if (_conditionAggregation != null) {
            _conditionAggregation.getAggregationBuilderList().forEach(builder::addAggregation);
        }

        if (_specification != null) {
            builder.setFetchSource(_specification.columnList.toArray(new String[_specification.columnList.size()]), null);
        }

        return builder;
    }

        if (_conditionAggregation != null) {
            _conditionAggregation.getAggregationBuilderList().forEach(builder::addAggregation);
        }

        if (_specification != null) {
            builder.setFetchSource(_specification.columnList.toArray(new String[_specification.columnList.size()]), null);
        }

        return builder;
    }

        if (_conditionAggregation != null) {
            _conditionAggregation.getAggregationBuilderList().forEach(builder::addAggregation);
        }

        if (_specification != null) {
            builder.setFetchSource(_specification.columnList.toArray(new String[_specification.columnList.size()]), null);
        }

        return builder;
    }

        if (_conditionAggregation != null) {
            _conditionAggregation.getAggregationBuilderList().forEach(builder::addAggregation);
        }

        if (_specification != null) {
            builder.setFetchSource(_specification.columnList.toArray(new String[_specification.columnList.size()]), null);
        }

        return builder;
    }

        if (_conditionAggregation != null) {
            _conditionAggregation.getAggregationBuilderList().forEach(builder::addAggregation);
        }

        if (_specification != null) {
            builder.setFetchSource(_specification.columnList.toArray(new String[_specification.columnList.size()]), null);
        }

        return builder;
    }

        if (_conditionAggregation != null) {
            _conditionAggregation.getAggregationBuilderList().forEach(builder::addAggregation);
        }

        if (_specification != null) {
            builder.setFetchSource(_specification.columnList.toArray(new String[_specification.columnList.size()]), null);
        }

        return builder;
    }

        or other situation, under Python's version specification rules,
        `tensorflow[and-cuda]==2.15.0` will not install this fixed version.
        Please use `==2.15.0.post1` to specify this exact version on Linux
        platforms, or a fuzzy version specification, such as `==2.15.*`, to
        specify the most recent compatible version of TensorFlow 2.15 on all
        platforms.

  <mime-type type="application/vnd.ms-wpl">
    <glob pattern="*.wpl"/>
  </mime-type>
  <mime-type type="application/vnd.ms-xpsdocument">
    <alias type="application/oxps"/>
    <_comment>Open XML Paper Specification</_comment>
    <glob pattern="*.xps"/>
    <glob pattern="*.oxps"/>
    <sub-class-of type="application/x-tika-ooxml"/>
  </mime-type>

  <mime-type type="application/vnd.msa-disk-image">

- Removed the networking `alpha` API `ClusterCIDR`. ([#121229](https://github.com/kubernetes/kubernetes/pull/121229),...

use to accurately and efficiently track set membership across `apply` operations. The format used for `ApplySet` is set out in  [KEP 3659](https://github.com/kubernetes/enhancements/issues/3659) as a low-level specification.  Other tools in the ecosystem can also build on this specification for improved interoperability.  To try the ApplySet-based pruning alpha, set `KUBECTL_APPLYSET=true` and use the flags `--prune --applyset=secret-name` with `kubectl apply`. ([#116205](https://github.com/kuber...