analytics/configuration/xqe/postgresql.properties

# Licensed Materials - Property of IBM
# IBM Cognos Products: OQP
# (C) Copyright IBM Corp. 2005, 2020
# US Government Users Restricted Rights - Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM corp.

#
# Delimiters.
#
# While a vendor may parse a statement with comments it may strip them out and the server not see them
delimiters.commentBegin=/*
delimiters.commentEnd=*/
# delimiters.catalogDelimiter=
# delimiters.schemaDelimiter=
# delimiters.tableDelimiter=
# delimiters.columnDelimiter=
# delimiters.identifierQuoteString=
# delimiters.searchStringEscape=
# delimiters.catalogSeparator=

#
# Keywords.
#
keywords.columnAlias=AS

#
# Various limits. A value of 0 means no limit, or the limit is unknown.
#
# Normally these values would be derived from the JDBC driver DatabaseMetadata
# limits.maxBinaryLiteralLength=
# limits.maxCharLiteralLength=
# limits.maxColumnNameLength=
# limits.maxColumnsInGroupby=
# limits.maxColumnsInIndex=
# limits.maxColumnsInOrderBy=
# limits.maxColumnsInSelect=
# limits.maxColumnsInTable=
# limits.maxConnections=
# limits.maxCursorNameLength=
# limits.maxIndexLength=
# limits.maxSchemaNameLength=
# limits.maxProcedureNameLength=
# limits.maxCatalogNameLength=
# limits.maxRowSize=
# limits.maxStatementLength=
# limits.maxStatements=
# limits.maxTableNameLength=
# limits.maxTablesInSelect=
# limits.maxUserNameLength=
# limits.defaultTransactionIsolation=
# limits.maxLengthInClause
limits.castClobToVarcharMaxSize=2000000

#
# General settings.
#
# 
# Null ordering
# 
# No support is provided for vendors who change how nulls sort based on data type.
general.nullsAreSortedAtEnd=false
general.nullsAreSortedAtStart=false
general.nullsAreSortedHigh=true
general.nullsAreSortedLow=false
general.nullsOrdering=true

#
# Override sampling policy with a different one.
# 1. tablesample accepting values such as BERNOULLI or SYSTEM
# 2. rowsample accepting values such as NTH or RANDOM
#
sampling.tablesample=BERNOULLI
sampling.rowsample=RANDOM

#
# Various features.
#
supports.columnAliasing=true
supports.tableCorrelationNames=true
supports.expressionsInOrderBy=true
supports.orderByAlias=true
supports.orderByName=true
supports.orderByOrdinal=true
supports.expressionsInINPredicate=true
supports.likeEscapeClause=true
supports.fullOuterJoins=true
supports.outerJoins=true
# Subquery column alias not supported
supports.subqueriesInComparisons=true
supports.subqueriesInExists=true
supports.subqueriesInIns=true
supports.subqueriesInQuantifieds=true
supports.subqueriesInCase=true
supports.correlatedSubqueries=true
supports.scalarSubqueries=true
supports.withClauseInDerivedTable=false
supports.nestedWithClause=true
supports.integerDivision=true
supports.nestedOlap=false
supports.derivedColumnLists=true
# Does not allow grouping on non project column
supports.blobsInGroupBy=false
supports.blobsInOrderBy=false
supports.emptyStringIsNull=false
supports.expressionsInGroupBy=true
supports.duplicateColumnsInSelectList=true
supports.expressionsInOrderBy=true
supports.aliasInOrderByExpression=false
supports.orderByUnrelated=true
supports.groupByUnrelated=false
supports.callProcedureInDerivedTable=false
supports.recursiveWithClause=false

supports.join.full.distinctJoins=false
supports.join.subqueriesInOnClause=false
#casting with formatting pattern support
supports.formatters.string_to_date=false
supports.formatters.string_to_time=false
supports.formatters.string_to_time_with_time_zone=false
supports.formatters.string_to_timestamp=false
supports.formatters.string_to_timestamp_with_time_zone=false

# After a cancel request, the db connection can no longer be used.
supports.connectionDroppedOnCancel=true

#
# Performance properties (force certain transformations to be applied). 
#
# If the RDBMS has costing/execution issues with group by or distinct consider these transforms
performance.convertGroupByToDistinct=false
performance.convertDistinctToGroupBy=false

