HDF5 FAQ -- Questions About the Software

INSTALLING/BUILDING HDF5

(For Fortran issues, see FORTRAN)

Information on building and using HDF/HDF5 on Windows
Having problems building an application with pre-built libraries.
Is the HDF5 C source C99 compliant? Is it C89 compatible ?
How can you determine what compiler/flags are used by an HDF5 installation?
The mtime test fails with the message 'Old modification time incorrect.', when building with an unsupported platform/compiler
Can't open shared library: <path&gr;/lib...s#.0
Gets -DPIC error building HDF5 on AIX w/F90
Problems installing Parallel HDF5 on IBM Regatta (with AIX5) (see PARALLEL HDF5)
Tests fail when building HDF5 on HP-UX 10.20
Building on MAC OSX, the symbols restFP and saveFP come up as undefined. Why?
Float to Conversion Tests Fail on AMD with Intel compiler. Why?
Building 5-1.6.2(3) using Intel 8.1, get ULLONG_MAX error.
AIX Configure failure: "...config.sub: too many arguments"
Using Purify on HDF5 library, get uninitialized memory read error
When Building HDF5, the Object Header test, "Testing message deletion", fails.
Building on AIX 64-bit, get: ERROR: No csects or exported symbols have been saved.

JAVA

Java error: can't find HDF5 file format
How do you read/write a string dataset in Java?
Data values are reversed/swapped/transposed in HDFView. Why?
Do you support Java 64-bit with HDF-JAVA?
What are the limitations of HDF Java interface ?
What kind of palettes are supported in HDFView?
java.lang.UnsatisfiedLinkError: no jhdf5 in java.library.path
Will you be adding a pure Java interface to HDF5?
Installing HDFView, cannot find shared object files
What are the issues regarding replacing the JNI?
Is parallel HDF5 supported with java?
Can HDFView handle bit-field data?
Can't get HDFView to work on HP-UX
HDFView installs properly on Mac but crashes when selected
HDFView: connection time out errors running behind a firewall
Will HDFView be supporting variable length strings soon?
How do you increase the Java Virtual machine memory?
Get EXCEPTION_ACCESS_VIOLATION when more than 1024MB is allocated to the Java Virtual machine.
How to workaround error Exception - dataset too big ?
Error - variable HDF5CDataTypes not found
Do you have an example of writing/reading compound datatypes in java?
How do you insert JAR files into JBuilder ?

PARALLEL HDF5

What do you need to run Parallel HDF5?
What performance can you expect from Parallel HDF5?
Performance: Parallel I/O with Chunking Storage
Does HDF5 support compression with parallel HDF5 ? If not, why ?
Does Parallel HDF5 support chunking ?
Can you run parallel HDF5 and the threadsafe feature together ? What about Parallel HDF5 and C++?
How do you write to attributes independently ?
Does Parallel HDF5 support variable length datatypes ?
Most HDF5 calls to not make a statement about whether they are being called collectively or independently. How are they being called?
Problems installing Parallel HDF5 on IBM Regatta (with AIX5)
How to write and NOT to write compound datasets usingF90 in Parallel HDF5
MPI ... failed: array services not available
How do you write data when one process doesn't have or need to write data ?
How do you build HDF5 on BlueGene/L?
How do you set up HDF5 so only one MPI rank 0 process does I/O ?
How do you configure HDF5 to create separate files for each compute node in a cluster ?
Also see INSTALLING/BUILDING HDF5 questions.

PLATFORM SPECIFIC

PROPERTIES

With HDF5-1.6.0-post*, a fix was added for using H5Pset_istore_k and H5Pget_istore_k. This fix required a change to the HDF5 format. What are the implications of this ?
What function do you use to get compression level information?
How do you use the stream driver in HDF5-1.6.2?
How do you work with a file created with the file family feature?
Can you work with an HDF5 file in memory ?

UTILITIES

How do you use the h5cc (h5fc) utility ?
Why is h5dump slower than h5ls?
Can you add an option to h5dump or h5ls to print the version of a file ?

ATTRIBUTES

When would you use attributes vs. datasets for your metadata ?

Datasets (and groups) are considered to be "primary" objects. Objects that are not primary are the datatype, dataspace, and attributes. An attribute is not considered a primary object because attributes are stored in an object's header.
There is a 64k limit for an attribute.
Attributes are not extendible.
You cannot use compression with attributes.
You cannot do partial I/O operations on attributes (such as hyperslab selections).

In general using attributes is convenient and straightforward, but if any of the above items may be an issue, then it may be preferable to use datasets for your metadata.

When would you use attributes vs. compact datasets ?

  Compact Storage RFC
 
Small 
Data Tuning RFC

An attribute cannot be shared between several objects. If you store the data in a compact dataset, other objects can use attributes with the object reference datatype to point to the compact dataset. This mechanism allows "sharing" the data stored in the compact dataset between the objects.

I/0 speed should be the same for both attributes and compact datasets since it will be a memory operation. Please remember that you will pay a price while opening/closing the file if you store information in the objects' headers. An application will benefit from the attribute or compact storage mechanism only if it accesses and updates the object state many times during the life of an application. If it is done just a few times, the benefit is questionable.

C++

Does C++ support stream operators?

No, not yet. We intend to add support for them, but since they are a convenience feature, this has not been high in priority.

Does it do IO via standard library containers?

No, we have not looked at this yet, but suspect it will be complicated to implement.

DATASETS

How do I find out what compression has been used to write a dataset?

Public filters are identified by a unique integer ID listed in H5Zpublic.h (currently only H5Z_FILTER_DEFLATE). See doc/html/Filters.html for more info (the transient filters it mentions have never been implemented).

You don't need to know what filters were used to write a particular dataset -- you only have to make sure that they have been registered with H5Zregister() before reading.

How do I create a chunked/compressed dataset?

Chunking and Extendible Dataset example

How do I read/write a subset or sub-sample of a dataset?

Hyperslabs, including repeated blocks as well as strides
Unions of hyperslabs
Sets of points

See the Hyperslab selection and Point selection examples in the HDF5 tutorial.

When you specify memspace and filespace for H5Dwrite and H5Dread does it mean it is allocating memory for both the dataset and memory space (ie. twice the size of dataset) ?

Also, you can adjust the 1MB default conversion buffer size. (see H5Pset_buffer)

DATASPACE

Can you subset or select hyperslabs from a compressed dataset?

Yes. You must use chunking in order to do this. With HDF5-1.4.4, the implementation of the I/O pipeline and caching may cause the same chunk to be brought to memory several times when hyperslabs of data are read from the file. That may slow down the performance.

DATATYPES

Why was the H5T_ARRAY created ? What is it for ?

Previously, you had to create a compound datatype if you wanted to use an array-like datatype for creating a dataset. This was fine if you really wanted to use the array as a field in a compound datatype, but there were developers who wanted to just have a "plain" array (without the compound datatype wrapping) as a datatype for their dataset. We decided to obsolete the array fields in compound datatypes and promote arrays to a "first-class" datatype. This allowed applications to create and use them without involving a compound datatype. Along with being more "obvious" about the intentions of the datatype, array datatypes are also somewhat more efficient in certain circumstances, as mentioned above.

How can you tell if two datasets share their (named, committed) datatype?

