Following is the simple MDX query with one cross join.

WITH
SET [~FILTER] AS
{[Time.Date].[2016].[January].[2016Q1].[1], [Time.Date].[2016].[January].[2016Q1].[2], [Time.Date].[2016].[January].[2016Q1].[3], [Time.Date].[2016].[January].[2016Q1].[4], [Time.Date].[2016].[February].[2016Q1].[6]}
SET [~ROWS_Sku_Sku.Sku] AS
{[Sku].[Sku_ID].Members}
SET [~ROWS_Location_Location.default] AS
{[Location.default].[Location_ID].Members}
SELECT
{[Measures].[Total_QTY]} ON COLUMNS,
CrossJoin([~ROWS_Sku_Sku.Sku], [~ROWS_Location_Location.default]) ON ROWS
FROM [TCS_CUBE]
WHERE [~FILTER]

IF I remove filter then also it fire multiple SQL query with in clause. Can any one provide some solution and tell me why this issue happening. Also I want to know which version of pentaho CE and mondrian is stable ? So i can able to use that.

SQL Queries :

select `store_locations`.`id` as `c0`, `dim_date`.`calendar_quarter` as `c1`, `dim_date`.`week_of_year` as `c2`, `sku_master`.`id` as `c3`, sum(`sales_fact_2`.`qty`) as `m0` from `store_locations` as `store_locations`, `sales_fact_2` as `sales_fact_2`, `dim_date` as `dim_date`, `sku_master` as `sku_master` where `sales_fact_2`.`store_location_id` = `store_locations`.`id` and `sales_fact_2`.`date_id` = `dim_date`.`date_key` and `dim_date`.`calendar_quarter` = 1 and `dim_date`.`week_of_year` in (1, 2, 3, 4, 6) and `sales_fact_2`.`sku_id` = `sku_master`.`id` and `sku_master`.`id` in ('4929', '4930', '4931', '4932', '4933', '4934', '4935', '4936', '4937', '4938', '4939', '4940', '4941', '4942', '4943', '4944', '4945', '4946', '4947', '4948', '4949', '4950', '4951', '4952', '4953', '4955', '4958', '4959', '4960', '4961', '4962', '4963', '4964', '4965', '4966', '4967', '4968', '4969', '4970', '4972', '4973', '4974', '4975', '4976', '4977', '4978', '4979', '4980', '4981', '4982', '4983', '4984', '4986', '4987', '4988', '4989', '4991', '4992', '4993', '4994', '4998', '4999', '5001', '5002', '5003', '5004', '5005', '5006', '5007', '5008', '5009', '5010', '5011', '5012', '5014', '5015', '5017', '5018', '5019', '5020', '5021', '5022', '5023', '5024', '5025', '5026', '5027', '5028', '5029', '5030', '5031', '5032', '5034', '5037', '5038', '5039', '5040', '5041', '5042', '5043', '5044', '5045', '5046', '5047', '5052', '5054', '5056', '5057', '5059', '5063', '5066', '5068', '5069', '5070', '5071', '5076', '5077', '5078', '5081', '5082', '5083', '5084', '5085', '5086', '5087', '5088', '5089', '5090', '5091', '5092', '5095', '5096', '5097', '5098', '5099', '5100', '5102', '5103', '5104', '5106', '5108', '5110', '5111', '5112', '5113', '5114', '5115', '5116', '5117', '5118', '5119', '5120', '5122', '5123', '5125', '5127', '5128', '5129', '5130', '5131', '5132', '5133', '5134', '5135', '5136', '5137', '5138', '5139', '5140', '5141', '5142', '5143', '5144', '5145', '5146', '5147', '5148', '5149', '5150', '5151', '5152', '5153', '5154', '5155', '5156', '5157', '5158', '5159', '5160', '5161', '5162', '5163', '5164', '5165', '5166', '5167', '5168', '5169', '5170', '5171', '5172', '5173', '5174', '5175', '5176', '5178', '5179', '5180', '5181', '5182', '5184') group by `store_locations`.`id`, `dim_date`.`calendar_quarter`, `dim_date`.`week_of_year`, `sku_master`.`id`