be URL encoded in the '%XX' form where each X is a hexadecimal digit. An example might look like this non-sensical example: ```` https://host.com/path#mode=nczarr,s3&bytes ```` It is important to note that the fragment part is not intended to be passed to the server, but rather is processed by the client program. It is this property that allows the netcdf-c library to use it to pass information deep into the dispatch table code that is processing the URL. ## Model Inference Inputs The inference algorithm is given the following information from which it must determine the kind of file being accessed. ### Mode The mode is a set of flags that are passed as the second argument to nc\_create and nc\_open. The set of flags is define in the netcdf.h header file. Generally it specifies the general format of the file: netcdf-3 (classic) or netcdf-4 (enhanced). Variants of these can also be specified, e.g. 64-bit netcdf-3 or classic netcdf-4. In the case where the path argument is a simple file path, using a mode flag is the most common mechanism for specifying the model. ### Path The file path, the first argument to nc\_create and nc\_open, Can be either a simple file path or a URL. If it is a URL, then it will be deeply inspected to determine the model. ### File Contents When the contents of a real file are available, the contents of the file can be used to determine the dispatch table. As a rule, this is likely to be useful only for *nc\_open*. It also requires access to functions that can open and read at least the initial part of the file. As a rule, the initial small prefix of the file is read and examined to see if it matches any of the so-called "magic numbers" that indicate the kind of file being read. ### Open vs Create Is the file being opened or is it being created? ### Parallelism Is parallel IO available? ## Model Inference Outputs The inferencing algorithm outputs two pieces of information. 1. model - this is used by nc\_open and nc\_create to choose the dispatch table. 2. newpath - in some case, usually URLS, the path may be rewritten to include extra information for use by the dispatch functions. The model output is actually a struct containing two fields: 1. implementation - this is a value from the NC\_FORMATX\_xxx values in netcdf.h. It generally determines the dispatch table to use. 2. format -- this is an NC\_FORMAT\_xxx value defining, in effect, the netcdf-format to which the underlying format is to be translated. Thus it can tell the netcdf-3 dispatcher that it should actually implement CDF5 rather than standard netcdf classic. ## The Inference Algorithm The construction of the model is primarily carried out by the function *NC\_infermodel()* (in *libdispatch/dinfermodel.c). It is given the following parameters: 1. path -- (IN) absolute file path or URL 2. modep -- (IN/OUT) the set of mode flags given to *NC\_open* or *NC\_create*. 3. iscreate -- (IN) distinguish open from create. 4. useparallel -- (IN) indicate if parallel IO can be used. 5. params -- (IN/OUT) arbitrary data dependent on the mode and path. 6. model -- (IN/OUT) place to store inferred model. 7. newpathp -- (OUT) the canonical rewrite of the path argument. As a rule, these values are used in the this order of preference to infer the model. 1. file contents -- highest precedence 2. url (if it is one) -- using the "mode=" key in the fragment (see below). 3. mode flags 4. default format -- lowest precedence The sequence of steps is as follows. ### URL processing -- processuri() If the path appears to be a URL, then it is parsed and processed by the processuri function as follows. 1. Protocol -- The protocol is extracted and tested against the list of legal protocols. If not found, then it is an error. If found, then it is replaced by a substitute -- if specified. So, for example, the protocol "dods" is replaced the protocol "http" (note that at some point "http" will be replaced with "https"). Additionally, one or more "key=value" strings is appended to the existing fragment of the url. So, again for "dods", the fragment is extended by the string "mode=dap2". Thus replacing "dods" does not lose information, but rather transfers it to the fragment for later use. 2. Fragment -- After the protocol is processed, the initial fragment processing occurs by converting it to a list data structure of the form ```` {,,,,,....