switch ef.Type {
	case BatchJobExpireObject:
		if obj.DeleteMarker {
			return false
		}
	case BatchJobExpireDeleted:
		if !obj.DeleteMarker {
			return false
		}
	default:
		// we should never come here, Validate should have caught this.
		batchLogOnceIf(context.Background(), fmt.Errorf("invalid filter type: %s", ef.Type), ef.Type)
		return false
	}

	if len(ef.Name) > 0 && !wildcard.Match(ef.Name, obj.Name) {

func loadBucketMetadataParse(ctx context.Context, objectAPI ObjectLayer, bucket string, parse bool) (BucketMetadata, error) {
	b, err := readBucketMetadata(ctx, objectAPI, bucket)
	b.Name = bucket // in-case parsing failed for some reason, make sure bucket name is not empty.
	if err != nil && !errors.Is(err, errConfigNotFound) {
		return b, err
	}
	if err == nil {
		b.defaultTimestamps()
	}

- Sometimes, the scheduler incorrectly placed a pod in the "unschedulable" queue instead of the "backoff" queue. This happened when some plugin previously declared the pod as "unschedulable" and then in a later attempt encounters some other error. Scheduling of that pod then got delayed by up to five minutes, after which periodic flushing moved the pod back into the "active" queue. ([#120334](https://github.com/kubernetes/kubernetes/pull/120334),...

                storedParams = crawlingInfoParamList;
            }
        }, CrawlingInfoService.class.getCanonicalName());

        // Add some info to map
        crawlingInfoHelper.putToInfoMap("url_count", "100");
        crawlingInfoHelper.putToInfoMap("error_count", "5");

        // Store with create=true
        crawlingInfoHelper.store(sessionId, true);

import java.util.Arrays;
import java.util.List;
import java.util.Random;
import junit.framework.TestSuite;
import org.jspecify.annotations.NullUnmarked;

/**
 * Unit test for {@link Files}.
 *
 * <p>Some methods are tested in separate files:
 *
 * <ul>
 *   <li>{@link Files#fileTraverser()} is tested in {@link FilesFileTraverserTest}.
 *   <li>{@link Files#createTempDir()} is tested in {@link FilesCreateTempDirTest}.
 * </ul>

    return arrayType.cast(Array.newInstance(requireNonNull(arrayType.getComponentType()), 0));
  }

  // Internal implementations of some classes, with public default constructor that get() needs.
  private static final class Dummies {

    @Keep
    public static final class InMemoryPrintStream extends PrintStream {
      @Keep

		return Endpoints{}
	}
	return disksToHeal
}

var newDiskHealingTimeout = newDynamicTimeout(30*time.Second, 10*time.Second)

var errRetryHealing = errors.New("some items failed to heal, we will retry healing this drive again")

func healFreshDisk(ctx context.Context, z *erasureServerPools, endpoint Endpoint) error {
	poolIdx, setIdx := endpoint.PoolIdx, endpoint.SetIdx

package gorm

import (
	"fmt"
	"reflect"
	"strings"

	"gorm.io/gorm/clause"
	"gorm.io/gorm/schema"
	"gorm.io/gorm/utils"
)

// Association Mode contains some helper methods to handle relationship things easily.
type Association struct {
	DB           *DB
	Relationship *schema.Relationship
	Unscope      bool
	Error        error
}

func (db *DB) Association(column string) *Association {

![hive-config](https://github.com/minio/minio/blob/master/docs/bigdata/images/image14.png?raw=true "restart hive services")

## **4. Run Sample Applications**

After installing Hive, Hadoop and Spark successfully, we can now proceed to run some sample applications to see if they are configured appropriately.  We can use Spark Pi and Spark WordCount programs to validate our Spark installation. We can also explore how to run Spark jobs from the command line and Spark shell.

			c = 'N'
		}
		buf.WriteByte(c)
	}
	if addNewline {
		if doCR {
			buf.WriteByte('\r')
		}
		buf.WriteByte('\n')
	}
}

// Test the line splitter, including some carriage returns but no long lines.
func TestScanLongLines(t *testing.T) {
	// Build a buffer of lots of line lengths up to but not exceeding smallMaxTokenSize.
	tmp := new(bytes.Buffer)
	buf := new(bytes.Buffer)