You can use the H5Gget_objinfo function to retrieve the "stat" information for each named datatype. Then, comparing the fileno and objno fields in the H5G_stat_t struct for each type should tell you if the two named datatypes refer to the same object in the file.

How do I create a String attribute or dataset?

hid_t strtype; /* HDF5 data type id. */

if((strtype=H5Tcopy(H5T_C_S1))<0) {
return -1;
}
/* the length */
if((H5Tset_size(strtype,size))<0) {
return -1;
}
/* optional--pad with zero or space */
if((H5Tset_strpad(strtype,pad))<0){
return -1;
}

/* use the strtype in H5Acreate  or H5Dcreate */

http://www.hdfgroup.uiuc.edu/UserSupport/code-examples/

How do you create datasets with a time datatype (class of H5T_TIME)?

h5time.c

When do you use pre-defined standard vs. native datatypes?

Datatypes Table

Following is what you must do (in HDF5-1.4) when creating a general purpose tool for reading HDF5 datasets. You should check both the class and size of the datatype for the dataset and also the size of the native C types for a particular machine. (With HDF5-1.6, we will be simplifying these steps by adding the H5Tget_native_type function to reconstruct a datatype based on the native memory datatype.)

dset=H5Dopen(...);
dtype=H5Dget_type(dset);
class=H5Tget_class(dtype);
size=H5Tget_size(dtype);

switch(class) {
	case H5T_INTEGER:
		if(size==sizeof(long long))
			mem_dtype=H5T_NATIVE_LLONG;
		else if(size==sizeof(long)
			mem_dtype=H5T_NATIVE_LONG;
		else if(size==sizeof(int)
			mem_dtype=H5T_NATIVE_INT;
		else if(size==sizeof(short)
			mem_dtype=H5T_NATIVE_SHORT;
		else 
			mem_dtype=H5T_NATIVE_CHAR;
		break;

	case H5T_FLOAT:
		if(size==sizeof(long double))
			mem_dtype=H5T_NATIVE_LDOUBLE;
		else if(size==sizeof(double)
			mem_dtype=H5T_NATIVE_DOUBLE;
		else 
			mem_dtype=H5T_NATIVE_FLOAT;
		break;
}

It may be useful to have the above switch statement in a simple function that returns the appropriate native datatype. Then that function could be used inside a wrapper which correctly handled compound, array and variable-length datatypes.

Users may also want to make certain that they malloc the appropriate amount of space needed to store the memory datatype, as well as making sure that they read in and access the data as the correct C type.

Does HDF5 support a boolean datatype ?

No. HDF5 is written in C, which does not have a boolean datatype. Use an integer type and interpret your data according to your rules.

What are the plusses and minusses of using compound datatypes ?

h5dread/write_f

There are some issues you may run into. First of all, applications that support HDF5 may not fully support compound datatypes. We only support them minimally in our HDF Java Viewer, because java doesn't handle them well.

There have been problems with including variable length datatypes in a compound datatype. Performance is slow and a couple of users have also encountered some other problems. We plan to address any problems, though.

Information on using bitfields in HDF5

bitfield.c

test/dtypes.c

What function can be used to create a bitfield ?
The H5Tset_precision() routine determines the number of bits in a datatype that are significant within it.

What are the limits on the number of bits ?
Up to the size of the datatype that contains it (which is defined for up to 64-bit datatypes currently)

How are these stored then? Any sort of padding or what?
We currently do not pack them, so a 13-bit field in a 32-bit datatype still takes up 4 bytes of space. This is not ideal, but it is a fairly complicated problem to pack the bits on disk (in light of using bitfields in compound, array and variable-length datatypes mostly). Eventually we should fix this.

How would you use a float pointer in a compound datatype ?

    typedef struct xxx_t {
        int    x;
        short  y;
        float * z;
    } xxx_t

hvl_t

There is no [easy] way to determine the end of an array of floating-point numbers (or other non-character string sequences), so the hvl_t struct must be used to provide the length of the sequence.

H5Tenum_insert returns error when type has different endianess

The best way to avoid the problem is to use the native type for the base type in calling H5Tenum_insert. In this example, it will be "char":

  int status = H5.H5Tenum_insert(booleanEnum, "true", new char[] {1});

When reading compound data from file w/different compound field name, the data is different for this field.

The right way to read data into memory is to call H5Dget_type and H5Tget_native_type to figure out the data type in memory. (Another way of course, is simply to avoid using wrong names. :)

What is the proper way to allocate memory when reading a variable length datatype?

In the case of a VL type, the HDF5 library allocates a buffer and the user's application has to free it. There is no special call for a character string, so just use a C free. For more complex VL types, use H5Dvlen_reclaim. See:

    http://www.hdfgroup.uiuc.edu/UserSupport/code-examples/hamlet.c

Is there a limit on the number of fields allowed in a compound datatype ?

If you are using HDF5 1.8.0 or previous releases, there is a limit on the number of fields you can have in a compound datatype. This is due to the 64K limit on object header messages, into which datatypes are encoded. (However, you can create a lot of fields before it will fail. One user was able to create up to 1260 fields in a compound datatype before it failed.)

EXTERNAL LIBRARIES

I build the SZIP library from source using the Intel compiler (icc), but the gentest fails when I run `make check`.

Build the SZIP library with the gcc compiler. We tested that it can be used when building HDF5 with the Intel compilers.
Disable optimization.

How to detect the SZIP encoder at run time

strings

grep

  strings libsz.a |grep ENCODE

Another way is to write an application that checks whether the SZIP library included with HDF5 is encoder-enabled or not. Use the H5Zget_filter_info function, as follows:

  #include "hdf5.h"

  int main(void)
  {
      herr_t   status;
      unsigned int filter_config_flags;

      status =H5Zget_filter_info(H5Z_FILTER_SZIP, &filter_config_flags);

      if ((filter_config_flags & H5Z_FILTER_CONFIG_ENCODE_ENABLED) == 0) 
        printf("SZIP encoding is disabled.\n");
      else printf ("SZIP encoding is enabled.\n");
  }

ERROR

The error report prints out full path for file name instead of file name only

The HDF5 library simply prints out the C macro __FILE__ as the file name. Each compiler has its own interpretation: Some compilers print the file name only; some print the full path name; others, just the relevant path name.

The HDF5 library has no control over this.

How do you turn off error messages ?

H5Eset_auto

FILE

Can you open a file, open a group, close the file, and continue working on a group ?

Yes, that is explicitly supported by the library. Once you are no longer in need of the file identifier, you can close the file.

How can I resolve file access problems due to objects being left open?

There are some things you can do. You can either close everything automatically, or get the number of open objects and then close them:

We have a file access property list that you can use to do a 'strong' close of a file. See the function: H5Pset_fclose_degree.
See the example program h5close.c.
You can call H5close, and that will automatically close everything.
You can call H5Fget_obj_count to get the number of open object identifiers for an open file.
You can call H5Fget_obj_ids to get the list of open object identifiers.
See the example program: h5ckopen.c

FORTRAN

How do you create a dataset with a 16-bit datatype in F90 ?

h5tset_size_f

Currently the F90 APIs do not support INTEGER*2 in memory.

See the example, h516bit.f90.

