if results[1] != "" {
				tx.Statement.Table = results[1]
			} else {
				tx.Statement.Table = results[2]
			}
		}
	} else if tables := strings.Split(name, "."); len(tables) == 2 {
		tx.Statement.TableExpr = &clause.Expr{SQL: tx.Statement.Quote(name)}
		tx.Statement.Table = tables[1]
	} else if name != "" {
		tx.Statement.TableExpr = &clause.Expr{SQL: tx.Statement.Quote(name)}

        for (final Map.Entry<String, String> entry : metaConfigMap.entrySet()) {
            final String key = entry.getKey();
            final String[] values = entry.getValue().split(",");
            for (final String value : values) {
                putResultDataWithTemplate(dataMap, key, metaDataMap.get(value), scriptConfigMap.get(key), scriptType);
            }
        }

    assertNotNull(ArbitraryInstances.get(Locale.class));
    assertNotNull(ArbitraryInstances.get(Joiner.class).join(ImmutableList.of("a")));
    assertNotNull(ArbitraryInstances.get(Splitter.class).split("a,b"));
    assertThat(ArbitraryInstances.get(com.google.common.base.Optional.class)).isAbsent();
    ArbitraryInstances.get(Stopwatch.class).start();
    assertNotNull(ArbitraryInstances.get(Ticker.class));

```
scala> val file = sc.textFile("s3a://testbucket/testdata")
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")
```

        if (last >= 0 && name.charAt(last) == '/') {
            trailingSlash = true;
            name = name.substring(0, last);
        }

        if (shr == null) {
            final String[] nameParts = name.split("/");

            // server is set through URL, however it's still in the name
            int pos = 0;
            if (context.getServer() == null) {
                pos = 1;
            }

     */
    private Iterator<String> linesIterator() {
      return new AbstractIterator<String>() {
        final Iterator<String> lines = LINE_SPLITTER.split(seq).iterator();

        @Override
        protected @Nullable String computeNext() {
          if (lines.hasNext()) {
            String next = lines.next();
            // skip last line if it's empty

     */
    private Iterator<String> linesIterator() {
      return new AbstractIterator<String>() {
        final Iterator<String> lines = LINE_SPLITTER.split(seq).iterator();

        @Override
        protected @Nullable String computeNext() {
          if (lines.hasNext()) {
            String next = lines.next();
            // skip last line if it's empty

        final String value = fessConfig.getPurgeByBots();
        String[] botNames;
        if (StringUtil.isBlank(value)) {
            botNames = StringUtil.EMPTY_STRINGS;
        } else {
            botNames = value.split(",");
        }

        final int batchSize = fessConfig.getSearchlogProcessBatchSizeAsInteger();

        final List<SearchLog> searchLogList = new ArrayList<>();

      case 2:
        return nums.get(start).multiply(nums.get(start + 1));
      case 3:
        return nums.get(start).multiply(nums.get(start + 1)).multiply(nums.get(start + 2));
      default:
        // Otherwise, split the list in half and recursively do this.
        int m = (end + start) >>> 1;
        return listProduct(nums, start, m).multiply(listProduct(nums, m, end));
    }
  }

  /**

        `tf.sparse.cross`/`tf.ragged.cross` directly.
    *   Added additional `standardize` and `split` modes to `TextVectorization`:
        *   `standardize="lower"` will lowercase inputs.
        *   `standardize="string_punctuation"` will remove all punctuation.
        *   `split="character"` will split on every unicode character.
    *   Added an `output_mode` argument to the `Discretization` and `Hashing`