Object
- io.delta.tables.DeltaTable

All Implemented Interfaces:

io.delta.tables.execution.DeltaTableOperations, java.io.Serializable, org.apache.spark.sql.delta.util.AnalysisHelper, scala.Serializable
```
public class DeltaTable
extends Object
implements io.delta.tables.execution.DeltaTableOperations, scala.Serializable
```
Main class for programmatically interacting with Delta tables. You can create DeltaTable instances using the static methods.
```
   DeltaTable.forPath(sparkSession, pathToTheDeltaTable)
 
```
Since:

0.3.0

See Also:

Serialized Form

Nested Class Summary
- Nested classes/interfaces inherited from interface org.apache.spark.sql.delta.util.AnalysisHelper
  org.apache.spark.sql.delta.util.AnalysisHelper.FakeLogicalPlan, org.apache.spark.sql.delta.util.AnalysisHelper.FakeLogicalPlan$

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`DeltaTable`	`alias(String alias)`	Apply an alias to the DeltaTable.
`DeltaTable`	`as(String alias)`	Apply an alias to the DeltaTable.
`static DeltaColumnBuilder`	`columnBuilder(String colName)`	:: Evolving ::
`static DeltaColumnBuilder`	`columnBuilder(org.apache.spark.sql.SparkSession spark, String colName)`	:: Evolving ::
`static DeltaTable`	`convertToDelta(org.apache.spark.sql.SparkSession spark, String identifier)`	Create a DeltaTable from the given parquet table.
`static DeltaTable`	`convertToDelta(org.apache.spark.sql.SparkSession spark, String identifier, String partitionSchema)`	Create a DeltaTable from the given parquet table and partition schema.
`static DeltaTable`	`convertToDelta(org.apache.spark.sql.SparkSession spark, String identifier, org.apache.spark.sql.types.StructType partitionSchema)`	Create a DeltaTable from the given parquet table and partition schema.
`static DeltaTableBuilder`	`create()`	:: Evolving ::
`static DeltaTableBuilder`	`create(org.apache.spark.sql.SparkSession spark)`	:: Evolving ::
`static DeltaTableBuilder`	`createIfNotExists()`	:: Evolving ::
`static DeltaTableBuilder`	`createIfNotExists(org.apache.spark.sql.SparkSession spark)`	:: Evolving ::
`static DeltaTableBuilder`	`createOrReplace()`	:: Evolving ::
`static DeltaTableBuilder`	`createOrReplace(org.apache.spark.sql.SparkSession spark)`	:: Evolving ::
`void`	`delete()`	Delete data from the table.
`void`	`delete(String condition)`	Delete data from the table that match the given `condition`.
`void`	`delete(org.apache.spark.sql.Column condition)`	Delete data from the table that match the given `condition`.
`org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>`	`detail()`	:: Evolving ::
`static DeltaTable`	`forName(String tableOrViewName)`	Instantiate a `DeltaTable` object using the given table or view name.
`static DeltaTable`	`forName(org.apache.spark.sql.SparkSession sparkSession, String tableName)`	Instantiate a `DeltaTable` object using the given table or view name using the given SparkSession.
`static DeltaTable`	`forPath(String path)`	Instantiate a `DeltaTable` object representing the data at the given path, If the given path is invalid (i.e.
`static DeltaTable`	`forPath(org.apache.spark.sql.SparkSession sparkSession, String path)`	Instantiate a `DeltaTable` object representing the data at the given path, If the given path is invalid (i.e.
`void`	`generate(String mode)`	Generate a manifest for the given Delta Table
`org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>`	`history()`	Get the information available commits on this table as a Spark DataFrame.
`org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>`	`history(int limit)`	Get the information of the latest `limit` commits on this table as a Spark DataFrame.
`static boolean`	`isDeltaTable(String identifier)`	Check if the provided `identifier` string, in this case a file path, is the root of a Delta table.
`static boolean`	`isDeltaTable(org.apache.spark.sql.SparkSession sparkSession, String identifier)`	Check if the provided `identifier` string, in this case a file path, is the root of a Delta table using the given SparkSession.
`DeltaMergeBuilder`	`merge(org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> source, String condition)`	Merge data from the `source` DataFrame based on the given merge `condition`.
`DeltaMergeBuilder`	`merge(org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> source, org.apache.spark.sql.Column condition)`	Merge data from the `source` DataFrame based on the given merge `condition`.
`DeltaOptimizeBuilder`	`optimize()`	Optimize the data layout of the table.
`static DeltaTableBuilder`	`replace()`	:: Evolving ::
`static DeltaTableBuilder`	`replace(org.apache.spark.sql.SparkSession spark)`	:: Evolving ::
`org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>`	`restoreToTimestamp(String timestamp)`	Restore the DeltaTable to an older version of the table specified by a timestamp.
`org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>`	`restoreToVersion(long version)`	Restore the DeltaTable to an older version of the table specified by version number.
`org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>`	`toDF()`	Get a DataFrame (that is, Dataset[Row]) representation of this Delta table.
`void`	`update(java.util.Map<String,org.apache.spark.sql.Column> set)`	Update rows in the table based on the rules defined by `set`.
`void`	`update(org.apache.spark.sql.Column condition, java.util.Map<String,org.apache.spark.sql.Column> set)`	Update data from the table on the rows that match the given `condition` based on the rules defined by `set`.
`void`	`update(org.apache.spark.sql.Column condition, scala.collection.immutable.Map<String,org.apache.spark.sql.Column> set)`	Update data from the table on the rows that match the given `condition` based on the rules defined by `set`.
`void`	`update(scala.collection.immutable.Map<String,org.apache.spark.sql.Column> set)`	Update rows in the table based on the rules defined by `set`.
`void`	`updateExpr(String condition, java.util.Map<String,String> set)`	Update data from the table on the rows that match the given `condition`, which performs the rules defined by `set`.
`void`	`updateExpr(String condition, scala.collection.immutable.Map<String,String> set)`	Update data from the table on the rows that match the given `condition`, which performs the rules defined by `set`.
`void`	`updateExpr(java.util.Map<String,String> set)`	Update rows in the table based on the rules defined by `set`.
`void`	`updateExpr(scala.collection.immutable.Map<String,String> set)`	Update rows in the table based on the rules defined by `set`.
`void`	`upgradeTableProtocol(int readerVersion, int writerVersion)`	Updates the protocol version of the table to leverage new features.
`org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>`	`vacuum()`	Recursively delete files and directories in the table that are not needed by the table for maintaining older versions up to the given retention threshold.
`org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>`	`vacuum(double retentionHours)`	Recursively delete files and directories in the table that are not needed by the table for maintaining older versions up to the given retention threshold.

Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.spark.sql.delta.util.AnalysisHelper
improveUnsupportedOpError, resolveReferencesForExpressions, toDataset, tryResolveReferences, tryResolveReferencesForExpressions

Methods inherited from interface io.delta.tables.execution.DeltaTableOperations
executeDelete, executeDetails, executeGenerate, executeHistory, executeHistory$default$2, executeHistory$default$3, executeRestore, executeUpdate, executeVacuum, executeVacuum$default$3, sparkSession, toStrColumnMap

- Method Detail
  - convertToDelta
```
public static DeltaTable convertToDelta(org.apache.spark.sql.SparkSession spark,
                                        String identifier,
                                        org.apache.spark.sql.types.StructType partitionSchema)
```
    Create a DeltaTable from the given parquet table and partition schema. Takes an existing parquet table and constructs a delta transaction log in the base path of that table.
    Note: Any changes to the table during the conversion process may not result in a consistent state at the end of the conversion. Users should stop any changes to the table before the conversion is started.
    An example usage would be
    io.delta.tables.DeltaTable.convertToDelta( spark, "parquet.`/path`", new StructType().add(StructField("key1", LongType)).add(StructField("key2", StringType)))
    Parameters:
    
    spark - (undocumented)
    
    identifier - (undocumented)
    
    partitionSchema - (undocumented)
    
    Since:
    
    0.4.0
  - convertToDelta
```
public static DeltaTable convertToDelta(org.apache.spark.sql.SparkSession spark,
                                        String identifier,
                                        String partitionSchema)
```
    Create a DeltaTable from the given parquet table and partition schema. Takes an existing parquet table and constructs a delta transaction log in the base path of that table.
    Note: Any changes to the table during the conversion process may not result in a consistent state at the end of the conversion. Users should stop any changes to the table before the conversion is started.
    An example usage would be
    io.delta.tables.DeltaTable.convertToDelta( spark, "parquet.`/path`", "key1 long, key2 string")
    Parameters:
    
    spark - (undocumented)
    
    identifier - (undocumented)
    
    partitionSchema - (undocumented)
    