# V5 master-detail optimization when allRows optimization is specified
v5.master-detail.transform=false

#
# Command.
#
commands.Select=SELECT
commands.Call= 

#
# Tables.
#
tables.joined=true
tables.derived=true

#
# Constructors.
#
constructors.table=true
constructors.row=true
constructors.array=true
constructors.period=false
constructors.row.simpleCase=true
constructors.row.between=true

#
# Clauses.
#
clauses.From=FROM
clauses.Where=WHERE
clauses.GroupBy=GROUP BY
clauses.Having=HAVING
# Recursive form of common table expression not supported
clauses.WithRecursive=
# Common table expression cannot be used within a derived table
clauses.With=WITH
clauses.OrderBy=ORDER BY
clauses.Distinct=DISTINCT
clauses.Top=LIMIT %1$s 
clauses.At=
clauses.Window=
clauses.ForSystemTimeAsOf=
clauses.ForSystemTimeFrom=
clauses.ForSystemTimeBetween=

#
# Joins.
#
# Does not allow non equi joins in full outer join
joins.Cross=%1$s CROSS JOIN %2$s
joins.Inner=%1$s INNER JOIN %2$s ON %3$s
joins.LeftOuter=%1$s LEFT OUTER JOIN %2$s ON %3$s
joins.RightOuter=%1$s RIGHT OUTER JOIN %2$s ON %3$s
joins.FullOuter=%1$s FULL OUTER JOIN %2$s ON %3$s

#
# Set operators.
#
# One or more set operations does not follow ISO data type combination rules. Can effect set operations, CASE, COALESCE...
operators.set.Union=%1$s UNION %2$s
operators.set.Union.all=%1$s UNION ALL %2$s
operators.set.Intersect=%1$s INTERSECT %2$s
operators.set.Intersect.all=%1$s INTERSECT ALL %2$s
operators.set.Except=%1$s EXCEPT %2$s
operators.set.Except.all=%1$s EXCEPT ALL %2$s

#
# Logical operators.
#
operators.logical.And=%1$s AND %2$s
operators.logical.Or=%1$s OR %2$s
operators.logical.Not=NOT ( %1$s )

#
# Arithmetic operators.
#
operators.arithmetic.Add[any,any]=%1$s + %2$s
operators.arithmetic.Subtract[any,any]=%1$s - %2$s
operators.arithmetic.Subtract[datetime,datetime]=
operators.arithmetic.Multiply[any,any]=%1$s * %2$s
# Division may return a precise type if expression not coerced to imprecise type
operators.arithmetic.Divide[any,any]=%1$s / %2$s
operators.arithmetic.UnaryPlus[any]=+%1$s
operators.arithmetic.Negate[any]=-%1$s
operators.arithmetic.Concat[any,any]=(%1$s || %2$s)
operators.arithmetic.Concat[char,any]=

#
# Group By Operators
#
operators.groupBy.Rollup= 
operators.groupBy.Cube= 
operators.groupBy.GroupingSets= 

#
# Comparison predicates.
#
predicates.comparison.Equals[any,any]=%1$s = %2$s
predicates.comparison.GreaterThan[any,any]=%1$s > %2$s
predicates.comparison.GreaterThanOrEquals[any,any]=%1$s >= %2$s
predicates.comparison.LessThan[any,any]=%1$s < %2$s
predicates.comparison.LessThanOrEquals[any,any]=%1$s <= %2$s
predicates.comparison.NotEquals[any,any]=%1$s <> %2$s

#
# Various predicates.
#
predicates.Between[any,any,any]=%1$s BETWEEN %2$s AND %3$s
predicates.In[any,any]=%1$s IN ( %2$s )
predicates.Overlaps[any,any,any,any]=(%1$s, %2$s) OVERLAPS (%3$s, %4$s)
predicates.IsNull=%1$s IS NULL
predicates.IsNotNull=%1$s IS NOT NULL
predicates.Like=%1$s LIKE %2$s
predicates.Like.escape=%1$s LIKE %2$s ESCAPE %3$s
predicates.LikeRegex=
predicates.LikeRegex.flag=
predicates.Similar=
predicates.Similar.escape= 
predicates.Exists=EXISTS %1$s
predicates.All=ALL %1$s
predicates.Any=
predicates.Some=SOME %1$s
predicates.IsDistinctFrom[any,any]=%1$s IS DISTINCT FROM %2$s
predicates.IsNotDistinctFrom[any,any]=%1$s IS NOT DISTINCT FROM %2$s

