SQLite

    if( sqlite3_column_int64(pStmt, 1)==0 ){
      /* The entire segment is stored on the root node (which must be a
      ** leaf). Do not bother inspecting any data in this case, just
      ** create a Fts3SegReader to scan the single leaf. 
      */
      rc = sqlite3Fts3SegReaderNew(p, iAge, 0, 0, 0, zRoot, nRoot, &pNew);
    }else{
      int rc2;                    /* Return value of sqlite3Fts3ReadBlock() */
      sqlite3_int64 i1;           /* Blockid of leaf that may contain zTerm */
      rc = fts3SelectLeaf(p, zTerm, nTerm, zRoot, nRoot, &i1);
      if( rc==SQLITE_OK ){
        sqlite3_int64 i2 = sqlite3_column_int64(pStmt, 2);
        rc = sqlite3Fts3SegReaderNew(p, iAge, i1, i2, 0, 0, 0, &pNew);
      }

      /* The following call to ReadBlock() serves to reset the SQL statement
      ** used to retrieve blocks of data from the %_segments table. If it is
      ** not reset here, then it may remain classified as an active statement 
      ** by SQLite, which may lead to "DROP TABLE" or "DETACH" commands 
      ** failing.
      */ 
      rc2 = sqlite3Fts3ReadBlock(p, 0, 0, 0);
      if( rc==SQLITE_OK ){
        rc = rc2;
      }
    }
    iAge++;

    /* If a new Fts3SegReader was allocated, add it to the apSegment array. */
    assert( pNew!=0 || rc!=SQLITE_OK );
    if( pNew ){

proc simple_term {zTerm} {
  set ret [list]
  foreach {key value} [array get ::t1] {
    if {[string first $zTerm $value]>=0} { lappend ret $key }
  }
  lsort -integer $ret
}

proc simple_prefix {zPrefix} {
  set ret [list]
  set pattern [format "*%s%s*" $zPrefix [
    string repeat {[a-z]} [expr {3-[string length $zPrefix]}]
  ]]
  foreach {key value} [array get ::t1] {
    if {[string match $pattern $value]} { lappend ret $key }
  }
  lsort -integer $ret
}

proc simple_near {termlist nNear} {
}

foreach nodesize {50 500 1000 2000} {
  catch { array unset ::t1 }

  # Create the FTS3 table. Populate it (and the Tcl array) with 100 rows.
  #
  db transaction {

    }
  
    # Pick 10 terms from the vocabulary. Check that the results of querying
    # the database for the set of documents containing each of these terms
    # is the same as the result obtained by scanning the contents of the Tcl 
    # array for each term.
    #
    for {set i 0} {$i < 10} {incr i} {
      set term [random_term]
      do_test fts3rnd-1.$nodesize.$iTest.1.$i {
        execsql { SELECT docid FROM t1 WHERE t1 MATCH $term }
      } [simple_term $term]
    }

    # This time, use the first two characters of each term as a term prefix
    # to query for. Test that querying the Tcl array produces the same results
    # as querying the FTS3 table for the prefix.
    #
    for {set i 0} {$i < 10} {incr i} {
      set prefix [string range [random_term] 0 1]
      set match "${prefix}*"
      do_test fts3rnd-1.$nodesize.$iTest.2.$i {
        execsql { SELECT docid FROM t1 WHERE t1 MATCH $match }
      } [simple_prefix $prefix]
    }

    # Similar to the above, except for phrase queries.
    #
    for {set i 0} {$i < 10} {incr i} {
      set term [list [random_term] [random_term]]
      set match "\"$term\""
      do_test fts3rnd-1.$nodesize.$iTest.3.$i {
        execsql { SELECT docid FROM t1 WHERE t1 MATCH $match }
      } [simple_term $term]
    }
    
    # Three word phrases.
    #
    for {set i 0} {$i < 10} {incr i} {
      set term [list [random_term] [random_term] [random_term]]
      set match "\"$term\""
      do_test fts3rnd-1.$nodesize.$iTest.4.$i {
        execsql { SELECT docid FROM t1 WHERE t1 MATCH $match }
      } [simple_term $term]
    }

    # A NEAR query with terms as the arguments.
    #
if 0 {
    for {set i 0} {$i < 10} {incr i} {
      set terms [list [random_term] [random_term]]
      set match [join $terms " NEAR "]
      do_test fts3rnd-1.$nodesize.$iTest.5.$i {
        execsql { SELECT docid FROM t1 WHERE t1 MATCH $match }
      } [simple_near $terms 10]
    }
}
  }
}

finish_test