    Since:
    
    0.4.0
  - convertToDelta
```
public static DeltaTable convertToDelta(org.apache.spark.sql.SparkSession spark,
                                        String identifier)
```
    Create a DeltaTable from the given parquet table. Takes an existing parquet table and constructs a delta transaction log in the base path of the table.
    Note: Any changes to the table during the conversion process may not result in a consistent state at the end of the conversion. Users should stop any changes to the table before the conversion is started.
    An Example would be
    io.delta.tables.DeltaTable.convertToDelta( spark, "parquet.`/path`"
    Parameters:
    
    spark - (undocumented)
    
    identifier - (undocumented)
    
    Since:
    
    0.4.0
  - forPath
```
public static DeltaTable forPath(String path)
```
    Instantiate a DeltaTable object representing the data at the given path, If the given path is invalid (i.e. either no table exists or an existing table is not a Delta table), it throws a not a Delta table error.
    Note: This uses the active SparkSession in the current thread to read the table data. Hence, this throws error if active SparkSession has not been set, that is, SparkSession.getActiveSession() is empty.
    
    Parameters:
    
    path - (undocumented)
    
    Since:
    
    0.3.0
  - forPath
```
public static DeltaTable forPath(org.apache.spark.sql.SparkSession sparkSession,
                                 String path)
```
    Instantiate a DeltaTable object representing the data at the given path, If the given path is invalid (i.e. either no table exists or an existing table is not a Delta table), it throws a not a Delta table error.
    
    Parameters:
    
    sparkSession - (undocumented)
    
    path - (undocumented)
    
    Since:
    
    0.3.0
  - forName
```
public static DeltaTable forName(String tableOrViewName)
```
    Instantiate a DeltaTable object using the given table or view name. If the given tableOrViewName is invalid (i.e. either no table exists or an existing table is not a Delta table), it throws a not a Delta table error.
    The given tableOrViewName can also be the absolute path of a delta datasource (i.e. delta.path), If so, instantiate a DeltaTable object representing the data at the given path (consistent with the forPath(java.lang.String)).
    Note: This uses the active SparkSession in the current thread to read the table data. Hence, this throws error if active SparkSession has not been set, that is, SparkSession.getActiveSession() is empty.
    
    Parameters:
    
    tableOrViewName - (undocumented)
  - forName
```
public static DeltaTable forName(org.apache.spark.sql.SparkSession sparkSession,
                                 String tableName)
```
    Instantiate a DeltaTable object using the given table or view name using the given SparkSession. If the given tableOrViewName is invalid (i.e. either no table exists or an existing table is not a Delta table), it throws a not a Delta table error.
    The given tableOrViewName can also be the absolute path of a delta datasource (i.e. delta.path), If so, instantiate a DeltaTable object representing the data at the given path (consistent with the forPath(java.lang.String)).
    
    Parameters:
    
    sparkSession - (undocumented)
    
    tableName - (undocumented)
  - isDeltaTable
```
public static boolean isDeltaTable(org.apache.spark.sql.SparkSession sparkSession,
                                   String identifier)
```
    Check if the provided identifier string, in this case a file path, is the root of a Delta table using the given SparkSession.
    An example would be
    DeltaTable.isDeltaTable(spark, "path/to/table")
    Parameters:
    
    sparkSession - (undocumented)
    
    identifier - (undocumented)
    
    Since:
    
    0.4.0
  - isDeltaTable
```
public static boolean isDeltaTable(String identifier)
```
    Check if the provided identifier string, in this case a file path, is the root of a Delta table.
    Note: This uses the active SparkSession in the current thread to search for the table. Hence, this throws error if active SparkSession has not been set, that is, SparkSession.getActiveSession() is empty.
    An example would be
    DeltaTable.isDeltaTable(spark, "/path/to/table")
    Parameters:
    
    identifier - (undocumented)
    
    Since:
    
    0.4.0
  - create
```
public static DeltaTableBuilder create()
```
    :: Evolving ::
    Return an instance of DeltaTableBuilder to create a Delta table, error if the table exists (the same as SQL CREATE TABLE). Refer to DeltaTableBuilder for more details.
    Note: This uses the active SparkSession in the current thread to read the table data. Hence, this throws error if active SparkSession has not been set, that is, SparkSession.getActiveSession() is empty.
    
