LCOV - code coverage report
Current view: top level - src/backend/tsearch - ts_typanalyze.c (source / functions) Hit Total Coverage
Test: PostgreSQL 17devel Lines: 109 129 84.5 %
Date: 2024-05-19 08:10:29 Functions: 7 8 87.5 %
Legend: Lines: hit not hit

          Line data    Source code
       1             : /*-------------------------------------------------------------------------
       2             :  *
       3             :  * ts_typanalyze.c
       4             :  *    functions for gathering statistics from tsvector columns
       5             :  *
       6             :  * Portions Copyright (c) 1996-2024, PostgreSQL Global Development Group
       7             :  *
       8             :  *
       9             :  * IDENTIFICATION
      10             :  *    src/backend/tsearch/ts_typanalyze.c
      11             :  *
      12             :  *-------------------------------------------------------------------------
      13             :  */
      14             : #include "postgres.h"
      15             : 
      16             : #include "catalog/pg_collation.h"
      17             : #include "catalog/pg_operator.h"
      18             : #include "commands/vacuum.h"
      19             : #include "common/hashfn.h"
      20             : #include "tsearch/ts_type.h"
      21             : #include "utils/builtins.h"
      22             : #include "varatt.h"
      23             : 
      24             : 
      25             : /* A hash key for lexemes */
      26             : typedef struct
      27             : {
      28             :     char       *lexeme;         /* lexeme (not NULL terminated!) */
      29             :     int         length;         /* its length in bytes */
      30             : } LexemeHashKey;
      31             : 
      32             : /* A hash table entry for the Lossy Counting algorithm */
      33             : typedef struct
      34             : {
      35             :     LexemeHashKey key;          /* This is 'e' from the LC algorithm. */
      36             :     int         frequency;      /* This is 'f'. */
      37             :     int         delta;          /* And this is 'delta'. */
      38             : } TrackItem;
      39             : 
      40             : static void compute_tsvector_stats(VacAttrStats *stats,
      41             :                                    AnalyzeAttrFetchFunc fetchfunc,
      42             :                                    int samplerows,
      43             :                                    double totalrows);
      44             : static void prune_lexemes_hashtable(HTAB *lexemes_tab, int b_current);
      45             : static uint32 lexeme_hash(const void *key, Size keysize);
      46             : static int  lexeme_match(const void *key1, const void *key2, Size keysize);
      47             : static int  lexeme_compare(const void *key1, const void *key2);
      48             : static int  trackitem_compare_frequencies_desc(const void *e1, const void *e2,
      49             :                                                void *arg);
      50             : static int  trackitem_compare_lexemes(const void *e1, const void *e2,
      51             :                                       void *arg);
      52             : 
      53             : 
      54             : /*
      55             :  *  ts_typanalyze -- a custom typanalyze function for tsvector columns
      56             :  */
      57             : Datum
      58           6 : ts_typanalyze(PG_FUNCTION_ARGS)
      59             : {
      60           6 :     VacAttrStats *stats = (VacAttrStats *) PG_GETARG_POINTER(0);
      61             : 
      62             :     /* If the attstattarget column is negative, use the default value */
      63           6 :     if (stats->attstattarget < 0)
      64           6 :         stats->attstattarget = default_statistics_target;
      65             : 
      66           6 :     stats->compute_stats = compute_tsvector_stats;
      67             :     /* see comment about the choice of minrows in commands/analyze.c */
      68           6 :     stats->minrows = 300 * stats->attstattarget;
      69             : 
      70           6 :     PG_RETURN_BOOL(true);
      71             : }
      72             : 
      73             : /*
      74             :  *  compute_tsvector_stats() -- compute statistics for a tsvector column
      75             :  *
      76             :  *  This functions computes statistics that are useful for determining @@
      77             :  *  operations' selectivity, along with the fraction of non-null rows and
      78             :  *  average width.
      79             :  *
      80             :  *  Instead of finding the most common values, as we do for most datatypes,
      81             :  *  we're looking for the most common lexemes. This is more useful, because
      82             :  *  there most probably won't be any two rows with the same tsvector and thus
      83             :  *  the notion of a MCV is a bit bogus with this datatype. With a list of the
      84             :  *  most common lexemes we can do a better job at figuring out @@ selectivity.
      85             :  *
      86             :  *  For the same reasons we assume that tsvector columns are unique when
      87             :  *  determining the number of distinct values.