How do you build HDF5 using gcc and either Intel or Lahey Fortran ?

unresolved __fixunsdfdi symbol

Use the,

     setenv LIBS "-lgcc_s"  (if using dynamic linking)
         or
     setenv LIBS "-lgcc"    (if using static linking.  For example, 
                             if using ifort with the "-static" option)

configure

fortran/test/Makefile

fortran/examples/Makefile

If you use h5cc or h5fc, you will also need to edit them and add "-lgcc_s" or "-lgcc" to them.

Can you build shared Fortran libraries in HDF5 ?

Shared Fortran libraries are not supported in the HDF5 1.6 branch, but they are supported for some platforms in the HDF5 1.8 branch. Refer to the Supported Configuration Features Summary in the 1.8.0 release notes for more details.

GENERAL

Do you have example code of reading an HDF5 file?


   h5_info.c

Can you delete objects in an HDF5 file ? If yes, how ?

HDFView

h5compact.c

In a future release of HDF5 we will include support for managing the free space in a file.

Does HDF5 support meshes ?

See the HDF5 Mesh API web page.

Does HDF5 support netCDF ?

netCDF 4: Merging the NetCDF and HDF5 Libraries

How do you create files over 2GB ?

You can use the file access property list to set up a file family driver. Your HDF5 file will be split into a "family" of files of the same size.

Another way is to use the external file feature. This is controlled by the Dataset Creation Property list. You could store the datasets in an HDF5 file in separate external files of less than 2GB.

For examples of using File Access and Dataset Creation property lists, see the Property tutorial topic in the Advanced section of the HDF5 Tutorial.

With Windows -32 bit, HDF5 can handle files greater than 2GB by use of the native datatype. For example, using H5T_NATIVE_LLONG instead of H5T_NATIVE_LONG.

Is HDF5 threadsafe? Multi-threaded? Explain.

The current implementation of the threadsafe HDF5 serializes all HDF5 calls. It provides thread safety but is not thread- efficient. We have a design plan to make it more thread-efficient but currently don't have the resources to implement it.

If you use only 1 thread to open a file, define the datasets, use only fixed dimension datasets (that is, no chunked storage or variable length types, ...), then HDF5 has all the data locations defined within the file. After that, you can use multiple threads to do read/write of the array data (in concept).

For further information on thread-safe HDF5, see:

threadsafe page/

Why are my files sizes different, if I open an HDF5 file more than once rather than writing the data out in one call?

Currently, all metadata below a certain threshold size (2KB by default) will cause the library to allocate a block of that threshold size (i.e. 2KB) to store the metadata in, anticipating that more metadata will be added to the file soon and could be sub-allocated from that block. A program which doesn't add more metadata to the block will cause the rest of that block to be wasted in the file because the library doesn't currently remember the free space in the file from one file open to the next.

The threshold block size in the library can be changed with a call to H5Pset_meta_block_size (and H5Pset_small_data_block_size, in libraries which have it - should be in the 1.4.4 release) like so:

	fapl_id=H5Pcreate(H5P_FILE_ACCESS);
	printf ("H5Pcreate returns: %i\n", fapl_id);

	status = H5Pset_meta_block_size (fapl_id,0);
	printf ("H5Pset_meta_block_size returns: %i\n", status);

#ifdef WHEN_ITS_AVAILABLE
	status = H5Pset_small_data_block_size (fapl_id,0);
	printf ("H5Pset_small_data_block_size returns: %i\n", status);
#endif /* WHEN_ITS_AVAILABLE */

Performance-wise, it would be better to hold the file open as long as possible and not to adjust the block size, but users will have to decide whether file size or I/O performance is their overall goal.

I'd like to access an HDF5 file without using the HDF5 library. Is this possible?

Although it is possible to parse through an HDF5 file using just the file format documentation as a guide, it is strongly recommended that you use the HDF5 library to access HDF5 files instead. The algorithms and data structures stored in an HDF5 file can be complex and difficult to understand well enough to parse correctly. Additionally, there are certain requirements on the structure of the data structures (the B-trees, for example) that may not be obvious from a static representation of them in the file and may not be fulfilled by indiscriminate operations on them. There are also some third-party data structures stored in the file that are not documented in the HDF5 file format documentation, such as the format of compressed data using the deflate algorithm.

Will data manipulation routines be added to HDF5?

No, this is left up to the user. There are many packages available, including BLAS and LINPACK for this.

Given an object binary file such as libhdf5.a or a.out, how can I easily determine which version of HDF5 is being used (aka linked)?

% strings libhdf5.a | grep "HDF5 library version:"
% strings a.out | grep "HDF5 library version:"

Given a library file such as libxyz.a that calls HDF5 functions, how can I easily determine which version of HDF5 is being used to build (aka compile) libxyz.a?

  /* C automatically merges two adjacent strings into one. */
  /* Use non static char string so that it is included always. */
  char     XYZ_built_with_H5_lib_vers_info_g[] = "XYZ built with " H5_VERS_INFO;

 % strings libxyz.a | grep "HDF5 library version:"
 XYZ built with HDF5 library version: 1.4.4

My HDF5-1.4 library cannot read files created with 5-1.6.0

Prior to 5-1.4.5-post2, HDF5 issued an error and failed to open objects with unknown header messages (for example, metadata about an object added in a later version of the library). It should have just ignored the unknown message and proceeded to open the object.

Can you read an HDF5 while it is being written to?

Here's what needs to be done:

Call H5Fflush() from the writing process.
The writing process _must_ wait until either a copy of the file is made for the reading process, or the reading process is done accessing the file (so that more data isn't written to the file, giving the reader an inconsistent view of the file's state).
The reading process _must_ open the file (it cannot have the file open before the writing process flushes its information, or it runs the risk of having its data cached in memory being incorrect with respect to the state of the file) and read whatever information it wants.
The reading process must close the file.
The writing process may now proceed to write more data to the file.

There must also be some mechanism for the writing process to signal the reading process that the file is ready for reading and some way for the reading process to signal the writing process that the file may be written to again.

Performance-wise, how does HDF5 compare to a relational database?

It doesn't have indexing capabilities, though we are working on some limited features. See the HDF5_Prototype_Indexing_Requirements for details.

HDF5 was designed to complement DBs and not to compete with them.

If you run an application twice on the same machine will it produce identical HDF5 files ?

I thought that netCDF4 would, like netCDF3, use deterministic algorithms without any date-stamps within the file, and thus produce BFB files. Apparently I am wrong.

To determine whether files were BFB I checked their SHA1 sums. netCDF3 produces BFB files and netCDF4 does not. BFB output files make models easier to debug, so it would be helpful if netCDF4 continued the netCDF3 BFB "tradition". Is this possible? Am I missing something? Is HDF5 the culprit?

Response: If you turn off the create/modify/access time tracking for objects created (with the H5Pset_obj_track_times() routine), everything should be bit-for-bit reproducible. Coincidentally, it makes accessing those objects faster and the size of their metadata smaller also. You do lose the ability to know when the object was created/modified/accessed.

GROUPS

H5Gget_obj_info: How do you tell the difference between a soft and hard link? If my reader reads an HDF5 file with a loop in it, then my code goes into an infinite loop, also.

Right now what you have to do is traverse all the objects in the file. For any object for which the link count is > 1, record it in a table, using the 'objno' as a key. (See H5Gget_objinfo) The first time you see it, there will be no entry in the table, subsequent visits will find an entry.

When you hit a group that you have already visited (it's in the table described above), you are about to loop, so stop.

If all you want is to avoid loops, then you only need a table of objects with link count > 1, so you know that you have visited them.

