[jira] [Updated] (DRILL-5955) Revisit Union Vectors
[
https://issues.apache.org/jira/browse/DRILL-5955?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Paul Rogers updated DRILL-5955:
---
Description:
Drill supports a “Union Vector” type that allows a single column to hold values
of multiple types. Conceptually, each column value is a (type, value) pair. For
example, row 0 might be an Int, row 1 a Varchar and row 2 a NULL value.
The name refers to a C “union” in which the same bit of memory is used to
represent one of a set of defined types.
Drill implements the union vector a bit like a map: as a collection of typed
vectors. Each value is keyed by type. The result is that a union vector is more
like a C “struct” than a C “union”: every vector takes space, but only one of
the vectors is used for each row. For the example above, the union vector
contains an Int vector, a Varchar vector and a type vector. For each row,
either the Int or the Varchar is used. For NULL values, neither vector is used.
h4. Memory Footprint Concerns
The current representation, despite its name, makes very inefficient use of
memory because it requires the sum of the storage for each included type. (That
is, if we store 1000 rows, we need 1000 slots for integers, another 1000 for
Varchar and yet another 1000 for the type vector.)
Drill poorly supports the union type. One operator that does support it is the
sort. If the union type is enabled, and the sort sees a schema change, the sort
will create a new union vector that combines the two types. The result is a
sudden, unplanned increase in memory usage. Since the sort can buffer many
hundreds of batches, this unplanned memory increase can cause the sort to run
out of memory.
h4. Muddy Semantics
The union vector is closely tied with the List vector: a list vector is,
essentially, an array of unions. (See DRILL-5958). The list type is used to
model JSON in which a list can hold anything: another list, an object or
scalars. For this reason, the union vector also can hold any type. And, indeed,
it can hold a union of any of these types: a Map and an Int, or a List and a
Map.
Drill is a relational, SQL-based tool. Work is required to bring non-relational
structures into Drill. As discussed below, a union of scalars can be made to
work. But, a union of structured types (lists, arrays or Maps) makes no sense.
h4. High Complexity
The union vector, as implemented is quite complex. It contains member variables
for every other vector type (except, strangely, the decimal types.) Access to
typed members is by type-specific methods, meaning that the client code must
include a separate call for every type, resulting in very complex client code.
The complexity allowed the union type to be made to work, but causes this one
type to consume a disproportionate amount of the vector and client code.
h4. Proposed Revision to Structure: The Variant Type
Given the above, we can now present the proposed changes. First let us
recognize that a union vector need not hold structured types; there are other
solutions as discussed in DRILL-. This leaves the union vector to hold just
scalars.
h4. Proposed Revision to Storage
This in turn lets us adopt the [Variant
type|https://en.wikipedia.org/wiki/Variant_type] originally introduced in
Visual Basic. Variant “is a tagged union that can be used to represent any
other data type”. The Variant type was designed to be compact by building on
the idea of a tagged union in C.
{code}
struct {
int tag; // type
union {
int intValue;
long longValue;
…
}
}
{code}
When implemented as a vector, the format could consume just a single
variable-width vector with each entry of the form: {{\[type value]}}. The
vector is simply a sequence of these (type, value) pairs.
The type is a single-byte that encodes the MinorType that describes the value.
That is, the type byte is like the existing type vector, but stored in the same
location as the data. The data is simply the serialized format of data. (Four
bytes for an Int, 8 bytes for a Float8 and so on.)
Variable-width types require an extra field: the type field: {{\[type length
value]}}. For example, a Varchar would be encoded as {{\[Varchar 27 byte0-26]}}.
A writer uses the type to drive the serialization. A reader uses the type to
drive deserialization.
Note that the type field must include a special marker for nulls. Today, the
union type uses 0 to indicate a null value. (Note that, in a union and variant,
a null value is not a null of some type, both the type and value are null.)
That form should be used in the variant representation as well. But, note that
the 0 value in the MajorType enum is not Null but is instead Late. This is an
unpleasant messiness that the union (and variant )encoding must handle.
An offset vector provides the location of each field, as is done with
variable-length vectors today.