    Since:
    
    1.0.0
  - create
```
public static DeltaTableBuilder create(org.apache.spark.sql.SparkSession spark)
```
    :: Evolving ::
    Return an instance of DeltaTableBuilder to create a Delta table, error if the table exists (the same as SQL CREATE TABLE). Refer to DeltaTableBuilder for more details.
    
    Parameters:
    
    spark - sparkSession sparkSession passed by the user
    
    Since:
    
    1.0.0
  - createIfNotExists
```
public static DeltaTableBuilder createIfNotExists()
```
    :: Evolving ::
    Return an instance of DeltaTableBuilder to create a Delta table, if it does not exists (the same as SQL CREATE TABLE IF NOT EXISTS). Refer to DeltaTableBuilder for more details.
    Note: This uses the active SparkSession in the current thread to read the table data. Hence, this throws error if active SparkSession has not been set, that is, SparkSession.getActiveSession() is empty.
    
    Since:
    
    1.0.0
  - createIfNotExists
```
public static DeltaTableBuilder createIfNotExists(org.apache.spark.sql.SparkSession spark)
```
    :: Evolving ::
    Return an instance of DeltaTableBuilder to create a Delta table, if it does not exists (the same as SQL CREATE TABLE IF NOT EXISTS). Refer to DeltaTableBuilder for more details.
    
    Parameters:
    
    spark - sparkSession sparkSession passed by the user
    
    Since:
    
    1.0.0
  - replace
```
public static DeltaTableBuilder replace()
```
    :: Evolving ::
    Return an instance of DeltaTableBuilder to replace a Delta table, error if the table doesn't exist (the same as SQL REPLACE TABLE) Refer to DeltaTableBuilder for more details.
    Note: This uses the active SparkSession in the current thread to read the table data. Hence, this throws error if active SparkSession has not been set, that is, SparkSession.getActiveSession() is empty.
    
    Since:
    
    1.0.0
  - replace
```
public static DeltaTableBuilder replace(org.apache.spark.sql.SparkSession spark)
```
    :: Evolving ::
    Return an instance of DeltaTableBuilder to replace a Delta table, error if the table doesn't exist (the same as SQL REPLACE TABLE) Refer to DeltaTableBuilder for more details.
    
    Parameters:
    
    spark - sparkSession sparkSession passed by the user
    
    Since:
    
    1.0.0
  - createOrReplace
```
public static DeltaTableBuilder createOrReplace()
```
    :: Evolving ::
    Return an instance of DeltaTableBuilder to replace a Delta table or create table if not exists (the same as SQL CREATE OR REPLACE TABLE) Refer to DeltaTableBuilder for more details.
    Note: This uses the active SparkSession in the current thread to read the table data. Hence, this throws error if active SparkSession has not been set, that is, SparkSession.getActiveSession() is empty.
    
    Since:
    
    1.0.0
  - createOrReplace
```
public static DeltaTableBuilder createOrReplace(org.apache.spark.sql.SparkSession spark)
```
    :: Evolving ::
    Return an instance of DeltaTableBuilder to replace a Delta table, or create table if not exists (the same as SQL CREATE OR REPLACE TABLE) Refer to DeltaTableBuilder for more details.
    
    Parameters:
    
    spark - sparkSession sparkSession passed by the user.
    
    Since:
    
    1.0.0
  - columnBuilder
```
public static DeltaColumnBuilder columnBuilder(String colName)
```
    :: Evolving ::
    Return an instance of DeltaColumnBuilder to specify a column. Refer to DeltaTableBuilder for examples and DeltaColumnBuilder detailed APIs.
    Note: This uses the active SparkSession in the current thread to read the table data. Hence, this throws error if active SparkSession has not been set, that is, SparkSession.getActiveSession() is empty.
    
    Parameters:
    
    colName - string the column name
    
    Since:
    
    1.0.0
  - columnBuilder
```
public static DeltaColumnBuilder columnBuilder(org.apache.spark.sql.SparkSession spark,
                                               String colName)
```
    :: Evolving ::
    Return an instance of DeltaColumnBuilder to specify a column. Refer to DeltaTableBuilder for examples and DeltaColumnBuilder detailed APIs.
    