#
# Period predicates.
#
predicates.PeriodOverlaps[any,any]=
predicates.PeriodEquals[any,any]=
predicates.PeriodContains[any,any]=
predicates.PeriodPrecedes[any,any]=
predicates.PeriodSucceeds[any,any]=
predicates.PeriodImmediatelyPrecedes[any,any]=
predicates.PeriodImmediatelySucceeds[any,any]=

#
# Expressions.
#
expressions.ArrayElementRef.zeroBased=false

# 
# Conditional expressions
# 
# One or more case operations does not follow ISO type rules.
expressions.SimpleCase=CASE
expressions.SearchedCase=CASE
expressions.Coalesce=COALESCE(%1$s)
expressions.NullIf=NULLIF(%1$s, %2$s)

#
# Cast expression.
#
# Cast of non-numeric to character types may produce wrong literal
expressions.Cast[any,any]=CAST(%1$s AS %2$s)
expressions.Cast[decimal,integer]=CAST(TRUNC(%1$s) AS INTEGER)
expressions.Cast[double,integer]=CAST(TRUNC(%1$s) AS INTEGER)
expressions.Cast[float,integer]=CAST(TRUNC(%1$s) AS INTEGER)
expressions.Cast[smallint,clob]=
expressions.Cast[integer,clob]=
expressions.Cast[long,float]=
expressions.Cast[long,clob]=
expressions.Cast[decimal,clob]=
expressions.Cast[decimal,float]=
expressions.Cast[float,char]=
expressions.Cast[float,varchar]=
expressions.Cast[float,clob]=
expressions.Cast[double,char]=
expressions.Cast[double,varchar]=
expressions.Cast[double,clob]=
expressions.Cast[float,float]=
expressions.Cast[char,float]=
expressions.Cast[char,varchar]=
expressions.Cast[char,clob]=
expressions.Cast[varchar,float]=
expressions.Cast[varchar,clob]=
expressions.Cast[clob,smallint]=
expressions.Cast[clob,integer]=
expressions.Cast[clob,long]=
expressions.Cast[clob,decimal]=
expressions.Cast[clob,float]=
expressions.Cast[clob,double]=
expressions.Cast[clob,char]=
expressions.Cast[clob,varchar]=
expressions.Cast[clob,clob]=
expressions.Cast[clob,date]=
expressions.Cast[clob,time]=
expressions.Cast[clob,timestamp]=
expressions.Cast[date,clob]=
expressions.Cast[time,char]=
expressions.Cast[time,varchar]=
expressions.Cast[time,clob]=
expressions.Cast[time,time]=
expressions.Cast[time,timestamp]=
expressions.Cast[time_with_time_zone,timestamp]=
expressions.Cast[timestamp,char]=
expressions.Cast[timestamp,varchar]=
expressions.Cast[timestamp,clob]=
expressions.Cast[timestamp,time]=

#
# Extract expression.
#
expressions.Extract.YEAR[any]=CAST(EXTRACT(YEAR FROM %1$s) AS BIGINT)
expressions.Extract.MONTH[any]=CAST(EXTRACT(MONTH FROM %1$s) AS BIGINT)
expressions.Extract.DAY[any]=CAST(EXTRACT(DAY FROM %1$s) AS BIGINT)
expressions.Extract.HOUR[any]=CAST(EXTRACT(HOUR FROM %1$s) AS BIGINT)
expressions.Extract.MINUTE[any]=CAST(EXTRACT(MINUTE FROM %1$s) AS BIGINT)
expressions.Extract.SECOND[any]=EXTRACT(SECOND FROM %1$s)
expressions.Extract.TIMEZONE_HOUR[any]=CAST(EXTRACT(TIMEZONE_HOUR FROM %1$s) AS BIGINT)
expressions.Extract.TIMEZONE_MINUTE[any]=CAST(EXTRACT(TIMEZONE_MINUTE FROM %1$s) AS BIGINT)

