The DELite Project: Database Support for Embedded Lightweight Devices

Prof. Krithi Ramamritham

April 8, 2023 2

Outline of the talkOutline of the talk

Need for small footprint DBMSs New Issues in Implementation Project Goals Review of Existing Work Current Implementation Status

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Small DBMSs, e.g., for HandheldsSmall DBMSs, e.g., for Handhelds

Small, Convenient, Carry anywhere Powerful

E.g. Simputer- 206MHz, 32MB SDRAM, 24 MB Flash memory, LCD display, Smart card

Applications Personal Info Management

E-dairy

Enterprise Applications Health-care, Micro-banking

April 8, 2023 4

Need for Handheld DBMSNeed for Handheld DBMS

Handheld applications Volume of data is high Simple and Complex Queries

select, project, aggregate

ACID properties of transactions Require Data Privacy Need Synchronization

Database management techniques are needed to meet the above requirements

April 8, 2023 5

New Issues in ImplementationNew Issues in Implementation

Small DBMS vs. Disk DBMS Handheld DB is Flash memory based

Disk read time is very small Storage model should consider small memory and

computation power Transaction management and synchronization have

to consider disconnections, mobility and communication cost

Handheld Operating System provides lesser facilities E.g. no multi-threading support in PalmOS

Better security measures are required as handhelds are easily stolen, damaged and lost

April 8, 2023 6

Project GoalsProject Goals

Existing work – Investigations of

Storage models Query processing & optimization Executor

Proposed work Compression in Storage Transaction management Synchronization

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Existing Work – ReviewExisting Work – Review

Storage Management Aim at compactness in representation of

data Limited storage could preclude any

additional index Data model should try to incorporate some index

information

Query Processing Minimize writes to secondary storage Efficient usage of limited main memory

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Storage ManagementStorage Management

Existing storage models Flat Storage

Tuples are stored sequentially. Duplicates not eliminated

Pointer-based Domain Storage Values partitioned into domains which are sets

of unique values Tuples reference the attribute value by means

of pointers One domain shared among multiple attributes

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Storage Management (cont)Storage Management (cont)

10 20

3040

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Flat Relation

CSE11

CSE11

CSE11CSE11

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DomainRelation

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Flat Storage Domain Storage

In Domain Storage, pointer of size p (typically 4 bytes) points to the domain value. Can we further reduce the storage cost?

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ID Based StorageID Based Storage

Relation R ID Values

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Domain Values

Positional Indexing

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ID Based StorageID Based Storage

ID Storage An identifier for each of the domain values Store the smaller identifier instead of the

pointer Identifier is the positional value in the

domain table. Use it as an offset into the domain table

D domain values can be distinguished by identifiers of length log2D /8 bytes.

April 8, 2023 12

ID Storage (cont)ID Storage (cont)

Extendable IDs are used. Length of the identifier grows and shrinks depending on the number of domain values

Starting with 1 byte identifiers, the length grows and shrinks.

To reduce reorganization of data, ID values are projected out from the rest of the relation and stored separately maintaining Positional Indexing.

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ID Storage (cont)ID Storage (cont) Ping Pong Effect

At the boundaries, there is reorganization of ID values when the identifier length changes Frequent insertions and deletions at the boundaries might result in a lot of reorganization Phenomena should be avoided

No deletion of Domain values Domain structure means a future insertion might reference the deleted value Do not delete a domain value even it is not referenced

Setting a threshold for deletion for domain values Delete only if number of deletions exceeds a threshold Increase the threshold when boundaries are being crossed

to reduce ping pong effect

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ID Storage (cont)ID Storage (cont) Primary Key-Foreign Key relationship

Primary key is a domain in itself IDs for primary key values Values present in child table are the corresponding primary

key IDs Projected foreign key column forms a Join Index

Figure: Primary Key-Foreign Key Join Index

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Parent TableRelation R

Child Table

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ID Storage (cont)ID Storage (cont)

ID based Storage wins over Domain Storage when pointer size > log2D /8

Relations in a small device do not have a very high cardinality.

Above condition true for most of the data. Advantages of ID storage

Considerable saving in storage cost. Efficient join between parent table and child

table

April 8, 2023 16

Query ProcessingQuery Processing

Considerations Minimize writes to secondary storage Use Main memory as write buffer

Need for Left-deep Query Plan Reduce materialization in flash memory. If

absolutely necessary use main memory Bushy trees use materialization Left deep tree is most suited for pipelined

evaluation Right operand in a left-deep tree is always a

stored relation

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Query Processing (cont)Query Processing (cont)

Need for optimal memory allocation Using nested loop algorithms for every operator

ensures that minimum amount of memory used to execute the plan

Nested loop algorithms are inefficient Different devices come with different memory sizes Query plans should make efficient use of memory.