If you need a table of contents for the whole file, then collect all the info you need, and use the objno as a key to avoid loops.

The following example illustrates how this could be done. However, this code is not considered "finished" or exemplary code:

h5_git.c

Iterating (H5Giterate) takes a long time when you have lots of objects. Can this be sped up?

Iterating does take a long time, and this is something we are trying to speed up (12/19/02). An alternative might be to store the names of the objects in a dataset, reading this and then accessing the object by its name. You could use Object References to do this.

IDENTIFIERS

How do you get the name of an object opened with H5Rdereference?

H5Rdereference

H5Iget_name

H5Rdereference

However, if you need to compare two object identifiers, there is a workaround. You can determine if two object identifiers point to the same object, by using H5Gget_objinfo:

hid_t  obj1, obj2;
H5G_stat_t stat1, stat2;

H5Gget_objinfo(obj1, ".", flag, &stat1);
H5Gget_objinfo(obj2, ".", flag, &stat2);

stat1

stat2

Although there are issues with creating a function that will return the name of a dereferenced object, we are planning on adding this function to HDF5. For more information, see:

  derefobjname.txt

IMAGES AND PALETTES

How do you store a true color image in HDF5 ?

For plane interlace the data will be store as: [pixel components][height][width]

Refer to the Image and Palette Specification for further details.

What kind of palettes are supported?

Image and Palette Specification

You can create your own image palette. An image palette in HDF5 is just another dataset. For example, if you were only interested in values between 50 and 100, you could create a palette such that all values over 100 were white and all values smaller than 50 to be black. Something like this:

index    red    green   blue
0          0       0         0
...
49        0        0        0
50  whatever color you want
...
100 whatever color you want
102      255     255    255
...
255      255     255    255

If you have an X by Y image in Z bands how would you store that in HDF5 ?

We don't address using bands with the Image Specification. You would have to store each band as a separate image.

How do you save an image made from (r,g,b) floating point values?

See the implementation of the HDF5 High Level function, H5IMmake_image_24bit, in the HDF5 source code. To save an image made from (r,g,b) floating point values, just replace the following call in this function:

 if ( H5LTmake_dataset( loc_id, dset_name, rank, dims, H5T_NATIVE_UCHAR, buffer
) < 0 )
  return -1;

 if ( H5LTmake_dataset( loc_id, dset_name, rank, dims, H5T_NATIVE_FLOAT, buffer
) < 0 )
  return -1;

INSTALLING/BUILDING HDF5

Having problems building an application with pre-built libraries.

Below is the list of steps that we hope will help you to successfully use the prebuilt HDF5 libraries:

Download the prebuilt binaries for your desired platform from the HDF5 FTP Site, and install them on your system. We will refer to the directory where HDF5 is installed as /HDF5_INSTALL.
Run the h5redeploy script in the /HDF5_INSTALL/bin directory to modify the h5cc/h5fc/h5c++ scripts to point to the /HDF5_INSTALL/... directories.
Check the libhdf5.settings file under the /HDF5_INSTALL/bin directory to see which external filters are enabled. For example, look for the following line:
```
	I/O filters (external): deflate,szip
```
Note: On some platforms (e.g. Crays) the szip library is not available, therefore only the deflate filter is used.
Make sure that your system has the required gzip and szip libraries installed.
NCSA provides the prebuilt zlib and szip libraries for all supported platforms and compiler options (for example 64-bit libraries for SunOS-5.7(8), IRIX64-6.5, AIX 5.1, etc.) You may download the prebuilt zlib and szip libraries from ftp://ftp.hdfgroup.org/lib-external/zlib/ and ftp://ftp.hdfgroup.org/lib-external/szip/ correspondingly or build and install the libraries yourself.
Make sure that the linker finds the correct library. For example, when building a 64-bit application on AIX 5.1 make sure that you use 64-bit zlib and 64-bit szip libraries along with the 64-bit HDF5 Libraries.
We recommend that you use the h5cc/h5fc/h5c++ scripts to build your application with the prebuilt HDF5 Libraries.
Before you use the script
1. make sure that h5redeploy was run in the bin directory to modify the scripts to point to the directory where HDF5 is currently installed.
2. make sure that the required zlib and/or szip libraries are
  - installed in the system directories on your system
```
				   or
```
  - installed somewhere on your system and h5cc/h5fc/h5c++ are edited to point to the correct location.
    To see the flags that are used by the h5cc/h5fc/h5c++ scripts use
```
		   h5cc  -show
		   h5fc  -show
		   h5c++ -show 
```
    commands.
If you still have problems, we recommend you
- build and install the HDF5 libraries from the source code on your system
- then use h5cc/h5fc/h5c++ to build your application
If it still doesn't work, please send email to THG Helpdesk and be ready to follow steps 0-6 with us :-)

How can you determine what compiler/flags are used by an HDF5 installation?

lib/

   libhdf5.settings         - HDF5 C library 
   libhdf5_cpp.settings     - HDF5 C++  (if built)
   libhdf5_fortran.settings - HDF5 Fortran library (if built)

The mtime test fails with the message 'Old modification time incorrect.', when building with an unsupported platform/compiler

This problem has occurred when using gcc on Solaris, which is not supported and tested.

Can't open shared library: /lib...s#.0

If you are on Mac OS X, you must either build the shared library from source, or change the path with install_name_tool:

   install_name_tool -change <oldpath> <newpath> <library>

otool -L

Gets -DPIC error building HDF5 on AIX w/F90

To get around it do NOT build the shared libraries. Specify the following options when configuring:

--disable-shared 
--enable-static

Tests fail when building HDF5 on HP-UX 10.20

One user was able to resolve this error by editing the libtool script to NOT use the pic option (pic_mode=no). (He noticed that the HDF5 tests were compiled with "+Z -DPIC", but linked with a static library; the +Z option probably cannot be used with a static library?)

How to build HDF5 Fortran with Intel Compilers

Use the -fpp -DDEC$=DEC_ -DMS$=MS_ compiler flags to disable DEC and MS compiler directives in source files in the fortran/src, fortran/test, and fortran/examples directories. See section 5.7 of the release_docs/INSTALL file. For example:
```
         setenv F9X 'ifc -fpp -DDEC$=DEC_ -DMS$=MS_'
         ./configure --enable-fortran ...
         make
         ....
```

If step 1 doesn't work, run the following script (courtesy of Hugh C. Pumphrey) to remove DEC and MS compiler directives from the source in each fortran directory (fortran/src, fortran/test, fortran/examples) before the configuration step:

#! /bin/bash
# script to forcibly disable directives like !DEC$Foo and !MS$Bar
# in a directoryload of  Fortran 90 code.
for filename in `ls *.f90`
do
    echo hacking $filename
    mv $filename tmpbollox.txt
    cat tmpbollox.txt | sed -e "s/\\!DEC\\$/\\!FooDECS/g" \
                 -e s/\\!MS\\$/\\!FooMSS/g  > $filename
done
# end script

exit

   IF (total_error .ne. 0) CALL exit (total_error)

Building on MAC OSX, the symbols restFP and saveFP come up as undefined. Why?

These are defined in /usr/lib/libgcc.a. To fix this, add -lgcc to your link line or link against /usr/lib/libgcc.a.

Float to Conversion Tests Fail on AMD with Intel compiler. Why?