#
# Trim expression.
#
expressions.Trim.BOTH[any]=TRIM(BOTH FROM %1$s)
expressions.Trim.LEADING[any]=TRIM(LEADING FROM %1$s)
expressions.Trim.TRAILING[any]=TRIM(TRAILING FROM %1$s)
expressions.Trim.BOTH[any,any]=TRIM(BOTH %1$s FROM %2$s)
expressions.Trim.LEADING[any,any]=TRIM(LEADING %1$s FROM %2$s)
expressions.Trim.TRAILING[any,any]=TRIM(TRAILING %1$s FROM %2$s)

#
# Windowed aggregates (SQL/OLAP).
#
olap.Min[string]=MIN(%1$s)
olap.Min[xml]= 
olap.Min[datetime]=MIN(%1$s)
olap.Min[varchar]=MIN(%1$s)
olap.Min[numeric]=MIN(%1$s)
olap.Min[blob]=MIN(%1$s)
olap.Max[string]=MAX(%1$s)
olap.Max[xml]= 
olap.Max[datetime]=MAX(%1$s)
olap.Max[varchar]=MAX(%1$s)
olap.Max[numeric]=MAX(%1$s)
olap.Max[blob]=MAX(%1$s)
olap.Sum[any]=SUM(%1$s)
olap.Avg[any]=AVG(%1$s)
olap.Count[any]=COUNT(%1$s)
olap.CountStar[]=COUNT(*)
olap.FirstValue[any]=FIRST_VALUE(%1$s)
olap.LastValue[any]=LAST_VALUE(%1$s)
# Olap lag did not throw expected exceptions
olap.Lag[any]=LAG(%1$s)
olap.Lag[any,any]=LAG(%1$s, %2$s)
# Postgres does not expose respect or ignore nulls
olap.Lag[any,any,any]=
olap.Lag[any,any,any,any]=
# Olap lead did not throw expected exceptions
olap.Lead[any]=LEAD(%1$s)
olap.Lead[any,any]=LEAD(%1$s, %2$s)
# Postgres does not expose respect or ignore nulls
olap.Lead[any,any,any]=
olap.Lead[any,any,any,any]=
# Olap Nth value did not throw expected exceptions
olap.NTile[any]=NTILE(%1$s)
olap.NthValue[any,any]=
olap.NthValue[any,any,any]=
olap.NthValue[any,any,any,any]=
olap.PercentileCont[any,any]=
olap.PercentileDisc[any,any]=
olap.Median[any]=
olap.Tertile[]=
olap.Rank[]=RANK()
olap.DenseRank[]=DENSE_RANK()
olap.PercentRank[]=PERCENT_RANK()
olap.CumeDist[]=CUME_DIST()
olap.RatioToReport[any]=
olap.RowNumber[]=ROW_NUMBER()
olap.Difference[any]=
olap.Collect[any]=

#
# Window clause.
#
olap.PartitionBy=PARTITION BY %1$s
general.nullsOrderingInWindowSpecification=true
olap.OrderBy=ORDER BY %1$s

# 
# Window specification
# 
olap.Window.Specification[POF]=true
olap.Window.Specification[PF]=true
olap.Window.Specification[OF]=true
olap.Window.Specification[PO]=true
olap.Window.Specification[P]=true
olap.Window.Specification[O]=false
olap.Window.Specification[F]=true
olap.Window.Specification[]=true

#
# Olap (distinct).
#
olap.Min.distinct[any]= 
olap.Max.distinct[any]= 
olap.Sum.distinct[any]= 
olap.Avg.distinct[any]= 
olap.Count.distinct[any]= 

#
# Aggregates.
#
aggregates.Max[any]=MAX(%1$s)
aggregates.Max[boolean]=
aggregates.Min[any]=MIN(%1$s)
aggregates.Min[boolean]=
aggregates.Count[any]=COUNT(%1$s)
aggregates.CountStar[]=COUNT(*)
aggregates.Sum[any]=SUM(%1$s)
aggregates.Avg[any]=AVG(%1$s)
aggregates.StdDevPop[any]=
aggregates.StdDevSamp[any]=STDDEV_SAMP(%1$s)
aggregates.VarPop[any]=VAR_POP(%1$s)
aggregates.VarSamp[any]=VAR_SAMP(%1$s)
# treats zero length and blank as equal
aggregates.Rank[any,any]=
aggregates.DenseRank[any,any]=
aggregates.PercentRank[any,any]=PERCENT_RANK(%1$s) WITHIN GROUP (ORDER BY %2$s)
aggregates.CumeDistH[any,any]=
aggregates.PercentileCont[any,any]=PERCENTILE_CONT(%1$s) WITHIN GROUP (ORDER BY %2$s)
aggregates.PercentileDisc[any,any]=PERCENTILE_DISC(%1$s) WITHIN GROUP (ORDER BY %2$s)
aggregates.Median[any]=
aggregates.Grouping[any]=
aggregates.XMLAgg=
aggregates.Collect[any]=
aggregates.ApproxCountDistinct[any]=