The result is huge compaction of
[jira] [Updated] (DRILL-5955) Revisit Union Vectors
[
https://issues.apache.org/jira/browse/DRILL-5955?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Paul Rogers updated DRILL-5955:
---
Description:
Drill supports a “Union Vector” type that allows a single column to hold values
of multiple types. Conceptually, each column value is a (type, value) pair. For
example, row 0 might be an Int, row 1 a Varchar and row 2 a NULL value.
The name refers to a C “union” in which the same bit of memory is used to
represent one of a set of defined types.
Drill implements the union vector a bit like a map: as a collection of typed
vectors. Each value is keyed by type. The result is that a union vector is more
like a C “struct” than a C “union”: every vector takes space, but only one of
the vectors is used for each row. For the example above, the union vector
contains an Int vector, a Varchar vector and a type vector. For each row,
either the Int or the Varchar is used. For NULL values, neither vector is used.
h4. Memory Footprint Concerns
The current representation, despite its name, makes very inefficient use of
memory because it requires the sum of the storage for each included type. (That
is, if we store 1000 rows, we need 1000 slots for integers, another 1000 for
Varchar and yet another 1000 for the type vector.)
Drill poorly supports the union type. One operator that does support it is the
sort. If the union type is enabled, and the sort sees a schema change, the sort
will create a new union vector that combines the two types. The result is a
sudden, unplanned increase in memory usage. Since the sort can buffer many
hundreds of batches, this unplanned memory increase can cause the sort to run
out of memory.
h4. Muddy Semantics
The union vector is closely tied with the List vector: a list vector is,
essentially, an array of unions. (See DRILL-). The list type is used to
model JSON in which a list can hold anything: another list, an object or
scalars. For this reason, the union vector also can hold any type. And, indeed,
it can hold a union of any of these types: a Map and an Int, or a List and a
Map.
Drill is a relational, SQL-based tool. Work is required to bring non-relational
structures into Drill. As discussed below, a union of scalars can be made to
work. But, a union of structured types (lists, arrays or Maps) makes no sense.
h4. High Complexity
The union vector, as implemented is quite complex. It contains member variables
for every other vector type (except, strangely, the decimal types.) Access to
typed members is by type-specific methods, meaning that the client code must
include a separate call for every type, resulting in very complex client code.
The complexity allowed the union type to be made to work, but causes this one
type to consume a disproportionate amount of the vector and client code.
h4. Proposed Revision to Structure: The Variant Type
Given the above, we can now present the proposed changes. First let us
recognize that a union vector need not hold structured types; there are other
solutions as discussed in DRILL-. This leaves the union vector to hold just
scalars.
h4. Proposed Revision to Storage
This in turn lets us adopt the [Variant
type|https://en.wikipedia.org/wiki/Variant_type] originally introduced in
Visual Basic. Variant “is a tagged union that can be used to represent any
other data type”. The Variant type was designed to be compact by building on
the idea of a tagged union in C.
{code}
struct {
int tag; // type
union {
int intValue;
long longValue;
…
}
}
{code}
When implemented as a vector, the format could consume just a single
variable-width vector with each entry of the form: {{\[type value]}}. The
vector is simply a sequence of these (type, value) pairs.
The type is a single-byte that encodes the MinorType that describes the value.
That is, the type byte is like the existing type vector, but stored in the same
location as the data. The data is simply the serialized format of data. (Four
bytes for an Int, 8 bytes for a Float8 and so on.)
Variable-width types require an extra field: the type field: {{\[type length
value]}}. For example, a Varchar would be encoded as {{\[Varchar 27 byte0-26]}}.
A writer uses the type to drive the serialization. A reader uses the type to
drive deserialization.
Note that the type field must include a special marker for nulls. Today, the
union type uses 0 to indicate a null value. (Note that, in a union and variant,
a null value is not a null of some type, both the type and value are null.)
That form should be used in the variant representation as well. But, note that
the 0 value in the MajorType enum is not Null but is instead Late. This is an
unpleasant messiness that the union (and variant )encoding must handle.
An offset vector provides the location of each field, as is done with
variable-length vectors today.