      88             :  *
      89             :  *  The algorithm used is Lossy Counting, as proposed in the paper "Approximate
      90             :  *  frequency counts over data streams" by G. S. Manku and R. Motwani, in
      91             :  *  Proceedings of the 28th International Conference on Very Large Data Bases,
      92             :  *  Hong Kong, China, August 2002, section 4.2. The paper is available at
      93             :  *  http://www.vldb.org/conf/2002/S10P03.pdf
      94             :  *
      95             :  *  The Lossy Counting (aka LC) algorithm goes like this:
      96             :  *  Let s be the threshold frequency for an item (the minimum frequency we
      97             :  *  are interested in) and epsilon the error margin for the frequency. Let D
      98             :  *  be a set of triples (e, f, delta), where e is an element value, f is that
      99             :  *  element's frequency (actually, its current occurrence count) and delta is
     100             :  *  the maximum error in f. We start with D empty and process the elements in
     101             :  *  batches of size w. (The batch size is also known as "bucket size" and is
     102             :  *  equal to 1/epsilon.) Let the current batch number be b_current, starting
     103             :  *  with 1. For each element e we either increment its f count, if it's
     104             :  *  already in D, or insert a new triple into D with values (e, 1, b_current
     105             :  *  - 1). After processing each batch we prune D, by removing from it all
     106             :  *  elements with f + delta <= b_current.  After the algorithm finishes we
     107             :  *  suppress all elements from D that do not satisfy f >= (s - epsilon) * N,
     108             :  *  where N is the total number of elements in the input.  We emit the
     109             :  *  remaining elements with estimated frequency f/N.  The LC paper proves
     110             :  *  that this algorithm finds all elements with true frequency at least s,
     111             :  *  and that no frequency is overestimated or is underestimated by more than
     112             :  *  epsilon.  Furthermore, given reasonable assumptions about the input
     113             :  *  distribution, the required table size is no more than about 7 times w.
     114             :  *
     115             :  *  We set s to be the estimated frequency of the K'th word in a natural
     116             :  *  language's frequency table, where K is the target number of entries in
     117             :  *  the MCELEM array plus an arbitrary constant, meant to reflect the fact
     118             :  *  that the most common words in any language would usually be stopwords
     119             :  *  so we will not actually see them in the input.  We assume that the
     120             :  *  distribution of word frequencies (including the stopwords) follows Zipf's
     121             :  *  law with an exponent of 1.
     122             :  *
     123             :  *  Assuming Zipfian distribution, the frequency of the K'th word is equal
     124             :  *  to 1/(K * H(W)) where H(n) is 1/2 + 1/3 + ... + 1/n and W is the number of
     125             :  *  words in the language.  Putting W as one million, we get roughly 0.07/K.
     126             :  *  Assuming top 10 words are stopwords gives s = 0.07/(K + 10).  We set
     127             :  *  epsilon = s/10, which gives bucket width w = (K + 10)/0.007 and
     128             :  *  maximum expected hashtable size of about 1000 * (K + 10).
     129             :  *
     130             :  *  Note: in the above discussion, s, epsilon, and f/N are in terms of a
     131             :  *  lexeme's frequency as a fraction of all lexemes seen in the input.
     132             :  *  However, what we actually want to store in the finished pg_statistic
     133             :  *  entry is each lexeme's frequency as a fraction of all rows that it occurs
     134             :  *  in.  Assuming that the input tsvectors are correctly constructed, no
     135             :  *  lexeme occurs more than once per tsvector, so the final count f is a
     136             :  *  correct estimate of the number of input tsvectors it occurs in, and we
     137             :  *  need only change the divisor from N to nonnull_cnt to get the number we
     138             :  *  want.
     139             :  */
     140             : static void
     141           6 : compute_tsvector_stats(VacAttrStats *stats,
     142             :                        AnalyzeAttrFetchFunc fetchfunc,
     143             :                        int samplerows,
     144             :                        double totalrows)
     145             : {
     146             :     int         num_mcelem;
     147           6 :     int         null_cnt = 0;
     148           6 :     double      total_width = 0;
     149             : 
     150             :     /* This is D from the LC algorithm. */
     151             :     HTAB       *lexemes_tab;
     152             :     HASHCTL     hash_ctl;
     153             :     HASH_SEQ_STATUS scan_status;
     154             : 
     155             :     /* This is the current bucket number from the LC algorithm */
     156             :     int         b_current;
     157             : 
     158             :     /* This is 'w' from the LC algorithm */
     159             :     int         bucket_width;
     160             :     int         vector_no,
     161             :                 lexeme_no;
     162             :     LexemeHashKey hash_key;
     163             : 
     164             :     /*
     165             :      * We want statistics_target * 10 lexemes in the MCELEM array.  This
     166             :      * multiplier is pretty arbitrary, but is meant to reflect the fact that
     167             :      * the number of individual lexeme values tracked in pg_statistic ought to
     168             :      * be more than the number of values for a simple scalar column.