#
# Aggregates (distinct).
#
aggregates.Avg.distinct[any]=AVG(DISTINCT %1$s)
aggregates.Min.distinct[any]=MIN(DISTINCT %1$s)
aggregates.Max.distinct[any]=MAX(DISTINCT %1$s)
aggregates.Count.distinct[any]=COUNT(DISTINCT %1$s)
aggregates.Sum.distinct[any]=SUM(DISTINCT %1$s)

#
# Linear regression aggregates.
#
aggregates.Corr[any,any]=CORR(%1$s, %2$s)
aggregates.CovarPop[any,any]=COVAR_POP(%1$s, %2$s)
aggregates.CovarSamp[any,any]=COVAR_SAMP(%1$s, %2$s)
aggregates.RegrAvgX[any,any]=REGR_AVGX(%1$s, %2$s)
aggregates.RegrAvgY[any,any]=REGR_AVGY(%1$s, %2$s)
aggregates.RegrCount[any,any]=REGR_COUNT(%1$s, %2$s)
aggregates.RegrIntercept[any,any]=REGR_INTERCEPT(%1$s, %2$s)
aggregates.RegrR2[any,any]=REGR_R2(%1$s, %2$s)
aggregates.RegrSlope[any,any]=REGR_SLOPE(%1$s, %2$s)
aggregates.RegrSXX[any,any]=REGR_SXX(%1$s, %2$s)
aggregates.RegrSXY[any,any]=REGR_SXY(%1$s, %2$s)
aggregates.RegrSYY[any,any]=REGR_SYY(%1$s, %2$s)

#
# JSON aggregates.
#
aggregates.JSONArrayAgg=
aggregates.JSONObjectAgg=

#
# Character scalar functions.
#
# Upper does not support character lobs
functions.Upper[any]=UPPER(%1$s)
# Lower does not support character lobs
functions.Lower[any]=LOWER(%1$s)
functions.CharLength[any]=
functions.OctetLength[any]=
functions.BitLength[any]=
functions.Substring[any,any]=SUBSTRING(%1$s FROM %2$s)
functions.Substring[any,any,any]=SUBSTRING(%1$s FROM %2$s FOR %3$s)
functions.Position[any,any]=POSITION(%1$s IN %2$s)
functions.Index[any,any]=
functions.Ascii[any]=
functions.Translate[any,any]=
functions.Normalize[any]=
functions.Normalize[any,any]=
functions.Normalize[any,any,any]=

#Substring function to negative START value to parse the input string from its rightmost end.
functions.SubstringR[any,any]=CASE WHEN (%2$s) < 0 THEN (SUBSTRING( %1$s FROM  (CHAR_LENGTH(%1$s ) - ABS(%2$s) + 1))) ELSE (SUBSTRING(%1$s FROM  %2$s)) END
functions.SubstringR[any,any,any]=CASE WHEN (%2$s) < 0 THEN (SUBSTRING( %1$s FROM  (CHAR_LENGTH(%1$s ) - ABS(%2$s) + 1) FOR %3$s)) ELSE (SUBSTRING(%1$s FROM  %2$s FOR %3$s)) END

#
# Regular expression functions.
#
functions.SubstringRegex[any,any,any,any,any]=
functions.OccurrencesRegex[any,any,any,any]=
functions.PositionRegex[any,any,any,any,any,any]=