    Parameters:
    
    spark - sparkSession sparkSession passed by the user
    
    colName - string the column name
    
    Since:
    
    1.0.0
  - as
```
public DeltaTable as(String alias)
```
    Apply an alias to the DeltaTable. This is similar to Dataset.as(alias) or SQL tableName AS alias.
    
    Parameters:
    
    alias - (undocumented)
    
    Since:
    
    0.3.0
  - alias
```
public DeltaTable alias(String alias)
```
    Apply an alias to the DeltaTable. This is similar to Dataset.as(alias) or SQL tableName AS alias.
    
    Parameters:
    
    alias - (undocumented)
    
    Since:
    
    0.3.0
  - toDF
```
public org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> toDF()
```
    Get a DataFrame (that is, Dataset[Row]) representation of this Delta table.
    
    Since:
    
    0.3.0
  - vacuum
```
public org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> vacuum(double retentionHours)
```
    Recursively delete files and directories in the table that are not needed by the table for maintaining older versions up to the given retention threshold. This method will return an empty DataFrame on successful completion.
    
    Parameters:
    
    retentionHours - The retention threshold in hours. Files required by the table for reading versions earlier than this will be preserved and the rest of them will be deleted.
    
    Since:
    
    0.3.0
  - vacuum
```
public org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> vacuum()
```
    Recursively delete files and directories in the table that are not needed by the table for maintaining older versions up to the given retention threshold. This method will return an empty DataFrame on successful completion.
    note: This will use the default retention period of 7 days.
    
    Since:
    
    0.3.0
  - history
```
public org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> history(int limit)
```
    Get the information of the latest limit commits on this table as a Spark DataFrame. The information is in reverse chronological order.
    
    Parameters:
    
    limit - The number of previous commands to get history for
    
    Since:
    
    0.3.0
  - history
```
public org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> history()
```
    Get the information available commits on this table as a Spark DataFrame. The information is in reverse chronological order.
    
    Since:
    
    0.3.0
  - detail
```
public org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> detail()
```
    :: Evolving ::
    Get the details of a Delta table such as the format, name, and size.
    
    Since:
    
    2.1.0
  - generate
```
public void generate(String mode)
```
    Generate a manifest for the given Delta Table
    
    Parameters:
    
    mode - Specifies the mode for the generation of the manifest. The valid modes are as follows (not case sensitive): - "symlink_format_manifest" : This will generate manifests in symlink format for Presto and Athena read support. See the online documentation for more information.
    
    Since:
    
    0.5.0
  - delete
```
public void delete(String condition)
```
    Delete data from the table that match the given condition.
    
    Parameters:
    
    condition - Boolean SQL expression
    
    Since:
    
    0.3.0
  - delete
```
public void delete(org.apache.spark.sql.Column condition)
```
    Delete data from the table that match the given condition.
    
    Parameters:
    
    condition - Boolean SQL expression
    
    Since:
    
    0.3.0
  - delete
```
public void delete()
```
    Delete data from the table.
    
    Since:
    
    0.3.0
  - optimize
```
public DeltaOptimizeBuilder optimize()
```
    Optimize the data layout of the table. This returns a DeltaOptimizeBuilder object that can be used to specify the partition filter to limit the scope of optimize and also execute different optimization techniques such as file compaction or order data using Z-Order curves.
    See the DeltaOptimizeBuilder for a full description of this operation.
    Scala example to run file compaction on a subset of partitions in the table:
    deltaTable .optimize() .where("date='2021-11-18'") .executeCompaction();
    Since:
    
    2.0.0
  - update
```
public void update(scala.collection.immutable.Map<String,org.apache.spark.sql.Column> set)
```
    Update rows in the table based on the rules defined by set.
    Scala example to increment the column data.
    import org.apache.spark.sql.functions._ deltaTable.update(Map("data" -> col("data") + 1))
    Parameters:
    
    set - rules to update a row as a Scala map between target column names and corresponding update expressions as Column objects.
    
