}

    @Test
    public void test_longQuery() throws Exception {
        StringBuilder longQuery = new StringBuilder();
        for (int i = 0; i < 100; i++) {
            longQuery.append("word").append(i).append(" ");
        }
        String query = longQuery.toString().trim();

        QueryLog queryLog = new QueryLog(query, null);

        assertEquals(query, queryLog.getQueryString());
    }

        assertEquals(sampleTimeMillis + serverTimeZoneOffset, response.getLastWriteTime());
        assertEquals(1024, response.getSize());
    }

    /**
     * Test of readParameterWordsWireFormat method with zero word count.
     */
    @Test
    public void testReadParameterWordsWireFormatWithZeroWordCount() {
        byte[] buffer = new byte[20];
        response.wordCount = 0;

labels.suggest_word_configuration=Wort vorschlagen
labels.suggest_word_title_details=Wort vorschlagen
labels.suggest_word_type=Worttyp
labels.suggest_word_number=Anzahl der Wörter
labels.suggest_word_type_all=Alle
labels.suggest_word_type_document=Dokument
labels.suggest_word_type_query=Abfrage
labels.elevate_word_configuration=Wort erhöhen
labels.elevate_word_title_details=Wort erhöhen
labels.elevate_word_link_list=Liste

		the end of the term you are searching.
		<pre>Fess^100</pre>
	</dd>
	<dt>Fuzzy</dt>
	<dd>
		To do a fuzzy search use the "~" symbol at the end of a single word
		term. For example to search for a term similar in spelling to "Fess"
		use the fuzzy search:
		<pre>Fess~0.5</pre>
	</dd>

     * indicate how many bytes(note: readParameterWordsWireFormat
     * returns bytes read and not the number of words(but the
     * wordCount member DOES store the number of words)) we
     * actually read. Incedentally this is important to the
     * AndXServerMessageBlock class that needs to potentially
     * read in another smb's parameter words and bytes based on
     * information in it's andxCommand, andxOffset, ...etc.
     */

labels.facet_contentLength_5m=5 Mo -  
labels.facet_filetype_title=Type de fichier
labels.facet_filetype_html=HTML
labels.facet_filetype_word=MS Word
labels.facet_filetype_excel=MS Excel
labels.facet_filetype_powerpoint=MS PowerPoint
labels.facet_filetype_odt=ODF Word
labels.facet_filetype_ods=Feuille de calcul ODF
labels.facet_filetype_odp=Présentation ODF
labels.facet_filetype_pdf=PDF
labels.facet_filetype_fb2=FictionBook

        assertNotNull(ex.toString(), "toString should be safe to call");
    }

    @ParameterizedTest
    @NullAndEmptySource
    @ValueSource(strings = { "oops", "multi word", "中文" })
    @DisplayName("Message+Cause constructor: preserves both values; no interactions with cause")
    void messageAndCauseConstructor_preservesBoth(String message) {
        // Arrange & Act

labels.facet_contentLength_5m=5MB -  
labels.facet_filetype_title=Tipo de arquivo
labels.facet_filetype_html=HTML
labels.facet_filetype_word=MS Word
labels.facet_filetype_excel=MS Excel
labels.facet_filetype_powerpoint=MS PowerPoint
labels.facet_filetype_odt=ODF Word
labels.facet_filetype_ods=ODF Planilha
labels.facet_filetype_odp=ODF Apresentação
labels.facet_filetype_pdf=PDF
labels.facet_filetype_fb2=FictionBook

file: org.apache.spark.rdd.RDD[String] = s3a://testbucket/testdata MapPartitionsRDD[1] at textFile at <console>:24

scala> val counts = file.flatMap(line => line.split(" ")).map(word => (word, 1)).reduceByKey(_ + _)
counts: org.apache.spark.rdd.RDD[(String, Int)] = ShuffledRDD[4] at reduceByKey at <console>:25

scala> counts.saveAsTextFile("s3a://testbucket/wordcount")
```

</p>

<p>
Reads of memory locations larger than a single machine word
are encouraged but not required to meet the same semantics
as word-sized memory locations,
observing a single allowed write <i>w</i>.
For performance reasons,
implementations may instead treat larger operations
as a set of individual machine-word-sized operations
in an unspecified order.
This means that races on multiword data structures