Testing random sw float -> double conversions                         *FAILED*
    test 1, elmt 323
        src = 80 32 39 ac               -1.19983053689896439985e-32
        dst = b7 f9 1c d6 00 00 00 00   -4.61246357842685217724e-39
        ans = 80 00 00 00 00 00 00 00   -0.00000000000000000000e+00

To enable support for denormalized values, add the option -mp to the compiler. If you do not want to sacrifice speed for this feature, go to the test program and comment out the test.

In one sentence, this is a feature, not an error.

Building 5-1.6.2(3) using Intel 8.1, get ULLONG_MAX error.

   ...src/H5S.c(842): error: identifier "ULLONG_MAX" is undefined

This error does not occur with versions of Intel prior to 8.1.

AIX Configure failure: "...config.sub: too many arguments"

Problem:

   checking build system type... /usr/bin/oslevel[7]:
/usr/bin/rm_mlcache_file: cannot execute
   config.sub: too many arguments

Answer:

Quick fix:

Details:

% ls -lc /usr/bin/rm_mlcache_file
----------   1 root     system        12726 Apr 24 10:23
/usr/bin/rm_mlcache_file

Using Purify on HDF5 library, get uninitialized memory read error

To use Purify on the HDF5 library, you must set the "-D H5_USING_PURIFY" flag for the CFLAGS environment variable. This is done during the configure step, as follows:

   env CFLAGS="-D H5_USING_PURIFY" ./configure

When Building HDF5, the Object Header test, "Testing message deletion", fails.

The "gmake check" fails as follows , when running the Object Header (ohdr) tests:

...
Testing object header overflow on disk                                 PASSED
Testing message deletion                                              *FAILED*
         at ohdr.c:220 in main()...
HDF5-DIAG: Error detected in HDF5 (1.8.0-beta5) thread 0:
  #000: H5Omessage.c line 948 in H5O_msg_remove(): unable to remove object header message
    major: Object header
    minor: Can't delete message
  #001: H5Omessage.c line 1124 in H5O_msg_remove_real(): error iterating over messages
    major: Object header
    minor: Object not found
  #002: H5Omessage.c line 1255 in H5O_msg_iterate_real(): unable to decode message
    major: Object header
    minor: Unable to decode value
  #003: H5Omtime.c line 220 in H5O_mtime_decode(): badly formatted modification time message
    major: Object header
    minor: Unable to initialize object
*** TESTS FAILED ***

This problem is due to how HDF5 translates the timestamp to UTC time from mktime. It is reproducible if the TZ variable is set to "EET-2EEST", which is the timezone for Eastern Europe. The timestamp which causes this error is encoded as "19700101003321", which represents Jan. 1, 1970 00:33:21. When HDF5 tries to translate this to UTC time from mktime, it subtracts 2 hours, thus putting it in pre-Epoch time, which is known to cause problems on Windows and AIX.

If you encounter this error, you can ignore it by using the the environment variable $HDF5_Make_Ignore to tell the hdf5 Makefile to ignore test errors and continue on. For example:

      env HDF5_Make_Ignore=yes gmake check

If a test fails, make will print a message (echo "*** Error ignored") and continue. Therefore, you can search the output for the string "Error ignored" to see if any tests failed.

Building on AIX 64-bit, get: ERROR: No csects or exported symbols have been saved.

--disable-shared --enable-static

JAVA

Java error: can't find HDF5 file format

not finding the Java classes
the dynamic link library is not linked correctly
the file format is not registered

Put the following code in your test code:

import ncsa.hdf.object.h5.*;
If you cannot do that, it means that the hdf5 package is not in your classpath
H5File h5file = new H5File(filename);
h5file.open();
If that fails, it means the dynamic link library is not linked correctly. Check your environment variable setting for your application. Make sure the path which contains the dll is in your path.

Make sure the following code is called in your server application:

    try {
        Class fileclass = Class.forName("ncsa.hdf.object.h5.H5File");
        FileFormat fileformat = (FileFormat)fileclass.newInstance();
        if (fileformat != null)
            FileFormat.addFileFormat("HDF5", fileformat);
    } catch (Throwable err ) {;}

How do you read/write a string dataset in Java?

stringdata/

Data values are reversed/swapped/transposed in HDFView. Why?

If your file was created with a C program, then the data is stored with the assumption that the last dimension of the slab varies fastest ("row-major order").
If your file was created with a F90 application, then the data is stored with the assumption that the first dimension varies fastest ("column-major order").

The data itself in HDF5 is exactly the same. Because HDF Java consists of wrappers around C, it would read the data in row-major order. If your data was written with a Fortran application, then the data would appear to be transposed in HDFView.

Since HDFView doesn't know how the file was created, it gives the user the choice of swapping the dimensions, if need be. You can change the order that the data is read and viewed as follows:

Do you support Java 64-bit with HDF-JAVA?

You will have to:

build the external libraries (jpeg, zlib, szip) with 64-bit flag
build 64-bit hdf4
build 64-bit hdf5
make changes to various configuration files
build jni with 64-bit flag
build Java classes with 64-bit Java

We are currently providing Java 64-bit support on a platform by platform basis, as we obtain funding to do so. We have been funded to build 64-bit HDF-Java for Opteron Linux and Solaris. The pre-compiled beta versions for these platforms can be found at:

    ftp://ftp.hdfgroup.org/HDF5/hdf-java24-beta/bin/

What are the limitations of the HDF Java interface?

Compound datatypes can only be read by field
Writing to variable length strings is not supported. You can actually create them with HDF Java, just not write to them.
Property lists are not completely supported. For example, the file family is not supported in HDFView. It is in HDF Java, but is not tested. In general, the file drivers are not supported with HDF Java.
Datatypes: bitfield, region references, and Date types are not supported
Dataset region references use a 12-byte structure which is not supported in the Java code. With version 2.4, HDFView will show the selection that was made when you look at the dataset region reference, but you won't actually be able to see the selection itself. This is a difficult thing to fix.

What kind of palettes are supported in HDFView?

Image and Palette Specification

HDFView only supports an indexed RGB color table with 256 colors (8-bit) or a 24-bit true color image. It does not support an image with any other color table. When an image has an unsupported color table, HDFView will display the image with one of the default color tables (grey, nature, wave and rainbow).

Also see the following question under "Images and Palettes": What kind of palettes are supported?

java.lang.UnsatisfiedLinkError: no jhdf5 in java.library.path

NCSA HDF Object Package - How to use it

Will you be adding a pure Java interface to HDF5?

We have no plans on doing this.

Installing HDFView, cannot open shared object files

hdfview_install_linux_vm.bin

  $ ./hdfview_install_linux_vm.bin
  Preparing to install...
  Extracting the JRE from the installer archive...
  Unpacking the JRE...
  Extracting the installation resources from the installer archive...
  Configuring the installer for this system's environment...
  awk: error while loading shared libraries: libdl.so.2: cannot open shared
  object file: No such file or directory

This problem occurs on Linux 2.6. Although we do not support HDFView on Linux 2.6, the following workaround has helped other users:

Run hexedit on hdfview_install_linux_vm.bin and change line 2251 from:
```
export LD_ASSUME_KERNEL=2.2.5
```
to
```
#xport LD_ASSUME_KERNEL=2.2.5
```
Then edit a few lines at the top of hdfview.sh so that HDFVIEW_HOME and JAVAPATH are set properly.