     169             :      */
     170           6 :     num_mcelem = stats->attstattarget * 10;
     171             : 
     172             :     /*
     173             :      * We set bucket width equal to (num_mcelem + 10) / 0.007 as per the
     174             :      * comment above.
     175             :      */
     176           6 :     bucket_width = (num_mcelem + 10) * 1000 / 7;
     177             : 
     178             :     /*
     179             :      * Create the hashtable. It will be in local memory, so we don't need to
     180             :      * worry about overflowing the initial size. Also we don't need to pay any
     181             :      * attention to locking and memory management.
     182             :      */
     183           6 :     hash_ctl.keysize = sizeof(LexemeHashKey);
     184           6 :     hash_ctl.entrysize = sizeof(TrackItem);
     185           6 :     hash_ctl.hash = lexeme_hash;
     186           6 :     hash_ctl.match = lexeme_match;
     187           6 :     hash_ctl.hcxt = CurrentMemoryContext;
     188           6 :     lexemes_tab = hash_create("Analyzed lexemes table",
     189             :                               num_mcelem,
     190             :                               &hash_ctl,
     191             :                               HASH_ELEM | HASH_FUNCTION | HASH_COMPARE | HASH_CONTEXT);
     192             : 
     193             :     /* Initialize counters. */
     194           6 :     b_current = 1;
     195           6 :     lexeme_no = 0;
     196             : 
     197             :     /* Loop over the tsvectors. */
     198        3054 :     for (vector_no = 0; vector_no < samplerows; vector_no++)
     199             :     {
     200             :         Datum       value;
     201             :         bool        isnull;
     202             :         TSVector    vector;
     203             :         WordEntry  *curentryptr;
     204             :         char       *lexemesptr;
     205             :         int         j;
     206             : 
     207        3048 :         vacuum_delay_point();
     208             : 
     209        3048 :         value = fetchfunc(stats, vector_no, &isnull);
     210             : 
     211             :         /*
     212             :          * Check for null/nonnull.
     213             :          */
     214        3048 :         if (isnull)
     215             :         {
     216           0 :             null_cnt++;
     217           0 :             continue;
     218             :         }
     219             : 
     220             :         /*
     221             :          * Add up widths for average-width calculation.  Since it's a
     222             :          * tsvector, we know it's varlena.  As in the regular
     223             :          * compute_minimal_stats function, we use the toasted width for this
     224             :          * calculation.
     225             :          */
     226        3048 :         total_width += VARSIZE_ANY(DatumGetPointer(value));
     227             : 
     228             :         /*
     229             :          * Now detoast the tsvector if needed.
     230             :          */
     231        3048 :         vector = DatumGetTSVector(value);
     232             : 
     233             :         /*
     234             :          * We loop through the lexemes in the tsvector and add them to our
     235             :          * tracking hashtable.
     236             :          */
     237        3048 :         lexemesptr = STRPTR(vector);
     238        3048 :         curentryptr = ARRPTR(vector);
     239      175848 :         for (j = 0; j < vector->size; j++)
     240             :         {
     241             :             TrackItem  *item;
     242             :             bool        found;
     243             : 
     244             :             /*
     245             :              * Construct a hash key.  The key points into the (detoasted)
     246             :              * tsvector value at this point, but if a new entry is created, we
     247             :              * make a copy of it.  This way we can free the tsvector value
     248             :              * once we've processed all its lexemes.