The result is huge compaction of
[jira] [Updated] (DRILL-5955) Revisit Union Vectors
[
https://issues.apache.org/jira/browse/DRILL-5955?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Paul Rogers updated DRILL-5955:
---
Description:
Drill supports a “Union Vector” type that allows a single column to hold values
of multiple types. Conceptually, each column value is a (type, value) pair. For
example, row 0 might be an Int, row 1 a Varchar and row 2 a NULL value.
The name refers to a C “union” in which the same bit of memory is used to
represent one of a set of defined types.
Drill implements the union vector a bit like a map: as a collection of typed
vectors. Each value is keyed by type. The result is that a union vector is more
like a C “struct” than a C “union”: every vector takes space, but only one of
the vectors is used for each row. For the example above, the union vector
contains an Int vector, a Varchar vector and a type vector. For each row,
either the Int or the Varchar is used. For NULL values, neither vector is used.
h4. Memory Footprint Concerns
The current representation, despite its name, makes very inefficient use of
memory because it requires the sum of the storage for each included type. (That
is, if we store 1000 rows, we need 1000 slots for integers, another 1000 for
Varchar and yet another 1000 for the type vector.)
Drill poorly supports the union type. One operator that does support it is the
sort. If the union type is enabled, and the sort sees a schema change, the sort
will create a new union vector that combines the two types. The result is a
sudden, unplanned increase in memory usage. Since the sort can buffer many
hundreds of batches, this unplanned memory increase can cause the sort to run
out of memory.
h4. Muddy Semantics
The union vector is closely tied with the List vector: a list vector is,
essentially, an array of unions. (See DRILL-). The list type is used to
model JSON in which a list can hold anything: another list, an object or
scalars. For this reason, the union vector also can hold any type. And, indeed,
it can hold a union of any of these types: a Map and an Int, or a List and a
Map.
Drill is a relational, SQL-based tool. Work is required to bring non-relational
structures into Drill. As discussed below, a union of scalars can be made to
work. But, a union of structured types (lists, arrays or Maps) makes no sense.
h4. High Complexity
The union vector, as implemented is quite complex. It contains member variables
for every other vector type (except, strangely, the decimal types.) Access to
typed members is by type-specific methods, meaning that the client code must
include a separate call for every type, resulting in very complex client code.
The complexity allowed the union type to be made to work, but causes this one
type to consume a disproportionate amount of the vector and client code.
h4. Proposed Revision to Structure: The Variant Type
Given the above, we can now present the proposed changes. First let us
recognize that a union vector need not hold structured types; there are other
solutions as discussed in DRILL-. This leaves the union vector to hold just
scalars.
h4. Proposed Revision to Storage
This in turn lets us adopt the [Variant
type|https://en.wikipedia.org/wiki/Variant_type] originally introduced in
Visual Basic. Variant “is a tagged union that can be used to represent any
other data type”. The Variant type was designed to be compact by building on
the idea of a tagged union in C.
{code}
struct {
int tag; // type
union {
int intValue;
long longValue;
…
}
}
{code}
When implemented as a vector, the format could consume just a single
variable-width vector with each entry of the form: {{\[type value]}}. The
vector is simply a sequence of these (type, value) pairs.
The type is a single-byte that encodes the MinorType that describes the value.
That is, the type byte is like the existing type vector, but stored in the same
location as the data. The data is simply the serialized format of data. (Four
bytes for an Int, 8 bytes for a Float8 and so on.)
Variable-width types require an extra field: the type field: {{\[type length
value]}}. For example, a Varchar would be encoded as {{\[Varchar 27 byte0-26]}}.
A writer uses the type to drive the serialization. A reader uses the type to
drive deserialization.
Note that the type field must include a special marker for nulls. Today, the
union type uses 0 to indicate a null value. (Note that, in a union and variant,
a null value is not a null of some type, both the type and value are null.)
That form should be used in the variant representation as well. But, note that
the 0 value in the MajorType enum is not Null but is instead Late. This is an
unpleasant messiness that the union (and variant )encoding must handle.
An offset vector provides the location of each field, as is done with
variable-length vectors today.
The result is huge compaction of