} ```` ### Macro Processing -- processmacros() If the fragment list produced by processuri() is non-empty, then it is processed for "macros". Notice that if the original path was not a URL, then the fragment list is empty and this processing will be bypassed. In any case, It is convenient to allow some singleton fragment keys to be expanded into larger fragment components. In effect, those singletons act as macros. They can help to simplify the user's URL. The term singleton means a fragment key with no associated value: "#bytes", for example. The list of fragments is searched looking for keys whose value part is NULL or the empty string. Then the table of macros is searched for that key and if found, then a key and values is appended to the fragment list and the singleton is removed. ### Mode Inference -- processinferences() This function just processes the list of values associated with the "mode" key. It is similar to a macro in that certain mode values are added or removed based on tables of "inferences" and "negations". Again, the purpose is to allow users to provide simplified URL fragments. The list of mode values is repeatedly searched and whenever a value is found that is in the "modeinferences" table, then the associated inference value is appended to the list of mode values. This process stops when no changes occur. This form of inference allows the user to specify "mode=zarr" and have it converted to "mode=nczarr,zarr". This avoids the need for the dispatch table code to do the same inference. After the inferences are made, The list of mode values is again repeatedly searched and whenever a value is found that is in the "modenegations" table, then the associated negation value is removed from the list of mode values, assuming it is there. This process stops when no changes occur. This form of inference allows the user to make sure that "mode=bytes,nczarr" has the bytes mode take precedence by removing the "nczarr" value. Such illegal combinations can occur because of previous processing steps. ### Fragment List Normalization As the fragment list is processed, duplicates appear with the same key. A function -- cleanfragments() -- is applied to clean up the fragment list by coalesing the values of duplicate keys and removing duplicate key values. ### S3 Rebuild If the URL is determined to be a reference to a resource on the Amazon S3 cloud, then the URL needs to be converted to what is called "path format". There are four S3 URL formats: 1. Virtual -- ````https://.s3..amazonaws.com/```` 2. Path -- ````https://s3..amazonaws.com//```` 3. S3 -- ````s3:///```` 4. Other -- ````https:////```` The S3 processing converts all of these to the Path format. In the "S3" format case it is necessary to find or default the region from examining the ".aws" directory files. ### File Rebuild If the URL protocol is "file" and its path is a relative file path, then it is made absolute by prepending the path of the current working directory. In any case, after S3 or File rebuilds, the URL is completely rebuilt using any modified protocol, host, path, and fragments. The query is left unchanged in the current algorithm. The resulting rebuilt URL is passed back to the caller. ### Mode Key Processing The set of values of the fragment's "mode" key are processed one by one to see if it is possible to determine the model. There is a table for format interpretations that maps a mode value to the model's implementation and format. So for example, if the mode value "dap2" is encountered, then the model implementation is set to NC\_FORMATX\_DAP2 and the format is set to NC\_FORMAT\_CLASSIC. ### Non-Mode Key Processing If processing the mode does not tell us the implementation, then all other fragment keys are processed to see if the implementaton (and format) can be deduced. Currently this does nothing. ### URL Defaults If the model is still not determined and the path is a URL, then the implementation is defaulted to DAP2. This is for back compatibility when all URLS implied DAP2. ### Mode Flags In the event that the path is not a URL, then it is necessary to use the mode flags and the isparallel arguments to choose a model. This is just a straight forward flag checking exercise. ### Content Inference -- check\_file\_type() If the path is being opened (as opposed to created), then it may be possible to actually read the first few bytes of the resource specified by the path and use that to determine the model. If this succeeds, then it takes precedence over all other model inferences. ### Flag Consistency Once the model is known, then the set of mode flags is modified to be consistent with that information. So for example, if DAP2 is the model, then all netcdf-4 mode flags and some netcdf-3 flags are removed from the set of mode flags because DAP2 provides only a standard netcdf-classic format. # 4. Adding a Standard Filter The standard filter system extends the netcdf-c library API to support a fixed set of "standard" filters. This is similar to the way that deflate and szip are currently supported. For background, the file filter.md should be consulted. In general, the API for a standard filter has the following prototypes. The case of zstandard (libzstd) is used as an example. ```` int