    Since:
    
    0.3.0
  - update
```
public void update(java.util.Map<String,org.apache.spark.sql.Column> set)
```
    Update rows in the table based on the rules defined by set.
    Java example to increment the column data.
    import org.apache.spark.sql.Column; import org.apache.spark.sql.functions; deltaTable.update( new HashMap<String, Column>() {{ put("data", functions.col("data").plus(1)); }} );
    Parameters:
    
    set - rules to update a row as a Java map between target column names and corresponding update expressions as Column objects.
    
    Since:
    
    0.3.0
  - update
```
public void update(org.apache.spark.sql.Column condition,
                   scala.collection.immutable.Map<String,org.apache.spark.sql.Column> set)
```
    Update data from the table on the rows that match the given condition based on the rules defined by set.
    Scala example to increment the column data.
    import org.apache.spark.sql.functions._ deltaTable.update( col("date") > "2018-01-01", Map("data" -> col("data") + 1))
    Parameters:
    
    condition - boolean expression as Column object specifying which rows to update.
    
    set - rules to update a row as a Scala map between target column names and corresponding update expressions as Column objects.
    
    Since:
    
    0.3.0
  - update
```
public void update(org.apache.spark.sql.Column condition,
                   java.util.Map<String,org.apache.spark.sql.Column> set)
```
    Update data from the table on the rows that match the given condition based on the rules defined by set.
    Java example to increment the column data.
    import org.apache.spark.sql.Column; import org.apache.spark.sql.functions; deltaTable.update( functions.col("date").gt("2018-01-01"), new HashMap<String, Column>() {{ put("data", functions.col("data").plus(1)); }} );
    Parameters:
    
    condition - boolean expression as Column object specifying which rows to update.
    
    set - rules to update a row as a Java map between target column names and corresponding update expressions as Column objects.
    
    Since:
    
    0.3.0
  - updateExpr
```
public void updateExpr(scala.collection.immutable.Map<String,String> set)
```
    Update rows in the table based on the rules defined by set.
    Scala example to increment the column data.
    deltaTable.updateExpr(Map("data" -> "data + 1")))
    Parameters:
    
    set - rules to update a row as a Scala map between target column names and corresponding update expressions as SQL formatted strings.
    
    Since:
    
    0.3.0
  - updateExpr
```
public void updateExpr(java.util.Map<String,String> set)
```
    Update rows in the table based on the rules defined by set.
    Java example to increment the column data.
    deltaTable.updateExpr( new HashMap<String, String>() {{ put("data", "data + 1"); }} );
    Parameters:
    
    set - rules to update a row as a Java map between target column names and corresponding update expressions as SQL formatted strings.
    
    Since:
    
    0.3.0
  - updateExpr
```
public void updateExpr(String condition,
                       scala.collection.immutable.Map<String,String> set)
```
    Update data from the table on the rows that match the given condition, which performs the rules defined by set.
    Scala example to increment the column data.
    deltaTable.update( "date > '2018-01-01'", Map("data" -> "data + 1"))
    Parameters:
    
    condition - boolean expression as SQL formatted string object specifying which rows to update.
    
    set - rules to update a row as a Scala map between target column names and corresponding update expressions as SQL formatted strings.
    
    Since:
    
    0.3.0
  - updateExpr
```
public void updateExpr(String condition,
                       java.util.Map<String,String> set)
```
    Update data from the table on the rows that match the given condition, which performs the rules defined by set.
    Java example to increment the column data.
    deltaTable.update( "date > '2018-01-01'", new HashMap<String, String>() {{ put("data", "data + 1"); }} );
    Parameters:
    
    condition - boolean expression as SQL formatted string object specifying which rows to update.
    
    set - rules to update a row as a Java map between target column names and corresponding update expressions as SQL formatted strings.
    