#
# Numeric scalar functions.
#
functions.Abs[any]=ABS(%1$s)
functions.Abs[interval_day_time]=
functions.Abs[interval_year_month]=
functions.Ceiling[any]=CEIL(%1$s)
functions.Exp[double]=EXP(%1$s)
functions.Exp[decimal]= 
functions.Exp[smallint]=EXP(%1$s)
functions.Exp[long]=EXP(%1$s)
functions.Exp[float]=EXP(%1$s)
functions.Exp[integer]=EXP(%1$s)
functions.Floor[any]=FLOOR(%1$s)
functions.Ln[any]=LN(%1$s)
functions.Log10[any]=
functions.Mod[any,any]=MOD(%1$s, %2$s)
functions.Random[]=RANDOM()
functions.Random[any]=
functions.Round[any]=ROUND(%1$s)
functions.Round[any,any]=ROUND(%1$s, %2$s)
functions.Round[double,any]=CASE WHEN (%1$s) < 0 THEN (CAST( ( (%1$s) * POWER( 10e0, (%2$s) ) - 0.1 ) AS BIGINT ) / POWER( 10e0, (%2$s) ) ) ELSE (CAST( ( (%1$s) * POWER( 10e0, (%2$s) ) + 0.1 ) AS BIGINT ) / POWER( 10e0, (%2$s) ) ) END
functions.Round[float,any]=CASE WHEN (%1$s) < 0 THEN (CAST( ( (%1$s) * POWER( 10e0, (%2$s) ) - 0.1 ) AS BIGINT ) / POWER( 10e0, (%2$s) ) ) ELSE (CAST( ( (%1$s) * POWER( 10e0, (%2$s) ) + 0.1 ) AS BIGINT ) / POWER( 10e0, (%2$s) ) ) END
functions.Round[any,any,any]=
functions.Sign[any]=SIGN(%1$s)
functions.Sqrt[any]=SQRT(%1$s)
functions.WidthBucket[any,any,any,any]=WIDTH_BUCKET(%1$s, %2$s, %3$s, %4$s)

#
# Array scalar functions.
#
functions.Cardinality[any]=CARDINALITY(%1$s)
functions.TrimArray[any,any]=

#
# Trigonometric functions.
#
functions.Arccos[any]=ACOS(%1$s)
functions.Arcsin[any]=ASIN(%1$s)
functions.Arctan[any]=ATAN(%1$s)
functions.Cos[any]=COS(%1$s)
functions.Coshyp[any]= 
functions.Sin[any]=SIN(%1$s)
functions.Sinhyp[any]= 
functions.Tan[any]=TAN(%1$s)
functions.Tanhyp[any]= 

#
# Datetime value functions.
#
# Note: JDBC does not define fractional seconds for TIME data type.
functions.CurrentDate[]=CURRENT_DATE
functions.CurrentTime[]=
functions.CurrentTimestamp[]=CURRENT_TIMESTAMP
functions.CurrentTimestamp[numeric]= 
functions.LocalTime[]=LOCALTIME
functions.LocalTimestamp[]=LOCALTIMESTAMP
functions.LocalTime[numeric]=
functions.LocalTimestamp[numeric]=

#
# XML functions.
#
functions.XMLAttributes=
functions.XMLComment=
functions.XMLConcat=
functions.XMLDocument=
functions.XMLElement=
functions.XMLExists=
functions.XMLForest=
functions.XMLParse=
functions.XMLPI=
functions.XMLNamespaces=
functions.XMLQuery=
functions.XMLSerialize=
functions.XMLTable=
functions.XMLText=
functions.XMLTransform=
functions.XMLValidate=

#
# JSON functions.
#
functions.JSONArray=
functions.JSONExists=
functions.JSONObject=
functions.JSONQuery=
functions.JSONTable=
functions.JSONValue=