nc_def_var_zstandard(int ncid, int varid, int level); int nc_inq_var_zstandard(int ncid, int varid, int* has_filterp, int* levelp); ```` So generally the API has the ncid and the varid as fixed, and then a list of parameters specific to the filter -- level in this case. For the inquire function, there is an additional argument -- has_filterp -- that is set to 1 if the filter is defined for the given variable and is 0 if not. The remainder of the inquiry parameters are pointers to memory into which the parameters are stored -- levelp in this case. It is important to note that including a standard filter still requires three supporting objects: 1. The implementing library for the filter. For example, libzstd must be installed in order to use the zstandard API. 2. A HDF5 wrapper for the filter must be installed in the directory pointed to by the HDF5_PLUGIN_PATH environment variable. 3. (Optional) An NCZarr Codec implementation must be installed in the the HDF5_PLUGIN_PATH directory. ## Adding a New Standard Filter The implementation of a standard filter must be loaded from one of several locations. 1. It can be part of libnetcdf.so (preferred), 2. it can be loaded as part of the client code, 3. or it can be loaded as part of an external library such as libccr. However, the three objects listed above need to be stored in the HDF5_PLUGIN_DIR directory, so adding a standard filter still requires modification to the netcdf build system. This limitation may be lifted in the future. ### Build Changes In order to detect a standard library, the following changes must be made for Automake (configure.ac/Makefile.am) and CMake (CMakeLists.txt) #### Configure.ac Configure.ac must have a block that similar to this that locates the implementing library. ```` # See if we have libzstd AC_CHECK_LIB([zstd],[ZSTD_compress],[have_zstd=yes],[have_zstd=no]) if test "x$have_zstd" = "xyes" ; then AC_SEARCH_LIBS([ZSTD_compress],[zstd zstd.dll cygzstd.dll], [], []) AC_DEFINE([HAVE_ZSTD], [1], [if true, zstd library is available]) fi AC_MSG_CHECKING([whether libzstd library is available]) AC_MSG_RESULT([${have_zstd}]) ```` Note the the entry point (*ZSTD_compress*) is library dependent and is used to see if the library is available. #### Makefile.am It is assumed you have an HDF5 wrapper for zstd. If you want it to be built as part of the netcdf-c library then you need to add the following to *netcdf-c/plugins/Makefile.am*. ```` if HAVE_ZSTD noinst_LTLIBRARIES += libh5zstd.la libh5szip_la_SOURCES = H5Zzstd.c H5Zzstd.h endif ```` # Need our version of szip if libsz available and we are not using HDF5 if HAVE_SZ noinst_LTLIBRARIES += libh5szip.la libh5szip_la_SOURCES = H5Zszip.c H5Zszip.h endif #### CMakeLists.txt In an analog to *configure.ac*, a block like this needs to be in *netcdf-c/CMakeLists.txt*. ```` FIND_PACKAGE(Zstd) set_std_filter(Zstd) ```` The FIND_PACKAGE requires a CMake module for the filter in the cmake/modules directory. The *set_std_filter* function is a macro. An entry in the file config.h.cmake.in will also be needed. ```` /* Define to 1 if zstd library available. */ #cmakedefine HAVE_ZSTD 1 ```` ### Implementation Template As a template, here is the implementation for zstandard. It can be used as the template for adding other standard filters. It is currently located in *netcdf-d/libdispatch/dfilter.c*, but could be anywhere as indicated above. ```` #ifdef HAVE_ZSTD int nc_def_var_zstandard(int ncid, int varid, int level) { int stat = NC_NOERR; unsigned ulevel; if((stat = nc_inq_filter_avail(ncid,H5Z_FILTER_ZSTD))) goto done; /* Filter is available */ /* Level must be between -131072 and 22 on Zstandard v. 1.4.5 (~202009) Earlier versions have fewer levels (especially fewer negative levels) */ if (level < -131072 || level > 22) return NC_EINVAL; ulevel = (unsigned) level; /* Keep bit pattern */ if((stat = nc_def_var_filter(ncid,varid,H5Z_FILTER_ZSTD,1,&ulevel))) goto done; done: return stat; } int nc_inq_var_zstandard(int ncid, int varid, int* hasfilterp, int *levelp) { int stat = NC_NOERR; size_t nparams; unsigned params = 0; int hasfilter = 0; if((stat = nc_inq_filter_avail(ncid,H5Z_FILTER_ZSTD))) goto done; /* Filter is available */ /* Get filter info */ stat = nc_inq_var_filter_info(ncid,varid,H5Z_FILTER_ZSTD,&nparams,NULL); if(stat == NC_ENOFILTER) {stat = NC_NOERR; hasfilter = 0; goto done;} if(stat != NC_NOERR) goto done; hasfilter = 1; if(nparams != 1) {stat = NC_EFILTER; goto done;} if((stat = nc_inq_var_filter_info(ncid,varid,H5Z_FILTER_ZSTD,&nparams,¶ms))) goto done; done: if(levelp) *levelp = (int)params; if(hasfilterp) *hasfilterp = hasfilter; return stat; } #endif /*HAVE_ZSTD*/ ```` # Point of Contact {#intern_poc} *Author*: Dennis Heimbigner
*Email*: dmh at ucar dot edu
*Initial Version*: 12/22/2021
*Last Revised*: 01/25/2022