Another solution which worked for a user was to copy an already working HDFView installation on a Linux 2.4 machine to the Linux 2.6 machine. Then modify the HDFVIEW_HOME and JAVAPATH in hdfview.sh. This user was using JDK 1.6.

What are the issues regarding replacing the JNI?

The Problems

Secondly, we need to replicate as much of the HDF5 library as possible. For a given use, it might be possible to write something that peeks into HDF5 files, extracts what you need, etc. However, we (NCSA) probably don't want to do a limited case.

Thirdly, is the issue of interoperability. Whatever we do must be able to exchange data with files created by the C library. This is a pretty stringent requirement which rules out some easy solutions, such as just writing and reading serialized objects.

Analysis

Reimplement in Java
The HDF5 library is much more than 100K lines of C, plus another 100K or so of unit tests, etc. There are >10 programmer years invested. Clearly, reengineering would be very costly--even if the library was totally stable and easy to understand. Also, although some of the code would be simple and elegant in Java, other parts would definitely not be.
Besides the scope, there are a number of features in the library and format that are very C-specific:
- parallel I/O with MPI/IO (MPI/IO is inside the library and wired into the format)
- zlib encryption (we import the zlib library -- in C)
- iterators that take C functions as arguments, i.e., as callbacks
- various aspects of datatypes that pass around "void *", assuming you can cast, etc., structures, variables length arrays, and so on. These are C features wired in.
We'd have to come up with emulation for as much of this as possible.
A third issue is that you would really want to deal nicely with Java datatypes, not translating to C. This would be a whole library in itself.
And fourth: how do we assure interoperability of Java and C libraries. It would take a lifetime to write a cross verification suite.
Overall, this would be a huge undertaking, with quite a lot of unknowns.
A CORBA server (or similar idea with your favorite technology)
The JNI is basically providing a Java <-> the real C library layer. JNI is a terrible instrument, so why not do it the right way: CORBA.
We've done explorations, so we know we could make a CORBA server that exports the HDF5 API. Java programs can talk directly or remotely to this layer. See:
```
/HDF5/XML/JSPExperiments/index.html
```
Good points:
- The I/O uses the real C library, which guarantees interoperability, has all the features, etc. Also, we can chase the library and format as they evolve.
- The server resides local to the data, which is definitely a plus for really big files or collections.
- The user app can be pure Java, and can even be remote.
- CORBA has all the right stuff, including security, etc.
- Same server can work with Smalltalk, etc., not just Java.
- This plugs in to Web services, etc., pretty well
Bad points:
- CORBA is painful and complex (and often expensive),
- CORBA has its own datatypes, so you have to deal with that.
- Several layers in the stack, who knows what the performance might be.
Creating a full feature CORBA server would be quite a bit of work, possibly a couple of programmer years. This estimate is based on our previous work which indicates a number of important tasks:
- Design reasonable interface, i.e., a network protocol -- pretty complex
- Special problems, such as caching, fiddling datatypes, etc., to implement the server layer
- Performance issues
We would also need a good free CORBA, and ideally a little mini ORB that could be packed with the library, etc.
Overall, using CORBA would probably be the preferable choice over reverse engineering the C library.

Summary

Is parallel HDF5 supported with java?

No.

Can HDFView handle bit-field data?

No. You can store bit-field data in HDF5, but HDFView does not know how to deal with bit-field data.

Can't get HDFView to work on HP-UX

HotSpot requires use of the HP aC++ compiler for any application C or C++ libraries loaded dynamically at runtime. Libraries compiled with the cfront HP C++ compiler will not work with HotSpot."

Note that all our products are portable C, not C++.

With proper modifications the JHI5 was able to compile with aCC. This involved making the C capable of being compiled with either C or C++, especially alternate calls the JNI depending on the languages.

However, the library was unable to link with the HDF5 library which is compiled with straight C. The HDF5 library cannot be compiled with aCC, at least not without significant effort.

Therefore, we cannot provide the JHI5 for HPUX 11, and we cannot provide HDFView for HPUX 11.

HDFView installs properly on Mac but crashes when selected

Another problem is that the installation requires install_name_tool to change the path of the dynamic link library. If the install_name_tool is not installed, then HDFView will not find the dynamic link library.

Also, due to a bug in JDK 1.4 on Mac OS X, the HDFView tool cannot be run by clicking on it from the desktop. The Java virtual machine in JDK 1.4 cannot obtain the environment variable, DYLD_LIBRARY_PATH, from the system. Therefore, HDFView cannot find the HDF5 library. This problem does not occur with JDK 1.3.

To work around this problem you can run HDFView from a command line prompt, by going to the directory where it is located and typing:

    open -a  <absolute path to HDFView executable>

HDFView: connection time out errors running behind a firewall

java.net.ConnectException: Connection Timed Out

Since the HDFView binaries ares built on networked machines, it is possible that somehow certain java network classes are getting pulled in.

Will HDFView be supporting variable length strings soon?

We have added the ability to view datasets with variable length strings in HDFView, but not to edit them. This is on our to-do list, but it is difficult to implement in Java.

How do you increase the Java Virtual machine memory?

heap size

On Linux, type free to see how much memory you have on your machine.

   JVMDG305: Java core not written, unable to allocate memory for print buffer.

Get EXCEPTION_ACCESS_VIOLATION when more than 1024MB is allocated to the Java Virtual machine.

When using the HDF Java package to read a dataset out of an HDF5 file, it works as expected when only 1024 MB are allocated to the java virtual machine. However, it encounters an unexpected error and crashes the VM at larger amounts. The basic process is opening the file, retrieving the file structure, getting and setting the start dimensions, and calling dataset.read. Then the file is closed.

This is a Java virtual machine problem. We have no solution for it at this time.

How to workaround error `Exception - dataset too big` ?

If your machine has enough memory to hold the data and you still get an out of memory error, the Java virtual machine may run out of memory. You can increase the heap size for the Java virtual machine by the "-mx" option. For example: java -mx512m

Error - variable HDF5CDataTypes not found

Now, you should use the constants just as they are used in HDF5 library constants. The JNI will translate for you. In other words, use H5T_xxx instead of JH5T_xxx.

Do you have an example of writing/reading compound datatypes in java?

You can look at the source code for our HDFView tool to see how it handles compound datatypes. The hdf java pages are at:

  /hdf-java-html/

  ftp://ftp.hdfgroup.org/HDF5/hdf-java/

How do you insert JAR files into JBuilder ?

   Project --> project properties --> paths --> required libraries --> add

   http://bdn.borland.com/article/0,1410,29008,00.html

PARALLEL HDF5

What do you need to run Parallel HDF5 ?

You need MPI and MPI I/O. (If you can't tell whether you have MPI I/O working on your system, let us know.)

What performance can you expect from Parallel HDF5 ?

If you want to compare the performance of MPI I/O and Parallel HDF5 on your system, you can use the h5perf program that is built along with the parallel library. This is under the ./<HDF5 source code>/perform/ directory of the source code.

Does HDF5 support compression with parallel HDF5 ? If not, why ?

As of HDF5 1.6.3, you can read compressed data but cannot write in parallel.

Why do we not support writing of compressed data in parallel? Compression uses chunking. Since chunks are preallocated in the file before writing, chunks have to be of the same size. However, the size of the compressed chunk is not known in advance.