     249             :              */
     250      172800 :             hash_key.lexeme = lexemesptr + curentryptr->pos;
     251      172800 :             hash_key.length = curentryptr->len;
     252             : 
     253             :             /* Lookup current lexeme in hashtable, adding it if new */
     254      172800 :             item = (TrackItem *) hash_search(lexemes_tab,
     255             :                                              &hash_key,
     256             :                                              HASH_ENTER, &found);
     257             : 
     258      172800 :             if (found)
     259             :             {
     260             :                 /* The lexeme is already on the tracking list */
     261      165954 :                 item->frequency++;
     262             :             }
     263             :             else
     264             :             {
     265             :                 /* Initialize new tracking list element */
     266        6846 :                 item->frequency = 1;
     267        6846 :                 item->delta = b_current - 1;
     268             : 
     269        6846 :                 item->key.lexeme = palloc(hash_key.length);
     270        6846 :                 memcpy(item->key.lexeme, hash_key.lexeme, hash_key.length);
     271             :             }
     272             : 
     273             :             /* lexeme_no is the number of elements processed (ie N) */
     274      172800 :             lexeme_no++;
     275             : 
     276             :             /* We prune the D structure after processing each bucket */
     277      172800 :             if (lexeme_no % bucket_width == 0)
     278             :             {
     279           0 :                 prune_lexemes_hashtable(lexemes_tab, b_current);
     280           0 :                 b_current++;
     281             :             }
     282             : 
     283             :             /* Advance to the next WordEntry in the tsvector */
     284      172800 :             curentryptr++;
     285             :         }
     286             : 
     287             :         /* If the vector was toasted, free the detoasted copy. */
     288        3048 :         if (TSVectorGetDatum(vector) != value)
     289         384 :             pfree(vector);
     290             :     }
     291             : 
     292             :     /* We can only compute real stats if we found some non-null values. */
     293           6 :     if (null_cnt < samplerows)
     294             :     {
     295           6 :         int         nonnull_cnt = samplerows - null_cnt;
     296             :         int         i;
     297             :         TrackItem **sort_table;
     298             :         TrackItem  *item;
     299             :         int         track_len;
     300             :         int         cutoff_freq;
     301             :         int         minfreq,
     302             :                     maxfreq;
     303             : 
     304           6 :         stats->stats_valid = true;
     305             :         /* Do the simple null-frac and average width stats */
     306           6 :         stats->stanullfrac = (double) null_cnt / (double) samplerows;
     307           6 :         stats->stawidth = total_width / (double) nonnull_cnt;
     308             : 
     309             :         /* Assume it's a unique column (see notes above) */
     310           6 :         stats->stadistinct = -1.0 * (1.0 - stats->stanullfrac);
     311             : 
     312             :         /*
     313             :          * Construct an array of the interesting hashtable items, that is,
     314             :          * those meeting the cutoff frequency (s - epsilon)*N.  Also identify
     315             :          * the minimum and maximum frequencies among these items.
     316             :          *
     317             :          * Since epsilon = s/10 and bucket_width = 1/epsilon, the cutoff
     318             :          * frequency is 9*N / bucket_width.
     319             :          */
     320           6 :         cutoff_freq = 9 * lexeme_no / bucket_width;
     321             : 
     322           6 :         i = hash_get_num_entries(lexemes_tab);  /* surely enough space */
     323           6 :         sort_table = (TrackItem **) palloc(sizeof(TrackItem *) * i);
     324             : 
     325           6 :         hash_seq_init(&scan_status, lexemes_tab);
     326           6 :         track_len = 0;
     327           6 :         minfreq = lexeme_no;
     328           6 :         maxfreq = 0;
     329        6852 :         while ((item = (TrackItem *) hash_seq_search(&scan_status)) != NULL)
     330             :         {
     331        6846 :             if (item->frequency > cutoff_freq)
     332             :             {
     333        6318 :                 sort_table[track_len++] = item;
     334        6318 :                 minfreq = Min(minfreq, item->frequency);
     335        6318 :                 maxfreq = Max(maxfreq, item->frequency);
     336             :             }
     337             :         }
     338             :         Assert(track_len <= i);
     339             : 
     340             :         /* emit some statistics for debug purposes */
     341           6 :         elog(DEBUG3, "tsvector_stats: target # mces = %d, bucket width = %d, "
     342             :              "# lexemes = %d, hashtable size = %d, usable entries = %d",
     343             :              num_mcelem, bucket_width, lexeme_no, i, track_len);
     344             : 
     345             :         /*
     346             :          * If we obtained more lexemes than we really want, get rid of those
     347             :          * with least frequencies.  The easiest way is to qsort the array into
     348             :          * descending frequency order and truncate the array.