Memory must be optimally allocated among all operators

Need to generate the best query execution plan depending on the available memory

April 8, 2023 18

Query Processing (cont)Query Processing (cont)

Operator evaluation schemes Different schemes for an operator Schemes conform to left-deep tree query

plan All have different memory usage and cost Cost of a scheme is the computation time

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Query Processing (cont)Query Processing (cont)

2-Phase optimizer Phase 1: Query is first optimized to get a query plan Phase 2: Division of memory among the operators Scheme for every operator is determined in phase 1

and remains unchanged after phase 2, memory allocation in phase 2 is on the basis of the cost functions of the schemes

Memory is assumed to be available for all the schemes, this may not be true for a resource constrained device

Traditional 2-phase optimization cannot be used

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Query Processing (cont)Query Processing (cont)

1-Phase optimizer Query optimizer is made memory cognizant Modified optimizer takes into account

division of memory among operators while choosing between plans

Ideally, 1-phase optimization should be done but the optimizer becomes complex.

April 8, 2023 21

Query Processing (cont)Query Processing (cont)

Modified 2-phase optimizer Optimal division of memory involves the

decision of selecting the best scheme for every operator

Phase 1: Determine the optimal left-deep join order using

dynamic programming approach

Phase 2: Divide memory among the operators Choose the scheme for every operator depending

on the memory allocated

April 8, 2023 22

Query Processing (cont)Query Processing (cont)

Memory allocation algorithms Exact memory allocation Heuristic memory allocation

Conclusions Response times highest with minimum

memory and least with maximum memory Computing power of the handheld affects

the response time in a big way Heuristic memory allocation differed from

exact algorithm in a few points only

April 8, 2023 23

Compression in DBCompression in DB

Advantages Saves space Reduces read time and write time as less

data is processed Logging consumes less space and time

Disadvantages CPU intensive Competes with other CPU intensive DBMS

tasks. May slow down the DBMS

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Compression in Disk DBCompression in Disk DB

Main assumption The high disk read time compensates for the extra

time required for compression and decompression E.g. Let time taken to read 10 blocks of data from the

disk be 10ms. Let the time taken for compression and decompression be 5ms. After compression 10 blocks occupy only 1 block.

Processing time with compression/decompression = ( 1ms + 5ms) = 6ms

Handheld DB is Flash memory based Read time is very less. Above assumption is no

longer valid!!

April 8, 2023 25

Transaction ManagementTransaction Management

Ensure ACID properties of local and global transactions Local transaction - Update address book

entry in Simputer Global transaction - Transfer money from a

bank account to an epurse in a smart card attached to a Simputer

Issues Frequent disconnections, resource

constraints, mobility, loss or damage to handheld

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SynchronizationSynchronization

Access data Anytime and Anywhere using the handheld Mobile sales person, Wireless ware house

Problem – Not possible to remain connected always

Solution- Replicate data in the handheld Download a copy of the data into the

handheld from the remote server and process it offline. Periodically merge the changes with the server

April 8, 2023 27

Synchronization -IssuesSynchronization -Issues

Data replication can lead to conflicts Update-update, Update-delete, Unique key violation,

Integrity constraint violation

Maintain global consistency between replicated copies Strict consistency with Data partitioning Strict consistency with Reservation protocols or Leases

Efficient when data is rarely shared

Weak consistency with Eventual consistency leases restrictive when data is shared between many copies

Independently access and update data

only tentative commits possible

Actual commit when transaction is executed at the server

April 8, 2023 28

ConclusionsConclusions

Handheld DBMS techniques have to consider the resource constraints, mobility, frequent disconnections, and security aspects of the handheld

The techniques used for one component will influence the choice of the technique used in another component. There is a very strong interdependence between the components of the handheld DBMS

Techniques rejected for the disk environment may be explored in the handheld environment

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Future workFuture work

Sync tool Transaction management component Recovery management component Concurrency control component Performance analysis of existing

compression techniques in handheld environment

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ReferencesReferences

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References (cont)References (cont)

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References (cont)References (cont)

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References (cont)References (cont)