    Since:
    
    0.3.0
  - merge
```
public DeltaMergeBuilder merge(org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> source,
                               String condition)
```
    Merge data from the source DataFrame based on the given merge condition. This returns a DeltaMergeBuilder object that can be used to specify the update, delete, or insert actions to be performed on rows based on whether the rows matched the condition or not.
    See the DeltaMergeBuilder for a full description of this operation and what combinations of update, delete and insert operations are allowed.
    Scala example to update a key-value Delta table with new key-values from a source DataFrame:
    deltaTable .as("target") .merge( source.as("source"), "target.key = source.key") .whenMatched .updateExpr(Map( "value" -> "source.value")) .whenNotMatched .insertExpr(Map( "key" -> "source.key", "value" -> "source.value")) .execute()
    
    Java example to update a key-value Delta table with new key-values from a source DataFrame:
    deltaTable .as("target") .merge( source.as("source"), "target.key = source.key") .whenMatched .updateExpr( new HashMap<String, String>() {{ put("value" -> "source.value"); }}) .whenNotMatched .insertExpr( new HashMap<String, String>() {{ put("key", "source.key"); put("value", "source.value"); }}) .execute();
    Parameters:
    
    source - source Dataframe to be merged.
    
    condition - boolean expression as SQL formatted string
    
    Since:
    
    0.3.0
  - merge
```
public DeltaMergeBuilder merge(org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> source,
                               org.apache.spark.sql.Column condition)
```
    Merge data from the source DataFrame based on the given merge condition. This returns a DeltaMergeBuilder object that can be used to specify the update, delete, or insert actions to be performed on rows based on whether the rows matched the condition or not.
    See the DeltaMergeBuilder for a full description of this operation and what combinations of update, delete and insert operations are allowed.
    Scala example to update a key-value Delta table with new key-values from a source DataFrame:
    deltaTable .as("target") .merge( source.as("source"), "target.key = source.key") .whenMatched .updateExpr(Map( "value" -> "source.value")) .whenNotMatched .insertExpr(Map( "key" -> "source.key", "value" -> "source.value")) .execute()
    
    Java example to update a key-value Delta table with new key-values from a source DataFrame:
    deltaTable .as("target") .merge( source.as("source"), "target.key = source.key") .whenMatched .updateExpr( new HashMap<String, String>() {{ put("value" -> "source.value") }}) .whenNotMatched .insertExpr( new HashMap<String, String>() {{ put("key", "source.key"); put("value", "source.value"); }}) .execute()
    Parameters:
    
    source - source Dataframe to be merged.
    
    condition - boolean expression as a Column object
    
    Since:
    
    0.3.0
  - restoreToVersion
```
public org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> restoreToVersion(long version)
```
    Restore the DeltaTable to an older version of the table specified by version number.
    An example would be
    io.delta.tables.DeltaTable.restoreToVersion(7)
    @since 1.2.0
    Parameters:
    
    version - (undocumented)
  - restoreToTimestamp
```
public org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> restoreToTimestamp(String timestamp)
```
    Restore the DeltaTable to an older version of the table specified by a timestamp.
    Timestamp can be of the format yyyy-MM-dd or yyyy-MM-dd HH:mm:ss
    An example would be
    io.delta.tables.DeltaTable.restoreToTimestamp("2019-01-01")
    @since 1.2.0
    Parameters:
    
    timestamp - (undocumented)
  - upgradeTableProtocol
```
public void upgradeTableProtocol(int readerVersion,
                                 int writerVersion)
```
    Updates the protocol version of the table to leverage new features. Upgrading the reader version will prevent all clients that have an older version of Delta Lake from accessing this table. Upgrading the writer version will prevent older versions of Delta Lake to write to this table. The reader or writer version cannot be downgraded.
    See online documentation and Delta's protocol specification at PROTOCOL.md for more details.
    
    Parameters:
    
    readerVersion - (undocumented)
    
    writerVersion - (undocumented)
    
    Since:
    
    0.8.0

Class DeltaTable

Nested Class Summary

Nested classes/interfaces inherited from interface org.apache.spark.sql.delta.util.AnalysisHelper

Method Summary

Methods inherited from class java.lang.Object

Methods inherited from interface org.apache.spark.sql.delta.util.AnalysisHelper

Methods inherited from interface io.delta.tables.execution.DeltaTableOperations

Method Detail

convertToDelta

convertToDelta

convertToDelta

forPath

forPath

forName

forName

isDeltaTable

isDeltaTable

create

create

createIfNotExists

createIfNotExists

replace

replace

createOrReplace

createOrReplace

columnBuilder

columnBuilder

as

alias

toDF

vacuum

vacuum

history

history

detail

generate

delete

delete

delete

optimize

update

update

update

update

updateExpr

updateExpr

updateExpr

updateExpr

merge

merge

restoreToVersion

restoreToTimestamp

upgradeTableProtocol