     349             :          */
     350           6 :         if (num_mcelem < track_len)
     351             :         {
     352           6 :             qsort_interruptible(sort_table, track_len, sizeof(TrackItem *),
     353             :                                 trackitem_compare_frequencies_desc, NULL);
     354             :             /* reset minfreq to the smallest frequency we're keeping */
     355           6 :             minfreq = sort_table[num_mcelem - 1]->frequency;
     356             :         }
     357             :         else
     358           0 :             num_mcelem = track_len;
     359             : 
     360             :         /* Generate MCELEM slot entry */
     361           6 :         if (num_mcelem > 0)
     362             :         {
     363             :             MemoryContext old_context;
     364             :             Datum      *mcelem_values;
     365             :             float4     *mcelem_freqs;
     366             : 
     367             :             /*
     368             :              * We want to store statistics sorted on the lexeme value using
     369             :              * first length, then byte-for-byte comparison. The reason for
     370             :              * doing length comparison first is that we don't care about the
     371             :              * ordering so long as it's consistent, and comparing lengths
     372             :              * first gives us a chance to avoid a strncmp() call.
     373             :              *
     374             :              * This is different from what we do with scalar statistics --
     375             :              * they get sorted on frequencies. The rationale is that we
     376             :              * usually search through most common elements looking for a
     377             :              * specific value, so we can grab its frequency.  When values are
     378             :              * presorted we can employ binary search for that.  See
     379             :              * ts_selfuncs.c for a real usage scenario.
     380             :              */
     381           6 :             qsort_interruptible(sort_table, num_mcelem, sizeof(TrackItem *),
     382             :                                 trackitem_compare_lexemes, NULL);
     383             : 
     384             :             /* Must copy the target values into anl_context */
     385           6 :             old_context = MemoryContextSwitchTo(stats->anl_context);
     386             : 
     387             :             /*
     388             :              * We sorted statistics on the lexeme value, but we want to be
     389             :              * able to find out the minimal and maximal frequency without
     390             :              * going through all the values.  We keep those two extra
     391             :              * frequencies in two extra cells in mcelem_freqs.
     392             :              *
     393             :              * (Note: the MCELEM statistics slot definition allows for a third
     394             :              * extra number containing the frequency of nulls, but we don't
     395             :              * create that for a tsvector column, since null elements aren't
     396             :              * possible.)
     397             :              */
     398           6 :             mcelem_values = (Datum *) palloc(num_mcelem * sizeof(Datum));
     399           6 :             mcelem_freqs = (float4 *) palloc((num_mcelem + 2) * sizeof(float4));
     400             : 
     401             :             /*
     402             :              * See comments above about use of nonnull_cnt as the divisor for
     403             :              * the final frequency estimates.
     404             :              */
     405        6006 :             for (i = 0; i < num_mcelem; i++)
     406             :             {
     407        6000 :                 TrackItem  *titem = sort_table[i];
     408             : 
     409       12000 :                 mcelem_values[i] =
     410        6000 :                     PointerGetDatum(cstring_to_text_with_len(titem->key.lexeme,
     411             :                                                              titem->key.length));
     412        6000 :                 mcelem_freqs[i] = (double) titem->frequency / (double) nonnull_cnt;
     413             :             }
     414           6 :             mcelem_freqs[i++] = (double) minfreq / (double) nonnull_cnt;
     415           6 :             mcelem_freqs[i] = (double) maxfreq / (double) nonnull_cnt;
     416           6 :             MemoryContextSwitchTo(old_context);
     417             : 
     418           6 :             stats->stakind[0] = STATISTIC_KIND_MCELEM;
     419           6 :             stats->staop[0] = TextEqualOperator;
     420           6 :             stats->stacoll[0] = DEFAULT_COLLATION_OID;
     421           6 :             stats->stanumbers[0] = mcelem_freqs;
     422             :             /* See above comment about two extra frequency fields */
     423           6 :             stats->numnumbers[0] = num_mcelem + 2;
     424           6 :             stats->stavalues[0] = mcelem_values;
     425           6 :             stats->numvalues[0] = num_mcelem;
     426             :             /* We are storing text values */
     427           6 :             stats->statypid[0] = TEXTOID;
     428           6 :             stats->statyplen[0] = -1;    /* typlen, -1 for varlena */
     429           6 :             stats->statypbyval[0] = false;
     430           6 :             stats->statypalign[0] = 'i';
     431             :         }
     432             :     }
     433             :     else
     434             :     {
     435             :         /* We found only nulls; assume the column is entirely null */
     436           0 :         stats->stats_valid = true;
     437           0 :         stats->stanullfrac = 1.0;
     438           0 :         stats->stawidth = 0; /* "unknown" */
     439           0 :         stats->stadistinct = 0.0;    /* "unknown" */
     440             :     }
     441             : 
     442             :     /*
     443             :      * We don't need to bother cleaning up any of our temporary palloc's. The
     444             :      * hashtable should also go away, as it used a child memory context.