Chunks are preallocated in the file to avoid the following problem: we allow independent I/O on raw data (with H5Dwrite), but require collective operations to operate on metadata (like the B-tree that tracks the chunks in a chunked dataset or the "free space in the file" metadata (for allocating space when a compressed chunk changes size)). Therefore, in order to allow independent raw data I/O (and simplify the collective raw data I/O), we require the chunks to be preallocated (so we don't have to change the chunk B-tree) and disallow writing to compressed chunked data and variable-length datatypes (so we don't have to allocate/free space in the file) when performing parallel I/O.

Does Parallel HDF5 support chunking ?

Yes. It is not necessarily efficient, though.

Can you run parallel HDF5 and the threadsafe feature together ? What about Parallel HDF5 and C++?

This is also true of C++. You cannot configure Parallel HDF5 with the --enable-cxx option.

How do you write to attributes independently ?

Right now, you cannot. The workaround is to use the H5D interface instead.

Does Parallel HDF5 support variable length datatypes ?

Currently, it does NOT.

Most HDF5 calls do not make a statement about whether they are being called collectively or independently. How are they being called?

For the H5P and H5S interfaces, it depends on each API call.

Problems installing Parallel HDF5 on IBM Regatta (with AIX5)

Macro name H5_PACKAGE_NAME cannot be redefined.
"H5_PACKAGE_NAME" is defined on line 312 of ../../src/H5pubconf.h.
Macro name H5_PACKAGE_STRING cannot be redefined.
... etc ...

./release_docs/INSTALL_parallel

 setenv LLNL_COMPILE_SINGLE_THREADED TRUE

mpcc_r

mpxlf_r

How to write and NOT to write compound datasets using F90 in Parallel HDF5

compound_pall.f90 - Right way
compound_p.f9 - Wrong way (for now)

Both examples write a one dimensional array of size 16 using 4 processes. Elements of the array are structures:

      char*2
      integer
      double precision
      float

compound_p.f90

  process 0 writes character field (16 elements)
  process 1 writes integer field (16 elements)
  process 2 writes double field (16 elements)
  process 3 writes real filed (16 elements)

The compound_pall.f90 program writes a dataset by each process writing all 4 fields and its own portion of the data array:

  process 0 writes character, integer, double and real fields for elements 1 through 4
  process 1 writes character, integer, double and real fields for elements 5 through 8
  process 2 writes character, integer, double and real fields for elements 9 through 12
  process 3 writes character, integer, double and real fields for elements 13 through 16

MPI ... failed: array services not available

   Sample_mpio.c
   Sample_mpio.f90

chkconfig array on

How do you write data when one process doesn't have or need to write data ?

coll_test.c - Uses H5Sset_none to tell H5Dwrite call that there will be no data. 4-th process HAS to participate since we are in a collective mode.
ind_test.c - Specifies which process writes data. H5Dwrite is not called by the 4-th process at all in this case; this approach will work only when independent mode is used.

PERFORMANCE

The Chunk Cache and Chunked Datasets:

A chunk cache serves to cache chunks of raw data from an associated open dataset, and goes away when the dataset is closed. The chunk caches exist primarily to reduce the overhead involved in reading and writing partial chunks.

If you create and/or open a large number of datasets, and then read or write to them all, the associated caches will fill up, and use a huge amount of memory.

If this is a problem, the obvious solution is to not to have a lot of chunked datasets open at once.

If that is not an option, you can also disable the chunk caches by setting the number of elements in the raw data cache (rdcc_nelmts) and the maximum number of bytes in the raw data cache (rdcc_nbytes) to zero using the H5Pset_cache / h5pset_cache_f call. This function must be used to modify the file access property list that is passed to h5fcreate_f(). Use H5Pget_cache / h5pget_cache_f to get the current values of the parameters you don't want to change. Again by default, each chunk cache can contain up to 1 MB of chunks.

If you only read and write integral chunks, and don't access the same chunk more than once in a short period of time, you should not see a performance hit if you disable chunk caching.

However, if you access partial chunks and disable the chunk cache, you will take a significant performance hit. For example, if you disable the chunk caches and write a chunk in several pieces, on each write after the first one, the library will have to read the chunk back into memory, decompress it (if required), write the new data to the uncompressed version, recompress (if required), and then write the modified chunk back to disk. In contrast, if the chunk cache was enabled, and the chunk was in cache, the write would just modify the cached image of the chunk.

Partial reads would not be quite as bad, but they would still be painful.

By default, the chunk caches are limited to 1 MB. If your chunk size is larger than this, and you don't always access integral chunks, you will probably want to increase the chunk cache size so that the cache can contain at least one chunk.

More generally, you want to choose chunk cache size so that the chance of a chunk staying in the cache until you are done with is high. However, this is very much access pattern dependent.

On the other hand, chunk caches take up space, so you don't want them to be any bigger than necessary. Remember, each open chunked dataset has its own cache. If you have a lot of open chunked datasets, the caches can eat up RAM quickly.

Needless to say, you can play games with chunk size to increase your chances of reading and writing integral chunks. Don't go too far with this, as small chunk sizes can also cause performance problems.

As long as chunks are large in comparison to the logical block size of the underlying file system, you shouldn't run into major performance problems on that front. If you use compression, remember to consider it in your choice of chunk size, as the underlying file system will be dealing with compressed chunks.

Another reason for relatively large chunks is the library overhead required for each chunk. The library has to keep track of each chunk, and large numbers of chunks result in large indexes (which are maintained in B-Trees). If the B-Tree is too big to fit in the metadata cache, you will see significant performace hits on chunk reads and writes. Also, since the B-Trees must be stored in the file, you will increased file size.

Following is a piece of code that shows the use of H5Pset_cache:

   hid_t       file;
   hid_t       fapl;
   hsize_t     dimsf[3];              /* dataset dimensions */
   hsize_t     ch_dims[3];            /* chunk dimensions */
   herr_t      status;
   int         mdc_nelmts, rdcc_nelmts;
   size_t rdcc_nbytes;
   double rdcc_w0;

   /* when opening the file for read, set cache size */
   /* need to do the same when writing the dataset */

   fapl = H5Pcreate (H5P_FILE_ACCESS);

   /* to be safe, retrieve the current settings, and reset only the total size */
	 
   status = H5Pget_cache (fapl, &mdc_nelmts, &rdcc_nelmts, &rdcc_nbytes, &rdcc_w0);
   rdcc_nbytes = /* size of the cache, at least the size of a chunk in bytes */;
   status = H5Pset_cache (fapl, mdc_nelmts, rdcc_nelmts, rdcc_nbytes, rdcc_w0);

   file = H5Fopen (DATAFILE, H5F_ACC_RDONLY /* or RDWR */, fapl);

   /* when creating:
   file = H5Fcreate (DATAFILE, H5F_ACC_RDONLY /* or RDWR */, fapl,
					 H5P_DEFAULT);
   */

PROPERTIES

With HDF5-1.6.0-post, a fix was added for using H5Pset_istore_k* and H5Pget_istore_k. This fix required a change to the HDF5 format. What are the implications of this ?

However, if you start using it, then old versions prior to HDF5-1.6.0-post* will not be able to read those HDF5 files created with the property list.

What function do you use to get compression level information?

The function H5Pget_filter_by_id returns this information. This function is new with HDF5-1.6.0.