#
# Business date functions.
#
functions.AddFractionalSeconds[any,any]=
functions.AddSeconds[any,any]=(%1$s + (INTERVAL '1 second' * FLOOR(%2$s)))
functions.AddMinutes[any,any]=(%1$s + (INTERVAL '1 minute' * FLOOR(%2$s)))
functions.AddHours[any,any]=(%1$s + (INTERVAL '1 hour' * FLOOR(%2$s)))
functions.AddDays[any,any]=(%1$s + (interval '1' day * floor(%2$s)))
functions.AddDays[date,any]=(cast(%1$s + interval '1' day * floor(%2$s) as date))
functions.AddWeeks[any,any]=(%1$s + (interval '7 day' * floor(%2$s)))
functions.AddWeeks[date,any]=(cast(%1$s + interval '7 day' * floor(%2$s) as date))
functions.AddMonths[any,any]=(%1$s + (interval '1 month' * floor(%2$s)))
functions.AddMonths[date,any]=(cast(%1$s + (interval '1 month' * floor(%2$s)) as date))
functions.AddQuarters[any,any]=(%1$s + (interval '3 month' * floor(%2$s)))
functions.AddQuarters[date,any]=(cast(%1$s + (interval '3 month' * floor(%2$s)) as date))
functions.AddYears[any,any]=(%1$s + (interval '1 year' * floor(%2$s)))
functions.AddYears[date,any]=cast(%1$s + (interval '1 year' * floor(%2$s)) as date)
functions.FractionalSecondsBetween[any,any]=
functions.SecondsBetween[any,any]=extract('epoch' from %2$s - %1$s )
functions.MinutesBetween[any,any]=cast(extract('epoch' from %2$s - %1$s ) /60 as integer)
functions.HoursBetween[any,any]=cast(extract('epoch' from %2$s - %1$s ) / 3600 as integer)
functions.WeeksBetween[any,any]=
functions.MonthsBetween[any,any]=
functions.QuartersBetween[any,any]=
functions.YearsBetween[any,any]=((extract(year from %1$s) - extract(year from %2$s)))
functions.Age[any]=cast(extract('year' from age( %1$s)) * 10000 + extract('month' from age( %1$s )) * 100 + extract('day' from age( %1$s )) as integer)
functions.DayOfWeek[any,any]=(mod(cast(extract(dow from %1$s) +7-%2$s as int),7)+1)
functions.DayOfYear[any]=cast(extract(doy from %1$s) as integer)
functions.DaysBetween[any,any]=(cast(%1$s as date) - cast(%2$s as date))
functions.DaysToEndOfMonth[any]=cast(extract('day' from ((date_trunc('month',%1$s) + interval '1 month' - interval '1 day') - cast(%1$s as date) )) as integer)
functions.FirstOfMonth[any]=(%1$s - ( EXTRACT( DAY FROM %1$s ) * INTERVAL '1 DAY' ) + INTERVAL '1 DAY')
functions.LastOfMonth[any]=(%1$s - ( EXTRACT( DAY FROM %1$s ) * INTERVAL '1 DAY' ) + INTERVAL '1 DAY' + INTERVAL '1 MONTH' - INTERVAL '1 DAY')
functions.MakeTimestamp[any,any,any]=cast(TO_TIMESTAMP(%1$s || '-' || %2$s || '-' || %3$s,'YYYY-MM-DD') as timestamp without time zone)
functions.WeekOfYear[any]=extract(week from %1$s)
functions.YMDIntBetween[any,any]=

#
# Table functions.
#

#
# Literals.
#
literals.integer=true
literals.smallint=true
literals.long=true
literals.decimal=true
literals.float=true
literals.double=true
literals.char=true
literals.nchar=true
literals.varchar=true
literals.nvarchar=true
literals.clob=true
literals.date=true
literals.time=true
literals.time_with_time_zone=true
literals.timestamp=true
literals.timestamp_with_time_zone=true
literals.interval_year=false
literals.interval_month=false
literals.interval_year_to_month=false
literals.interval_day=false
literals.interval_hour=false
literals.interval_minute=false
literals.interval_second=false
literals.interval_day_to_hour=false
literals.interval_day_to_minute=false
literals.interval_day_to_second=false
literals.interval_hour_to_minute=false
literals.interval_hour_to_second=false
literals.interval_minute_to_second=false
literals.date=true
literals.time=true
literals.time_with_time_zone=true
literals.timestamp=true
literals.timestamp_with_time_zone=true
literals.binary=false
literals.boolean=true
literals.xml=true

