ECL (data-centric programming language): Difference between revisions

Revision as of 11:35, 9 September 2013

Revision as of 11:55, 10 September 2013

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| name = ECL

| developer = [[HPCC|HPCC Systems]], LexisNexis Risk Solutions

| logo =

| paradigm = [[declarative programming|declarative]], [[structured]], [[Data-centric programming language|data-centric]]

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| latest release date =

| influenced_by = [[Prolog]], [[Pascal (programming language)|Pascal]], [[SQL]], [[Snobol4]], [[C++]], [[Clarion (programming language)|Clarion]]

| influenced = [[big data]]

| operating_system = [[Linux]]

| license =

| website = http://hpccsystems.com/

}}

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=== Hello world ===

ECL is to have succinct solutions to problems and sensible defaults. The ‘Hello"Hello World’World" program is characteristically short:

"Hello World".

‘Hello World’.

Perhaps a more flavorful example would take a list of strings, sort them into order, and then return that as a result instead.

<PREpre>

// First declare a dataset with one column containing a list of strings

// Datasets can also be binary, csvCSV, xmlXML or externally defined structures

D := DATASET([{'ECL'},{'Declarative'},{'Data'},{'Centric'},{'Programming'},{'Language'}],{STRING Value;});

SD := SORT(D,Value);

output(SD)

</PREpre>

The statements containing a <code>:=</code> are defined in ECL as attribute definitions. They do not denote an action; rather a definition of a term. Thus, logically, an ECL program can be read: “bottom"bottom to top”top"

OUTPUT(SD)

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D is a dataset with one column labeled ‘Value’ and containing the following list of data.

=== ECL Primitivesprimitives ===

ECL primitives that act upon datasets include: SORT, ROLLUP, DEDUP, ITERATE, PROJECT, JOIN, NORMALIZE, DENORMALIZE, PARSE, CHOSEN, ENTH, TOPN, DISTRIBUTE

=== ECL Encapsulationencapsulation ===

Whilst ECL is terse and LexisNexis claims that 1 line of ECL is roughly equivalent to 120 lines of C++ it still has significant support for large scale programming including data encapsulation and code re-use. The constructs available include: MODULE, FUNCTION, INTERFACE, MACRO, EXPORT, SHARED

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=== Comparison to Map-Reduce ===

The Hadoop Map-Reduce paradigm actually consists of three phases which correlate to ECL primitives as follows.

{| class="wikitable sortable" style="font-size: 90%; text-align: center; width: auto;"

|-

! Hadoop Name/Term

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! Comments

|-

!| MAPing within the MAPper

!| PROJECT/TRANSFORM

!| Takes a record and converts to a different format; in the [[Hadoop]] case the conversion is into a key-value pair

|-

!| SHUFFLE (Phase 1)

!| DISTRIBUTE(,HASH(KeyValue))

!| The records from the mapper are distributed dependent upon the KEY value

|-

!| SHUFFLE (Phase 2)

!| SORT(,LOCAL)

!| The records arriving at a particular reducer are sorted into KEY order

|-

!| REDUCE

!| ROLLUP(,Key,LOCAL)

!| The records for a particular KEY value are now combined together

|}