How do you use the stream driver in HDF5-1.6.2?

Use the Reference Manual entry for H5Pset_fapl_stream() and the test program test/stream_test.c in the HDF5 source code. Eventually we will add this information to the User's Guide.

How do you work with a file created with the file family feature?

Property List

To access a file with the file family feature, when you open or create the file, the name of it should include a printf integer format specifier (which gets replaced with the family member number). For example, junk%d.h5 would result in files, such as, junk0.h5, junk1.h5, junk2.h5 ...

There are some problems with the file family feature with the 5-1.6* (and earlier) releases.

Right now, if you are going to use the file family feature, we recommend that when you read the file, you know that it was created with the file family feature and what the file member size is. Also, you must have written enough data to the file when you created it, to fill up the first file member. Otherwise, HDF5 will re-set the file member size to the size of the data that was written.

Here is an example of how you would read a file that was created using the file family feature:

  ...
  #define FILE "junk%d.h5"

  main() {

    hid_t       file_id, fapl;
    hsize_t     msize;
    herr_t      status;

    fapl = H5Pcreate (H5P_FILE_ACCESS);
    msize = 1024*1024;
    status = H5Pset_fapl_family (fapl, msize, H5P_DEFAULT);
    file_id = H5Fopen(FILE, H5F_ACC_RDWR, fapl);
    ...

However, if you open the file using the wrong file member size, and try to *write* data to the file, it may not work as expected.

The problems with the file family feature will be fixed in a future release.

Can you work with an HDF5 file in memory ?

Yes. You can create an HDF5 file in memory using H5Pset_fapl_core and use the backing_store parameter to write the data to disk on closing.

Can I subsequently open the file and put the data in memory ?

Yes, with HDF5 1.8.0, you can bring the file into memory, read it, modify it and write it back, using the core driver. With HDF5 1.6, you could only write it back, with no open.

UTILITIES

How do you use the h5cc (h5fc, h5c++) utility?

h5cc

h5fc

h5c++

You can just type, h5cc -o prog prog.c where prog is the executable that gets created and prog.c is your application.

Use h5cc -show to see what libraries and compiler are used by h5cc.

If building the HDF5 library from source, then the compile scripts should be ready to use without changes.

If using the pre-compiled binaries that we provide, you will need to do a few things before you can use h5cc, as it has site specific paths in it.

After you have copied the files to the final installation directory, do the following:

cd to the bin/ directory in the pre-compiled binaries.
Run ./h5redeploy and enter yes to the question. This will fix some of the paths used in h5cc.
Edit h5cc and search for LDFLAGS and CPPFLAGS. Check, and if need be, update the paths for the external libraries (SZIP, ZLIB). If ZLIB is in a default location, then it will probably be okay, but the SZIP path will need to be updated.

The h5cc utility should then be ready for use in most cases. However, if you use a different compiler name or if some of the required libraries are in non-standard places, you may need to edit it and modify some other variables. Take a look at these variables in the script:

  prefix - Path to the HDF5 top level installation directory
  CCBASE - Name of the alternative C compiler
  CLINKERBASE - Name of the alternative linker
  LDFLAGS   - Path to different libraries your application will link with
              (this path should include the path to the zlib library)
  LIBS      - Libraries your application will link with

Why is h5dump slower than h5ls?

h5dump

h5ls

h5dump

h5ls -f -r

h5dump

Can you add an option to h5dump or h5ls to print the version of a file ?

No, we do not plan on adding this option. Users should use attributes to specify the version of a file. There are many reasons why we shouldn't add this. For example, different objects in the file could be created or modified by different versions of the library.

- - Last modified:July 01st 2008

HDF5 FAQ -- Questions About the Software

ATTRIBUTES

C++

DATASETS

DATASPACE

DATATYPES

EXTERNAL LIBRARIES

ERROR

FILE

FORTRAN

GENERAL

GROUPS

IDENTIFIERS

IMAGES AND PALETTES

INSTALLING/BUILDING HDF5

JAVA

PARALLEL HDF5

PERFORMANCE

PLATFORM SPECIFIC

PROPERTIES

UTILITIES

ATTRIBUTES

When would you use attributes vs. datasets for your metadata ?

When would you use attributes vs. compact datasets ?

C++

Does C++ support stream operators?

Does it do IO via standard library containers?

DATASETS

How do I find out what compression has been used to write a dataset?

How do I create a chunked/compressed dataset?

How do I read/write a subset or sub-sample of a dataset?

When you specify memspace and filespace for H5Dwrite and H5Dread does it mean it is allocating memory for both the dataset and memory space (ie. twice the size of dataset) ?

DATASPACE

Can you subset or select hyperslabs from a compressed dataset?

DATATYPES

Why was the H5T_ARRAY created ? What is it for ?

How can you tell if two datasets share their (named, committed) datatype?

How do I create a String attribute or dataset?

How do you create datasets with a time datatype (class of H5T_TIME)?

When do you use pre-defined standard vs. native datatypes?

Does HDF5 support a boolean datatype ?

What are the plusses and minusses of using compound datatypes ?

Information on using bitfields in HDF5

How would you use a float pointer in a compound datatype ?

H5Tenum_insert returns error when type has different endianess

When reading compound data from file w/different compound field name, the data is different for this field.

What is the proper way to allocate memory when reading a variable length datatype?

Is there a limit on the number of fields allowed in a compound datatype ?

EXTERNAL LIBRARIES

I build the SZIP library from source using the Intel compiler (icc), but the gentest fails when I run make check.

How to detect the SZIP encoder at run time

ERROR

The error report prints out full path for file name instead of file name only

How do you turn off error messages ?

FILE

Can you open a file, open a group, close the file, and continue working on a group ?

How can I resolve file access problems due to objects being left open?

FORTRAN

How do you create a dataset with a 16-bit datatype in F90 ?

How do you build HDF5 using gcc and either Intel or Lahey Fortran ?

Can you build shared Fortran libraries in HDF5 ?

GENERAL

Do you have example code of reading an HDF5 file?

Can you delete objects in an HDF5 file ? If yes, how ?

Does HDF5 support meshes ?

Does HDF5 support netCDF ?

How do you create files over 2GB ?

Is HDF5 threadsafe? Multi-threaded? Explain.

Why are my files sizes different, if I open an HDF5 file more than once rather than writing the data out in one call?

I'd like to access an HDF5 file without using the HDF5 library. Is this possible?

Will data manipulation routines be added to HDF5?

Given an object binary file such as libhdf5.a or a.out, how can I easily determine which version of HDF5 is being used (aka linked)?

Given a library file such as libxyz.a that calls HDF5 functions, how can I easily determine which version of HDF5 is being used to build (aka compile) libxyz.a?

My HDF5-1.4 library cannot read files created with 5-1.6.0

Can you read an HDF5 while it is being written to?

Performance-wise, how does HDF5 compare to a relational database?

If you run an application twice on the same machine will it produce identical HDF5 files ?

GROUPS

H5Gget_obj_info: How do you tell the difference between a soft and hard link? If my reader reads an HDF5 file with a loop in it, then my code goes into an infinite loop, also.

Iterating (H5Giterate) takes a long time when you have lots of objects. Can this be sped up?

I build the SZIP library from source using the Intel compiler (icc), but the gentest fails when I run `make check`.

How to workaround error `Exception - dataset too big` ?