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public static final class DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder extends GeneratedMessage.Builder<DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder> implements DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfoOrBuilderThe profile information for an integer type field.
Protobuf type
google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo
Inheritance
java.lang.Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessage.Builder > DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.BuilderStatic Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()| Returns | |
|---|---|
| Type | Description |
Descriptor |
|
Methods
addAllQuartiles(Iterable<? extends Long> values)
public DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder addAllQuartiles(Iterable<? extends Long> values)Output only. A quartile divides the number of data points into four parts, or quarters, of more-or-less equal size. Three main quartiles used are: The first quartile (Q1) splits off the lowest 25% of data from the highest 75%. It is also known as the lower or 25th empirical quartile, as 25% of the data is below this point. The second quartile (Q2) is the median of a data set. So, 50% of the data lies below this point. The third quartile (Q3) splits off the highest 25% of data from the lowest 75%. It is known as the upper or 75th empirical quartile, as 75% of the data lies below this point. Here, the quartiles is provided as an ordered list of approximate quartile values for the scanned data, occurring in order Q1, median, Q3.
repeated int64 quartiles = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameter | |
|---|---|
| Name | Description |
values |
Iterable<? extends java.lang.Long>The quartiles to add. |
| Returns | |
|---|---|
| Type | Description |
DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder |
This builder for chaining. |
addQuartiles(long value)
public DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder addQuartiles(long value)Output only. A quartile divides the number of data points into four parts, or quarters, of more-or-less equal size. Three main quartiles used are: The first quartile (Q1) splits off the lowest 25% of data from the highest 75%. It is also known as the lower or 25th empirical quartile, as 25% of the data is below this point. The second quartile (Q2) is the median of a data set. So, 50% of the data lies below this point. The third quartile (Q3) splits off the highest 25% of data from the lowest 75%. It is known as the upper or 75th empirical quartile, as 75% of the data lies below this point. Here, the quartiles is provided as an ordered list of approximate quartile values for the scanned data, occurring in order Q1, median, Q3.
repeated int64 quartiles = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameter | |
|---|---|
| Name | Description |
value |
longThe quartiles to add. |
| Returns | |
|---|---|
| Type | Description |
DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder |
This builder for chaining. |
build()
public DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo build()| Returns | |
|---|---|
| Type | Description |
DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo |
|
buildPartial()
public DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo buildPartial()| Returns | |
|---|---|
| Type | Description |
DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo |
|
clear()
public DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder clear()| Returns | |
|---|---|
| Type | Description |
DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder |
|
clearAverage()
public DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder clearAverage()Output only. Average of non-null values in the scanned data. NaN, if the field has a NaN.
double average = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder |
This builder for chaining. |
clearMax()
public DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder clearMax()Output only. Maximum of non-null values in the scanned data. NaN, if the field has a NaN.
int64 max = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder |
This builder for chaining. |
clearMin()
public DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder clearMin()Output only. Minimum of non-null values in the scanned data. NaN, if the field has a NaN.
int64 min = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder |
This builder for chaining. |
clearQuartiles()
public DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder clearQuartiles()Output only. A quartile divides the number of data points into four parts, or quarters, of more-or-less equal size. Three main quartiles used are: The first quartile (Q1) splits off the lowest 25% of data from the highest 75%. It is also known as the lower or 25th empirical quartile, as 25% of the data is below this point. The second quartile (Q2) is the median of a data set. So, 50% of the data lies below this point. The third quartile (Q3) splits off the highest 25% of data from the lowest 75%. It is known as the upper or 75th empirical quartile, as 75% of the data lies below this point. Here, the quartiles is provided as an ordered list of approximate quartile values for the scanned data, occurring in order Q1, median, Q3.
repeated int64 quartiles = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder |
This builder for chaining. |
clearStandardDeviation()
public DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder clearStandardDeviation()Output only. Standard deviation of non-null values in the scanned data. NaN, if the field has a NaN.
double standard_deviation = 3 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder |
This builder for chaining. |
getAverage()
public double getAverage()Output only. Average of non-null values in the scanned data. NaN, if the field has a NaN.
double average = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
double |
The average. |
getDefaultInstanceForType()
public DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo getDefaultInstanceForType()| Returns | |
|---|---|
| Type | Description |
DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo |
|
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()| Returns | |
|---|---|
| Type | Description |
Descriptor |
|
getMax()
public long getMax()Output only. Maximum of non-null values in the scanned data. NaN, if the field has a NaN.
int64 max = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
long |
The max. |
getMin()
public long getMin()Output only. Minimum of non-null values in the scanned data. NaN, if the field has a NaN.
int64 min = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
long |
The min. |
getQuartiles(int index)
public long getQuartiles(int index)Output only. A quartile divides the number of data points into four parts, or quarters, of more-or-less equal size. Three main quartiles used are: The first quartile (Q1) splits off the lowest 25% of data from the highest 75%. It is also known as the lower or 25th empirical quartile, as 25% of the data is below this point. The second quartile (Q2) is the median of a data set. So, 50% of the data lies below this point. The third quartile (Q3) splits off the highest 25% of data from the lowest 75%. It is known as the upper or 75th empirical quartile, as 75% of the data lies below this point. Here, the quartiles is provided as an ordered list of approximate quartile values for the scanned data, occurring in order Q1, median, Q3.