#
# Literal constraints.
#

#
# Literal format specifications. Formats are compatible with String.format().
# Values for default behaviour are listed.
# Only char, temporal and string types can be overridden.
# Fractional seconds are presented as a string of up to 10 characters: '.' followed by 9 character
# 0-padded string representing nanoseconds or empty.
literals.format.boolean=TRUE:FALSE:UNKNOWN
literals.format.char=char '%s'
literals.format.clob=text '%s'
literals.format.date=DATE '%1$04d-%2$02d-%3$02d'
literals.format.interval_day=INTERVAL %3$s'%1$d' DAY
literals.format.interval_day_to_hour=INTERVAL %4$s'%1$d %2$d' DAY TO HOUR
literals.format.interval_day_to_minute=INTERVAL %5$s'%1$d %2$02d:%3$02d' DAY TO MINUTE
literals.format.interval_day_to_second=INTERVAL %8$s'%1$d %2$02d:%3$02d:%4$02d%5$.10s' DAY TO SECOND
literals.format.interval_hour=INTERVAL %3$s'%1$d' HOUR
literals.format.interval_hour_to_minute=INTERVAL %4$s'%1$02d:%2$02d' HOUR TO MINUTE
literals.format.interval_hour_to_second=INTERVAL %7$s'%1$02d:%2$02d:%3$02d%4$.10s' HOUR TO SECOND
literals.format.interval_minute=INTERVAL %3$s'%1$d' MINUTE
literals.format.interval_minute_to_second=INTERVAL %6$s'%1$02d:%2$02d%3$.10s' MINUTE TO SECOND
literals.format.interval_month=INTERVAL %3$s'%1$d' MONTH
literals.format.interval_second=INTERVAL %3$s'%1$d%2$.10s' SECOND
literals.format.interval_year=INTERVAL %3$s'%1$d' YEAR
literals.format.interval_year_to_month=INTERVAL %4$s'%1$d-%2$d' YEAR TO MONTH
literals.format.nchar=N'%s'
literals.format.nvarchar=N'%s'
literals.format.time=TIME '%1$02d:%2$02d:%3$02d%4$.10s'
literals.format.time_with_time_zone=TIMETZ '%1$02d:%2$02d:%3$02d%4$.10s%7$c%5$02d:%6$02d'
literals.format.timestamp=TIMESTAMP '%1$04d-%2$02d-%3$02d %4$02d:%5$02d:%6$02d%7$.10s'
literals.format.timestamp_with_time_zone=TIMESTAMPTZ '%1$04d-%2$02d-%3$02d %4$02d:%5$02d:%6$02d%7$.10s%10$c%8$02d:%9$02d'
literals.format.varchar=varchar '%s'

#
# Data types.
#
dataType.smallint=true
dataType.integer=true
dataType.long=true
dataType.decimal=true
dataType.float=true
dataType.double=true
dataType.char=true
dataType.nchar=false
dataType.varchar=true
dataType.nvarchar=false
dataType.clob=true
dataType.blob=false
dataType.date=true
dataType.time=true
dataType.time_with_time_zone=false
dataType.timestamp=true
dataType.timestamp_with_time_zone=false
dataType.interval_year=false
dataType.interval_month=false
dataType.interval_year_to_month=false
dataType.interval_day=false
dataType.interval_hour=false
dataType.interval_minute=false
dataType.interval_second=false
dataType.interval_day_to_hour=false
dataType.interval_day_to_minute=false
dataType.interval_day_to_second=false
dataType.interval_hour_to_minute=false
dataType.interval_hour_to_second=false
dataType.interval_minute_to_second=false
dataType.boolean=true
dataType.binary=false
dataType.xml=true
dataType.period=false

# 
# Collation
# 
# Collation Sequence SQL (SQL statement for retrieving the collation sequence)
# This statement returns a single row and single column containing the collation sequence
collation.sequence.sql=
# Datbase Encoding SQL. This statement retrieves the charset name for the non-unicode character data.
# This statement returns a single row and single column with the charset name for use in a java.nio.CharsetEncoder.
database.charset.sql=

# 
# dataType.comparable
# 
# Used to indicate that some data types that are comparable locally may not by the database
# e.g. dataType.comparable[varchar,nvarchar]=false

# 
# dataType.promotion
# 
# Used to indicate what direction the promotion needs to occur
# <lhs> -> <rhs> these properties are not symetrical
# e.g. dataType.promotion[char,nvarchar]=true

#
# Database functions hacks
#
functions.overlay[any,any,any,any]=overlay(%1$s placing %2$s from %3$s for %4$s)
functions.overlay[any,any,any]=overlay(%1$s placing %2$s from %3$s)