     445             :      */
     446           6 : }
     447             : 
     448             : /*
     449             :  *  A function to prune the D structure from the Lossy Counting algorithm.
     450             :  *  Consult compute_tsvector_stats() for wider explanation.
     451             :  */
     452             : static void
     453           0 : prune_lexemes_hashtable(HTAB *lexemes_tab, int b_current)
     454             : {
     455             :     HASH_SEQ_STATUS scan_status;
     456             :     TrackItem  *item;
     457             : 
     458           0 :     hash_seq_init(&scan_status, lexemes_tab);
     459           0 :     while ((item = (TrackItem *) hash_seq_search(&scan_status)) != NULL)
     460             :     {
     461           0 :         if (item->frequency + item->delta <= b_current)
     462             :         {
     463           0 :             char       *lexeme = item->key.lexeme;
     464             : 
     465           0 :             if (hash_search(lexemes_tab, &item->key,
     466             :                             HASH_REMOVE, NULL) == NULL)
     467           0 :                 elog(ERROR, "hash table corrupted");
     468           0 :             pfree(lexeme);
     469             :         }
     470             :     }
     471           0 : }
     472             : 
     473             : /*
     474             :  * Hash functions for lexemes. They are strings, but not NULL terminated,
     475             :  * so we need a special hash function.
     476             :  */
     477             : static uint32
     478      172800 : lexeme_hash(const void *key, Size keysize)
     479             : {
     480      172800 :     const LexemeHashKey *l = (const LexemeHashKey *) key;
     481             : 
     482      172800 :     return DatumGetUInt32(hash_any((const unsigned char *) l->lexeme,
     483             :                                    l->length));
     484             : }
     485             : 
     486             : /*
     487             :  *  Matching function for lexemes, to be used in hashtable lookups.
     488             :  */
     489             : static int
     490      165954 : lexeme_match(const void *key1, const void *key2, Size keysize)
     491             : {
     492             :     /* The keysize parameter is superfluous, the keys store their lengths */
     493      165954 :     return lexeme_compare(key1, key2);
     494             : }
     495             : 
     496             : /*
     497             :  *  Comparison function for lexemes.
     498             :  */
     499             : static int
     500      227028 : lexeme_compare(const void *key1, const void *key2)
     501             : {
     502      227028 :     const LexemeHashKey *d1 = (const LexemeHashKey *) key1;
     503      227028 :     const LexemeHashKey *d2 = (const LexemeHashKey *) key2;
     504             : 
     505             :     /* First, compare by length */
     506      227028 :     if (d1->length > d2->length)
     507           0 :         return 1;
     508      227028 :     else if (d1->length < d2->length)
     509           0 :         return -1;
     510             :     /* Lengths are equal, do a byte-by-byte comparison */
     511      227028 :     return strncmp(d1->lexeme, d2->lexeme, d1->length);
     512             : }
     513             : 
     514             : /*
     515             :  *  Comparator for sorting TrackItems on frequencies (descending sort)
     516             :  */
     517             : static int
     518       38460 : trackitem_compare_frequencies_desc(const void *e1, const void *e2, void *arg)
     519             : {
     520       38460 :     const TrackItem *const *t1 = (const TrackItem *const *) e1;
     521       38460 :     const TrackItem *const *t2 = (const TrackItem *const *) e2;
     522             : 
     523       38460 :     return (*t2)->frequency - (*t1)->frequency;
     524             : }
     525             : 
     526             : /*
     527             :  *  Comparator for sorting TrackItems on lexemes
     528             :  */
     529             : static int
     530       61074 : trackitem_compare_lexemes(const void *e1, const void *e2, void *arg)
     531             : {
     532       61074 :     const TrackItem *const *t1 = (const TrackItem *const *) e1;
     533       61074 :     const TrackItem *const *t2 = (const TrackItem *const *) e2;
     534             : 
     535       61074 :     return lexeme_compare(&(*t1)->key, &(*t2)->key);
     536             : }

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