repeated int64 quartiles = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameter | |
|---|---|
| Name | Description |
index |
intThe index of the element to return. |
| Returns | |
|---|---|
| Type | Description |
long |
The quartiles at the given index. |
getQuartilesCount()
public int getQuartilesCount()Output only. A quartile divides the number of data points into four parts, or quarters, of more-or-less equal size. Three main quartiles used are: The first quartile (Q1) splits off the lowest 25% of data from the highest 75%. It is also known as the lower or 25th empirical quartile, as 25% of the data is below this point. The second quartile (Q2) is the median of a data set. So, 50% of the data lies below this point. The third quartile (Q3) splits off the highest 25% of data from the lowest 75%. It is known as the upper or 75th empirical quartile, as 75% of the data lies below this point. Here, the quartiles is provided as an ordered list of approximate quartile values for the scanned data, occurring in order Q1, median, Q3.
repeated int64 quartiles = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
int |
The count of quartiles. |
getQuartilesList()
public List<Long> getQuartilesList()Output only. A quartile divides the number of data points into four parts, or quarters, of more-or-less equal size. Three main quartiles used are: The first quartile (Q1) splits off the lowest 25% of data from the highest 75%. It is also known as the lower or 25th empirical quartile, as 25% of the data is below this point. The second quartile (Q2) is the median of a data set. So, 50% of the data lies below this point. The third quartile (Q3) splits off the highest 25% of data from the lowest 75%. It is known as the upper or 75th empirical quartile, as 75% of the data lies below this point. Here, the quartiles is provided as an ordered list of approximate quartile values for the scanned data, occurring in order Q1, median, Q3.
repeated int64 quartiles = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
List<Long> |
A list containing the quartiles. |
getStandardDeviation()
public double getStandardDeviation()Output only. Standard deviation of non-null values in the scanned data. NaN, if the field has a NaN.
double standard_deviation = 3 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
double |
The standardDeviation. |
internalGetFieldAccessorTable()
protected GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()| Returns | |
|---|---|
| Type | Description |
FieldAccessorTable |
|
isInitialized()
public final boolean isInitialized()| Returns | |
|---|---|
| Type | Description |
boolean |
|
mergeFrom(DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo other)
public DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder mergeFrom(DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo other)| Parameter | |
|---|---|
| Name | Description |
other |
DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo |
| Returns | |
|---|---|
| Type | Description |
DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder |
|
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)| Parameters | |
|---|---|
| Name | Description |
input |
CodedInputStream |
extensionRegistry |
ExtensionRegistryLite |
| Returns | |
|---|---|
| Type | Description |
DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder |
|
| Exceptions | |
|---|---|
| Type | Description |
IOException |
|
mergeFrom(Message other)
public DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder mergeFrom(Message other)| Parameter | |
|---|---|
| Name | Description |
other |
Message |
| Returns | |
|---|---|
| Type | Description |
DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder |
|
setAverage(double value)
public DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder setAverage(double value)Output only. Average of non-null values in the scanned data. NaN, if the field has a NaN.
double average = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameter | |
|---|---|
| Name | Description |
value |
doubleThe average to set. |
| Returns | |
|---|---|
| Type | Description |
DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder |
This builder for chaining. |
setMax(long value)
public DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder setMax(long value)Output only. Maximum of non-null values in the scanned data. NaN, if the field has a NaN.
int64 max = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameter | |
|---|---|
| Name | Description |
value |
longThe max to set. |
| Returns | |
|---|---|
| Type | Description |
DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder |
This builder for chaining. |
setMin(long value)
public DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder setMin(long value)Output only. Minimum of non-null values in the scanned data. NaN, if the field has a NaN.
int64 min = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameter | |
|---|---|
| Name | Description |
value |
longThe min to set. |
| Returns | |
|---|---|
| Type | Description |
DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder |
This builder for chaining. |
setQuartiles(int index, long value)
public DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder setQuartiles(int index, long value)Output only. A quartile divides the number of data points into four parts, or quarters, of more-or-less equal size. Three main quartiles used are: The first quartile (Q1) splits off the lowest 25% of data from the highest 75%. It is also known as the lower or 25th empirical quartile, as 25% of the data is below this point. The second quartile (Q2) is the median of a data set. So, 50% of the data lies below this point. The third quartile (Q3) splits off the highest 25% of data from the lowest 75%. It is known as the upper or 75th empirical quartile, as 75% of the data lies below this point. Here, the quartiles is provided as an ordered list of approximate quartile values for the scanned data, occurring in order Q1, median, Q3.
repeated int64 quartiles = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameters | |
|---|---|
| Name | Description |
index |
intThe index to set the value at. |
value |
longThe quartiles to set. |
| Returns | |
|---|---|
| Type | Description |
DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder |
This builder for chaining. |
setStandardDeviation(double value)
public DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder setStandardDeviation(double value)Output only. Standard deviation of non-null values in the scanned data. NaN, if the field has a NaN.
double standard_deviation = 3 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameter | |
|---|---|
| Name | Description |
value |
doubleThe standardDeviation to set. |
| Returns | |
|---|---|
| Type | Description |
DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.Builder |
This builder for chaining. |